Ozone and grosswetterlagen

Meteorological conditions have a decisive impact on surface ozone concentrations. In this study, an empirical model is used to explain the interdependence of ozone and grosswetterlagen. Different meteorological parameters such as air temperature, global solar radiation, relative humidity, wind direction and wind speed are used. Additional nitric oxide (NO) was taken as a representative for the emission situation and ozone maximum of the preceding day in order to evaluate the development of the photochemical situation. The dataset includes data collected over a period of three years (1992–1994) from three stations outside of Munich and one in the center of Munich. All values become variables by calculating means, sums or maxima of the basic dataset consisting of half-hour means. Seasonal periodicity of data is detected with Fourier analysis and eliminated by a division method after computing a seasonal index. The dataset is divided into three different grosswetterlagen groups, depending on main wind direction. One mostly cyclonic (westerly winds), onemixed (alternating winds) and one onlyanticyclonic (easterly winds). The last is completed with one summertime group including values from April to August. Factor analysis is performed for each group to obtain independent linear variable combinations. Overall, relative humidity is the dominant parameter, a typical value indicating meteorological conditions during a grosswetterlage. Linear multiple regression analysis is performed using the factors obtained to reveal how the ozone concentrations are explained in terms of meteorological parameters and NO. The results improve from cyclonic to anticyclonic grosswetterlagen in conformance with the increasing significance of photochemistry, indicated by the high solar radiation and high temperature, and the low relative humidity and low wind speed. The explained variance r² reaches its maximum with more than 50 % of the time in Munich center. This empirical model is applicable to the forecasting of local ozone maximum concentrations with a total standard error deviation of 8.5 to 12.8 % and, if ozone concentrations exceed 80 ppb, with a standard error deviation of 5.4 to 9.5 %.     

Ozone and grosswetterlagen

Meteorological conditions have a decisive impact on surface ozone concentrations. In this study, an empirical model is used to explain the interdependence of ozone and grosswetterlagen. Different meteorological parameters such as air temperature, global solar radiation, relative humidity, wind direction and wind speed are used. Additional nitric oxide (NO) was taken as a representative for the emission situation and ozone maximum of the preceding day in order to evaluate the development of the photochemical situation. The dataset includes data collected over a period of three years (1992–1994) from three stations outside of Munich and one in the center of Munich. All values become variables by calculating means, sums or maxima of the basic dataset consisting of half-hour means. Seasonal periodicity of data is detected with Fourier analysis and eliminated by a division method after computing a seasonal index. The dataset is divided into three different grosswetterlagen groups, depending on main wind direction. One mostly cyclonic (westerly winds), one mixed (alternating winds) and one only anticyclonic (easterly winds). The last is completed with one summertime group including values from April to August. Factor analysis is performed for each group to obtain independent linear variable combinations. Overall, relative humidity is the dominant parameter, a typical value indicating meteorological conditions during a grosswetterlage. Linear multiple regression analysis is performed using the factors obtained to reveal how the ozone concentrations are explained in terms of meteorological parameters and NO. The results improve from cyclonic to anticyclonic grosswetterlagen in conformance with the increasing significance of photochemistry, indicated by the high solar radiation and high temperature, and the low relative humidity and low wind speed. The explained variance r² reaches its maximum with more than 50 % of the time in Munich center. This empirical model is applicable to the forecasting of local ozone maximum concentrations with a total standard error deviation of 8.5 to 12.8 % and, if ozone concentrations exceed 80 ppb, with a standard error deviation of 5.4 to 9.5 %.     

Peroxyacetylnitrate (PAN) in the atmosphere of Edmonton,Alberta, Canada

Peroxyacetyl nitrate (PAN) concentrations were measured from December 1982 to May 1984 in downtown Edmonton, Alberta, as well as upwind and downwind of the city. The highest PAN concentration recorded in Edmonton was 7.5 ppb, and the mean daily maximum was 0.6 ppb. Maximum PAN and ozone concentrations were often reached in the early afternoon but there were many exceptions, with maxima as early as 0900 MST and as late as 2000 MST. PAN often persisted throughout the night in Edmonton, whereas in Calgary it disappeared rapidly in the evening. Edmonton PAN concentrations showed seasonal variation and were limited in the wintertime by the lack of solar radiation and in the summer by the low concentration of pollutants. PAN episodes were highly correlated with the presence of anticyclonic synoptic disturbances (ridges) in the upper air flow. Surface synoptic conditions varied but weak pressure gradients were common to all episodes. Seasonal and diurnal variations of PAN are discussed in relation to observations from Calgary, Alberta; Los Angeles, CA; and other North American cities.     

