Localizing Gaseous Fugitive Emission Sources by Combining Real-Time Optical Remote Sensing and Wind Data

ABSTRACT

This paper presents a new approach to localize point emissions from ground-level fugitive gaseous air pollution sources. We estimate the crosswind plume's ground-level peak location downwind from the source by combining smooth basis functions minimization (SBFM) with path-integrated optical remote sensing concentration data acquired along the crosswind direction in alternating beam path lengths. Peak location estimates, in conjunction with real-time measured wind direction data, are used to reconstruct the fugitive source location. We conducted a synthetic data study to evaluate the proposed peak location SBFM reconstruction. Furthermore, the methodology was validated with open-path Fourier transform infrared concentration data collected with wind direction data downwind from a controlled point source. This approach was found to provide reasonable estimates of point source location. The field study reconstructed source location was within several meters of the real source location.     

Characterization of Near-Road Pollutant Gradients Using Path-Integrated Optical Remote Sensing

Abstract

Understanding motor vehicle emissions, near-roadway pollutant dispersion, and their potential impact to near-roadway populations is an area of growing environmental interest. As part of ongoing U.S. Environmental Protection Agency research in this area, a field study was conducted near Interstate 440 (I-440) in Raleigh, NC, in July and August of 2006. This paper presents a subset of measurements from the study focusing on nitric oxide (NO) concentrations near the roadway. Measurements of NO in this study were facilitated by the use of a novel path-integrated optical remote sensing technique called deep ultraviolet differential optical absorption spectroscopy (DUV-DOAS). This paper reviews the development and application of this measurement system. Time-resolved near-road NO concentrations are analyzed in conjunction with wind and traffic data to provide a picture of emissions and near-road dispersion for the study. Results show peak NO concentrations in the 150 ppb range during weekday morning rush hours with winds from the road accompanied by significantly lower afternoon and weekend concentrations. Traffic volume and wind direction are shown to be primary determinants of NO concentrations with turbulent diffusion and meandering accounting for significant near-road concentrations in off-wind conditions. The enhanced source capture performance of the open-path configuration allowed for robust comparisons of measured concentrations with a composite variable of traffic intensity coupled with wind transport (R² = 0.84) as well as investigations on the influence of wind direction on NO dilution near the roadway. The benefits of path-integrated measurements for assessing line source impacts and evaluating models is presented. The advantages of NO as a tracer compound, compared with nitrogen dioxide, for investigations of mobile source emissions and initial dispersion under crosswind conditions are also discussed.     

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.     

Daily, weekly, and seasonal time courses of VOC concentrations in a semi-urban area near Barcelona

In order to study the daily, weekly, and seasonal patterns and possible origins of air concentrations of volatile organic compounds (VOCs), measurements were taken on a minute-by-minute basis with a PTR-MS in the vicinity of a highway in a semi-urban site near Barcelona. Four periods of the year were chosen and samples were taken under different meteorological conditions and at different phenological stages of the surrounding vegetation. None of the measured VOCs concentrations exceeded air-quality guidelines. The results showed that diurnal, weekly, and seasonal fluctuations in measured VOC concentrations depended on variations in the strength of sources, as well as on photochemical activity and meteorological conditions. There was a decrease in concentrations in most VOCs when mixing depth, photochemical destruction, and wind speed increased at midday. On the other hand, high values of some VOCs occurred at night when the strength of their sinks and the mixing layer decreased. Interestingly, in June, night emissions and concentration peaks of methanol and acetone occurred in periods with dew formation and no wind. VOCs related to anthropogenic emissions presented a weekly pattern of variation with a clear distinction being found between working days and the weekend. The seasonal variation showed higher levels in December for all VOCs, except for isoprene. The thinning of the mixing layer leading to greater concentrations of volatiles and lower wind speeds in winter could account for those higher VOC levels. Benzene and toluene originated mainly from anthropogenic emissions. The sources of acetaldehyde, methanol, and acetone appeared to be mainly biogenic and these compounds were the most abundant of all the measured VOCs. Isoprene concentration patterns suggest a predominantly anthropogenic origin in December and March and a mainly biogenic origin in June and October. All these data provide useful information on the dynamics of VOCs in an area where ozone levels in summer exceed quite often the standard protection thresholds for O₃.     

The Influence of Annual Meteorological Variations On Regional Air Pollution Modeling: A Case Study of Allegheny County,Pennsylvania

The influence of year-to-year meteorological variations on the prediction of annual average ground-level pollutant concentrations has been examined via case studies of Allegheny County, Pa. Twenty-two stability wind roses representing different averaging intervals of from one to seven years were employed in the Air Quality Display Model to predict annual average SO₂ concentrations in two multiple source sub-basins, and from two single point sources representing industrial and utility boiler stacks. Effects of annual meteorological variations were manifested by changes in the magnitude of peak concentrations, the location of peak concentrations, and the geographic distribution of pollutants. For fixed rates of emission, the peak annual average SO₂ ground-level concentration varied by an average of up to 33% of highest values for point sources and 17% for sub-basin complexes. In both cases, there was relatively little change in the location of peak concentration, though occasional directional shifts were noted. In contrast, marked variations were noted in the geographic area exposed to annual average concentrations in excess of several selected values. To aid in regional planning, several methods were formulated which considerably reduced the uncertainty in predicting peak annual concentration for varying degrees of historical data on regional stability wind rose. These methods are-especially applicable to analysis of control strategies directed at attaining annual ambient air quality standards which nominally must never be exceeded.     

The Transport of Suspended Particulates as a Function of Wind Direction and Atmospheric Conditions

Linear regression of high volume air sampler data and various meteorological parameters was used to determine a suspended particulate air pollution climatology for Albany, NY. A new method for exhibiting associations between wind direction and pollutant levels using correlation coefficients is presented. Correlations between wind direction distribution frequency and other meteorological parameters is employed to help explain differences in correlations for direction with suspended particulate levels. Results show that high particulate concentrations correlate well with southerly wind flow throughout the study area, regardless of relative location of receptor to local sources. This suggests that ambient background concentrations inherent in different air masses more consistently affected suspended particulate levels than did the diffusion from local sources during the study period. Maximum particulate advection occurs under conditions of good mixing of the boundary layer and moderate wind speeds and is enhanced further in the absence of removal processes such as rainout and washout. Trajectory analysis of selected days indicates a definite relationship between path and origin of the wind flow and regional average particulate concentration.     

A Methodological Approach for Exposure Assessment Studies in Residences Using Volatile Organic-Compound-Contaminated Water

Abstract

This paper presents a methodological approach for assessing total exposures to volatile organic compounds (VOCs) in residences using contaminated water supplies. This approach is founded on assessment of ingestion, inhalation, and dermal exposures; both long-term (i.e., 12 to 24 hr) lowlevel exposures and short-term (i.e., =10 min) high-level exposures are considered.

The methodology is based on the collection of water samples to establish the identity of the contaminants, maximum source terms, and possible dermal and ingestion exposures; integrated whole-air samples are collected to assess long- and short-term inhalation exposures; whole-air grab samples are used to confirm peak and typical inhalation exposures; and alveolar breath samples are used to confirm exposures and to estimate contaminant concentrations in the blood of the test subjects. While we do not suggest that this methodology should supersede any current investigative approach, this material is primarily offered as a consolidated reference to the many people or organizations who might contemplate a study of this type. Application of this investigative protocol should provide detailed exposure assessment information, while it supplies critical real world data for risk assessment specialists, toxicologists, and modeling experts. Data from a recent field study assessing exposures to trichloroethylene are presented to illustrate the utility and some of the limitations of this strategy.     

Characterization of near-road pollutant gradients using path-integrated optical remote sensing

Understanding motor vehicle emissions, near-roadway pollutant dispersion, and their potential impact to near-roadway populations is an area of growing environmental interest. As part of ongoing U.S. Environmental Protection Agency research in this area, a field study was conducted near Interstate 440 (I-440) in Raleigh, NC, in July and August of 2006. This paper presents a subset of measurements from the study focusing on nitric oxide (NO) concentrations near the roadway. Measurements of NO in this study were facilitated by the use of a novel path-integrated optical remote sensing technique called deep ultraviolet differential optical absorption spectroscopy (DUV-DOAS). This paper reviews the development and application of this measurement system. Time-resolved near-road NO concentrations are analyzed in conjunction with wind and traffic data to provide a picture of emissions and near-road dispersion for the study. Results show peak NO concentrations in the 150 ppb range during weekday morning rush hours with winds from the road accompanied by significantly lower afternoon and weekend concentrations. Traffic volume and wind direction are shown to be primary determinants of NO concentrations with turbulent diffusion and meandering accounting for significant near-road concentrations in off-wind conditions. The enhanced source capture performance of the open-path configuration allowed for robust comparisons of measured concentrations with a composite variable of traffic intensity coupled with wind transport (R2 = 0.84) as well as investigations on the influence of wind direction on NO dilution near the roadway. The benefits of path-integrated measurements for assessing line source impacts and evaluating models is presented. The advantages of NO as a tracer compound, compared with nitrogen dioxide, for investigations of mobile source emissions and initial dispersion under crosswind conditions are also discussed.     