Emissions of liquefied petroleum gas (LPG) from motor vehicles

Continuous on-site measurements of 50 speciated volatile organic compounds (VOCs) were conducted in downtown Guangzhou to characterize the sources and concentration profiles of ambient VOCs. The synchronicity in diurnal variation between the VOCs and NO suggests that traffic emissions were responsible for the observed VOCs in downtown Guangzhou.It was found that the three major constituent species of liquefied petroleum gas (LPG), i.e., propane, iso-butane, and n-butane, together termed LPG alkanes, contributed, on average, 24% of the total VOCs (TVOCs). Their high correlation and synchronized diurnal variations between NO and the LPG alkanes suggest that their origin lies in LPG fueled car exhaust in Guangzhou. LPG buses and taxis were likely to be responsible for the bulk of ambient LPG species. Using propane and 3-methyl pentane (3MC5A) as the indicators for the LPG and gasoline emissions, respectively, the emissions of the LPG fleet were found to increase more than those of the gasoline fleet during the morning and evening rush hours, as well the noontime break in downtown Guangzhou.Although LPG alkanes account for 24% of the TVOC, their contribution to the total ozone forming potential (OFP) is only about 7%. Ethylene and propylene contribute about 26% to the total OFP despite their lower contribution of 16% to the TVOC.     

Impact of biogenic terpene emissions from <Emphasis Type="Italic">Brassica napus</Emphasis> on tropospheric ozone over saxony (Germany)

INTRODUCTION: The role of biogenic emissions in tropospheric ozone production is currently under discussion and major aspects are not well understood yet. This study aims towards the estimation of the influence of biogenic emissions on tropospheric ozone concentrations over Saxony in general and of biogenic emissions from brassica napus in special. MODELLING TOOLS: The studies are performed by utilizing a coupled numerical modelling system consisting of the meteorological model METRAS and the chemistry transport model MUSCAT. For the chemical part, the Euro-RADM algorithm is used. EMISSIONS: Anthropogenic and biogenic emissions are taken into account. The anthropogenic emissions are introduced by an emission inventory. Biogenic emissions, VOC and NO, are calculated within the chemical transport model MUSCAT at each time step and in each grid cell depending on land use type and on the temperature. The emissions of hydrocarbons from forest areas as well as biogenic NO especially from agricultural grounds are considered. Also terpene emissions from brassica napus fields are estimated. SIMULATION SETUP AND METEOROLOGICAL CONDITIONS: The simulations were performed over an area with an extension of 160 x 140 km2 which covers the main parts of Saxony and neighboring areas of Brandenburg, Sachsen-Anhalt and Thuringia. Summer smog with high ozone concentrations can be expected during high pressure conditions on hot summer days. Typical meteorological conditions for such cases were introduced in an conceptual way. RESULTS: It is estimated that biogenic emissions change tropospheric ozone concentrations in a noticeable way (up to 15% to 20%) and, therefore, should not be neglected in studies about tropospheric ozone. Emissions from brassica napus do have a moderate potential to enhance tropospheric ozone concentrations, but emissions are still under consideration and, therefore, results vary to a high degree. CONCLUSIONS: Summing up, the effect of brassica napus terpene emissions on ozone concentrations is noticeable, but not too pronounced. The results give a preliminary estimate on what the effect due to brassica napus emissions could be until better parameterizations can be derived from measurements.     

Traffic congestion and ozone precursor emissions in Bilbao (Spain)

GOAL. SCOPE. BACKGROUND: In urban environments, the measured levels of ozone are the result of the interaction between emissions of precursors (mainly VOCs and NOx) and meteorological effects. In this work, time series of daily values of ozone, measured at three locations in Bilbao (Spain), have been built. Then, after removing meteorological effects from them, ozone and traffic data have been analyzed jointly. The goal was to identify traffic situations and link them to ozone levels in the area of Bilbao. METHODS: To remove meteorological effects from the selected ozone time series, the technique developed by Rao and Zurbenko was used. This is a widely used technique and, after its application, the fraction obtained from a given ozone time series represents an ozone forming capability attributable to emissions of precursors. This fraction is devoid of any meteorological influence and includes only the apportion of periodicities above 1.7 years. In the case of Bilbao, the ozone fractions obtained at three locations have been compared on that time scale with traffic data from the area. RESULTS AND DISCUSSION: For the 1993-1996 period, a regression analysis of the ozone and traffic fractions due to periodicities above 1.7 years (long-term fractions), shows that traffic is the main explanatory factor for ozone with R2 ranging from 0.916 to 0.996 at the three locations studied. Analysis of these longterm fractions has made it possible to identify two traffic regimes for the whole area, associated to different profiles of ozone forming capability. The first one favors low ozone forming capability, and is associated with a situation of fluent traffic. The second one shows high ozone forming capability and represents congestion. Joint analysis of raw data of ozone and traffic do not show any clear pattern due to the strong masking effects that seasonal-meteorological effects (mainly radiation) have on the measured ozone signal. If only immission data of ozone are available, as in this case, a comparison between ozone and traffic can only be made on the long-term time scale, since that is the only fraction embedded in the ozone time series that can exclusively be attributed to emissions of precursors. This fact stresses the need to study the different fractions embedded in the time series of ozone measured levels separately. CONCLUSION: Though the coefficients obtained in the regression are only valid for the 1993-1996 period, these traffic regimes represent long-term targets (congestion or fluent traffic) that can inspire policies for a joint management of the traffic and pollution by ozone in the area of Bilbao beyond that period. RECOMMENDATIONS AND OUTLOOK: The results of this work show the need of a joint management of ozone and traffic in Bilbao. Since an accurate knowledge of traffic was not available, the use of emission factors to relate traffic and actual ozone levels has not been possible. For this reason, this study has focused on the long-term fractions of traffic and ozone. In the future, if a more accurate knowledge of traffic is available, it will be possible to find relationships between traffic and ozone on all time scales.     

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.     

Study of atmospheric ozone formation by means of a neural network-based model

The occurrence of high ozone levels in the atmosphere of urban areas has become a serious pollution problem in a number of large cities in the world. Although mathematical models have been proposed for predicting ozone concentrations as a function of a number of gas components, sometimes there are uncertainties due to lack of the combined effects of meteorological factors and the complex chemical reaction system involved. The application of neural network models, based on measured values of air pollutants and meteorological factors at different locations within the S?o Paulo Metropolitan Area, combine chemical and meteorological information. This has shown to be a promising tool for predicting ozone concentration. Simulations carried out with the model indicate the sensitivity of ozone in relation to different air pollution and weather conditions. Predictions using this model have shown good agreement with measured values of ozone concentrations.     

Artificial Neural Network-Derived Trends in Daily Maximum Surface Ozone Concentrations

ABSTRACT

Interannual variability in meteorological conditions can confound attempts to identify changes in ozone concentrations driven by reduced precursor emissions. In this paper, a technique is described that attempts to maximize the removal of meteorological variability from a daily maximum ozone time series, thereby revealing longer term changes in ozone concentrations with increased confidence. The technique employs artificial neural network [multilayer perceptron (MLP)] models, and is shown to remove more of the meteorological variability from U.S. ozone data than does a Kolmogorov-Zurbenko (KZ) filter and conventional regression-based technique.     

High NOx levels and lack of ozone in downtown Caracas

An evaluation of the NO, NO₂ and O₃ concentrations in downtown Caracas atmosphere at two different heights (1.5 and 56 m ) during the dry and wet season was performed.The qualitative variation of NO and NO₂ concentrations throughout the day was the same for all conditions. The profiles are explained considering the automobile emissions and the fates by photochemical reactions and dispersion. The daily mean averages for NO_x exceed all available air quality standards, making the downtown Caracas air polluted with these compounds at harmful levels.The O₃ concentrations are lower than the natural background levels practically all day long for all conditions. This lack of O₃ is explained mainly by the very high continuous NO emissions occuring in Caracas. NO reacts very fast with O₃ consuming all the O₃ produced by photochemical reactions. Possible health implications of the low O₃ levels are pointed out.     

Long-term meteorologically independent trend analysis of ozone air quality at an urban site in the greater Houston area

The Houston-Galveston-Brazoria (HGB) area of Texas has a history of ozone exceedances and is currently classified under moderate nonattainment status for the 2008 8-hr ozone standard of 75 ppb. The HGB area is characterized by intense solar radiation, high temperature, and high humidity, which influence day-to-day variations in ozone concentrations. Long-term air quality trends independent of meteorological influence need to be constructed for ascertaining the effectiveness of air quality management in this area. The Kolmogorov-Zurbenko (KZ) filter technique, used to separate different scales of motion in a time series, is applied in the current study for maximum daily 8-hr (MDA8) ozone concentrations at an urban site (U.S. Environmental Protection Agency [EPA] Air Quality System [AQS] Site ID: 48-201-0024, Aldine) in the HGB area. This site, located within 10 miles of downtown Houston and the George Bush Intercontinental Airport, was selected for developing long-term meteorologically independent MDA8 ozone trends for the years 1990–2016. Results from this study indicate a consistent decrease in meteorologically independent MDA8 ozone between 2000 and 2016. This pattern could be partially attributed to a reduction in underlying nitrogen oxide (NO_x) emissions, particularly lowering nitrogen dioxide (NO₂) levels, and a decrease in the release of highly reactive volatile organic compounds (HRVOCs). Results also suggest solar radiation to be most strongly correlated to ozone, with temperature being the secondary meteorological control variable. Relative humidity and wind speed have tertiary influence at this site. This study observed that meteorological variability accounts for a high of 61% variability in baseline ozone (low-frequency component, sum of long-term and seasonal components), whereas 64% of the change in long-term MDA8 ozone post 2000 could be attributed to NO_x emission reduction. Long-term MDA8 ozone trend component was estimated to be decreasing at a linear rate of 0.412 ± 0.007 ppb/yr for the years 2000–2016 and 0.155 ± 0.005 ppb/yr for the overall period of 1990–2016.

Implications: The effectiveness of air emission controls can be evaluated by developing long-term air quality trends independent of meteorological influences. The KZ filter technique is a well-established method to separate an air quality time series into short-term, seasonal, and long-term components. This paper applies the KZ filter technique to MDA8 ozone data between 1990 and 2016 at an urban site in the greater Houston area and estimates the variance accounted for by the primary meteorological control variables. Estimates for linear trends of MDA8 ozone are calculated and underlying causes are investigated to provide a guidance for further investigation into air quality management of the greater Houston area.     

Artificial neural network-derived trends in daily maximum surface ozone concentrations

Interannual variability in meteorological conditions can confound attempts to identify changes in ozone concentrations driven by reduced precursor emissions. In this paper, a technique is described that attempts to maximize the removal of meteorological variability from a daily maximum ozone time series, thereby revealing longer term changes in ozone concentrations with increased confidence. The technique employs artificial neural network [multilayer perceptron (MLP)] models, and is shown to remove more of the meteorological variability from U.S. ozone data than does a Kolmogorov-Zurbenko (KZ) filter and conventional regression-based technique.     

Prediction of NO and NO2 concentrations near a street with heavy traffic in Santiago,Chile

Based on NO concentrations and meteorological variables recorded hourly at a point close to an avenue with heavy traffic in the city of Santiago, we are able to build a simple model that allows prediction of NO concentrations several hours in advance. Predicted NO concentrations in conjunction with forecasted meteorological data may be used to predict NO₂ concentrations with reasonable accuracy. We compare predictions generated using persistence, linear regressions and multi layer neural networks.     

Monitoring of ozone in a marine environment in Tenerife (Canary Islands)

In the Aguere Valley (in the oceanic boundary layer at Tenerife, 28°N, 16°W, 580 m a.s.l.) the ozone levels were monitored for ambient air quality assessment. Although precursors are emitted in this area, the strong correlation between ozone levels and wind velocity indicates that ozone is transported into the valley from the ocean. The inland ozone supply along the valley is induced by an orographic channelling effect of the northern oceanic air masses. The highest ozone concentrations are mostly recorded during the nocturnal stage under the influence of fresh oceanic air masses, and during high wind speed events. The seasonal cycle is characterised by elevated ozone mixing ratios in the spring (nighttime levels >45 ppbv) and low mixing ratios in the summer (nighttime levels in the range 20–35 ppbv). Back-trajectory analysis shows that the ozone monitored in the Aguere Valley is associated with long-range transport processes. High ozone events in the spring are associated with transport from upper tropospheric levels, both over the North Atlantic-high latitudes (>45°N) and Europe. This downward transport was observed in the western edge of upper tropospheric cyclones, which suggests that the upper tropospheric/low stratospheric ozone sources play a significant role. In summer, ozone is mainly transported from the North Atlantic-high latitudes (>45°N) and from mid- to low-tropospheric levels. In autumn and winter, the high ozone concentrations are transported from sources located a few km above the North Atlantic-high latitudes (>45°N) and over Europe. The Central-North Atlantic (<45°N) and North Africa are not significant sources of ozone. The high spring and lower summer ozone events in the Aguere Valley agree with other North Atlantic ozone observation in the oceanic boundary layer. However, this behaviour contrasts with the high ozone events frequently recorded at Izaña BAPMoN station (located in the free troposphere in Tenerife) during the summer, which have been attributed in the literature to downward transport from upper levels. An intensification of the inversion layer that separates the oceanic boundary layer of the free troposphere during the summer in Canary Islands is interpreted as the cause of this different behaviour between ozone in the Aguere Valley and Izaña BAPMoN station.     

Influence of ozone and ethylenediurea (EDU) on growth and yield of bean (Phaseolus vulgaris L.) in open-top field chambers

Greenhouse and ambient air experiments have shown ethylene diurea (EDU) to be a strong and specific protective suppressant of ozone injury in plants. To examine how EDU affects plant responses to various ozone (O(3)) levels under controlled field conditions, Phaseolus vulgaris L. cv. Lit was treated with 150 ppm EDU every 14 days and exposed in open-top chambers to charcoal-filtered air (CF), nonfiltered air (NF) or two cf treatments with ozone added. The ozone treatments were proportional additions of one (CF1) and two (CF2) times ambient ozone levels. The mean ozone concentrations in the CF, NF, CF1 and CF2 treatments were 0.98, 14.1, 14.98 and 31.56 nl litre(-1). A two-way split plot ANOVA revealed that shoot dry weight was significantly reduced by ozone. EDU treatment was highly significant for leaf dry weight, root dry weight and shoot dry weight, but not for pod dry weight; leading to a higher biomass of EDU-treated plants. Ozone/EDU interactions were significant for root weight only, indicating that EDU reduced growth suppression by ozone. These results show that EDU action on plant biomass could be interpreted as a delay in senescence since EDU-treated plants showed a significant decreased biomass loss even in the CF treatment.     

Traffic pollution in a downtown site of Buenos Aires City

It has recently been recognized that air and noise pollution constitutes an extended problem over the densely populated city of Buenos Aires. Traffic emissions are of paramount concern, especially along narrow and main traffic arteries. In spite of these considerations, few systematic studies have been undertaken to evaluate the air quality in the metropolitan area of the city. In 1996, concentrations of carbon monoxide (CO), nitric oxide (NO), nitrogen dioxide (NO₂) and ozone (O₃) were simultaneously measured for the first time using a continuous monitoring station. This station was placed in a building at Belgrano Avenue, which is a heavy traffic street in the downtown area of the city (Bogo et al., Atmospheric Environment 33 (1999) 2587. In this work, we analyze the dependence of the measured primary pollutants, CO and the mixture of nitrogen oxides (NO_x), with meteorological conditions, traffic emissions and monitoring location. We compare the registered values with the results obtained from modeling the dispersion of the pollutants emitted from mobile and area sources. We also discuss the relevance of street canyon effects compared with background concentrations of these pollutants.     

Meteorologically adjusted long-term trend of ground-level ozone concentrations in Kaohsiung County,southern Taiwan

Since meteorological changes strongly affect ambient ozone concentrations, trends in concentrations of ozone upon the adjustment of meteorological variations are important of evaluating emission reduction efforts. The goal of this work is to study meteorological effects on the long-term trends of ozone concentration using a multi-variable additive model. Data on the hourly concentrations of ozone were collected from four air-quality stations from 1997 to 2006 in Kaohsiung County to determine the monthly, seasonal and annual average concentrations of ozone. The model incorporates seven meteorological parameters – pressure, temperature, relative humidity, wind speed, wind direction, duration of sunshine and cloud cover. The simulated results show that the long-term ozone concentration increases at 13.84% (or 13.06%) monthly (or annually) after meteorological adjustments, less than at 26.10% (or 23.80%) without meteorological adjustments. Wind speed, duration of sunshine and pressure are the three dominant factors that influence the ground-level ozone levels.     

Extreme value modeling for the analysis and prediction of time series of extreme tropospheric ozone levels: a case study

The occurrence of high concentrations of tropospheric ozone is considered as one of the most important issues of air management programs. The prediction of dangerous ozone levels for the public health and the environment, along with the assessment of air quality control programs aimed at reducing their severity, is of considerable interest to the scientific community and to policy makers. The chemical mechanisms of tropospheric ozone formation are complex, and highly variable meteorological conditions contribute additionally to difficulties in accurate study and prediction of high levels of ozone. Statistical methods offer an effective approach to understand the problem and eventually improve the ability to predict maximum levels of ozone. In this paper an extreme value model is developed to study data sets that consist of periodically collected maxima of tropospheric ozone concentrations and meteorological variables. The methods are applied to daily tropospheric ozone maxima in Guadalajara City, Mexico, for the period January 1997 to December 2006. The model adjusts the daily rate of change in ozone for concurrent impacts of seasonality and present and past meteorological conditions, which include surface temperature, wind speed, wind direction, relative humidity, and ozone. The results indicate that trend, annual effects, and key meteorological variables along with some interactions explain the variation in daily ozone maxima. Prediction performance assessments yield reasonably good results.     

UV Fourier transform measurements of tropospheric O3, NO2, SO2, benzene, and toluene.

Using the differential optical absorption spectroscopy (DOAS) technique and a Fourier transform spectrometer, NO2, SO2, O3, benzene. and toluene were measured during three measurement campaigns held in Brussels in 1995, 1996, and 1997. The O3 concentrations could be explained as the results of the local photochemistry and the dynamical properties of the mixing layer. NO2 concentrations were anti-correlated to the O3 concentrations, as expected. SO2 also showed a pronounced dependence on car traffic. Average benzene and toluene concentrations were, respectively 1.7 ppb and between 4.4 and 6.6 pbb, but high values of toluene up to 98.8 ppb were observed. SO2 concentrations and to a lesser extent, those of NO2 and 03, were dependent on the wind direction. Ozone in Brussels has been found to be influenced by the meteorological conditions prevailing in central Europe. Comparisons with other measurements have shown that 03 and SO2 data are in general in good agreement, but our NO2 concentrations seem to be generally higher.     

Effects of Heating Season on Residential Indoor and Outdoor Polycyclic Aromatic Hydrocarbons, Black Carbon, and Particulate Matter in an Urban Birth Cohort

Exposure to air pollutants has been associated with adverse health effects. However, analyses of the effects of season and ambient parameters such as ozone have not been fully conducted. Residential indoor and outdoor air levels of polycyclic aromatic hydrocarbons (PAH), black carbon (measured as absorption coefficient [Abs]), and fine particulate matter <2.5 μm (PM)(2.5) were measured over two-weeks in a cohort of 5-6 year old children (n=334) living in New York City's Northern Manhattan and the Bronx between October 2005 and April 2010. The objectives were to: 1) characterize seasonal changes in indoor and outdoor levels and indoor/outdoor (I/O) ratios of PAH (gas + particulate phase; dichotomized into Σ(8)PAH(semivolatile) (MW 178-206), and Σ(8)PAH(nonvolatile) (MW 228-278)), Abs, and PM(2.5); and 2) assess the relationship between PAH and ozone. Results showed that heating compared to nonheating season was associated with greater Σ(8)PAH(nonvolatile) (p<0.001) and Abs (p<0.05), and lower levels of Σ(8)PAH(semivolatile) (p<0.001). In addition, the heating season was associated with lower I/O ratios of Σ(8)PAH(nonvolatile) and higher I/O ratios of Σ(8)PAH(semivolatile) (p<0.001) compared to the nonheating season. In outdoor air, Σ(8)PAH(nonvolatile) was correlated negatively with community-wide ozone concentration (p<0.001). Seasonal changes in emission sources, air exchanges, meteorological conditions and photochemical/chemical degradation reactions are discussed in relationship to the observed seasonal trends.