Stochastic simulation of meteorological variability for long-range atmospheric transport—II. Long-term statistical models

Methods are developed for simulating meteorological inputs for statistical atmospheric transport models. Stochastic models are presented for the annual mean wind vector, the horizontal diffusion coefficient, the fraction of time it is raining, and the quantity of precipitation. The models are derived by aggregating the statistical models for short-term meteorological processes given in the companion paper of Small and Samson (Atmospheric Environment, 1989, 23, 2813–2824). Normal distributions are used for each variable. The normal distribution is derived directly for the mean wind vector based on the normality of short-term winds, and serves as an acceptable approximation for the other variables given their low interannual coefficient of variation. Correlation between variables is considered, including correlation between winds and precipitation, between the fraction of time it is raining and the total quantity of precipitation at a site, and between the annual precipitation quantity at multiple sites. Development and confirmation of the interannual distributions is supported by long-term meteorological data, including a nine-year backward trajectory record computed for a site in western Pennsylvania. Application of the method is demonstrated with a statistical atmospheric LRT model used to predict distributions of annual precipitation sulfates in eastern North America. Predicted interannual coefficients of variation of wet SO₄²⁻ concentrations range from about 10 to 15 per cent, similar to the level of interannual variation inferred from long-term data sets.     

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

ABSTRACT

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

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

Estimating Maximum Concentrations for Open Path Monitoring Along a Fixed Beam Path

ABSTRACT

Researchers have applied open path optical sensing techniques to a variety of workplace and environmental monitoring problems. Usually these data are reported in terms of a path-average (or path-integrated) concentration. When assessing potential human exposures along a beam path, this path-average value is not always informative, since concentrations along the path can vary substantially from the beam average. The focus of this research is to arrive at a method for estimating the upper-bound in contaminant concentrations over a fixed open beam path. The approach taken here uses a statistical model to estimate an upper-bound concentration based on a combination of the path-average and a measure of the spatial variability computed from point samples along the beam path. Results of computer simulations and experimental testing in a controlled ventilation chamber indicate that the model produced conservative estimates for the maximum concentration along the beam path. This approach may have many applications for open path monitoring in workplaces or wherever maximum concentrations are a concern.     

Assessment of spatial variation of ambient volatile organic compound levels at a power station in Kuwait

Twenty-four-hour integrated ambient air samples were collected in canisters at 10 locations within Kuwait’s major power station: Doha West Power Station to assess the spatial distribution of volatile organic compounds (VOCs) within the perimeter of the station. A total of 30 samples, i.e., three samples per location, were collected during February and March. The samples were analyzed using a gas chromatography with flame ionization detection (GC-FID) system and following the U.S. EPA Method TO-14A with modification. The results reflected the emission activities on the site and the meteorological conditions during sampling. Generally speaking, there was a negative correlation between the ambient temperature and the VOC concentrations, which indicates the sources were local. The halogenated compounds formed the highest proportion (i.e. 50–75 %) of the total VOC concentrations at the ten locations. 1,2,4-Trichlorobenzene and Vinyl Chloride concentrations were the highest amongst the other halogenated compounds. The aromatic compounds formed the least proportion (i.e. 1–4%) of the total VOC levels at all locations with Toluene having the highest concentrations amongst the aromatic compounds at seven locations. Propene, which is a major constituent of the fuel used, was the highest amongst the aliphatic compounds. The findings of this study and other relevant work suggests the measured VOC levels were the highest over the year, nevertheless, further work is required to assess the precisely temporal variation of VOC due to change in meteorological conditions and the emission rates.

Implications: Assessment of VOC concentrations around a power plant in Kuwait during the peak season showed halogenated compounds to be the dominant group. The calculated indoor concentrations were lower than those reported in a residential area about 12 km away.     

Application of artificial neural networks to modeling and prediction of ambient ozone concentrations

The deterministic modeling of ambient O3 concentrations is difficult because of the complexity of the atmospheric system in terms of the number of chemical species; the availability of accurate, time-resolved emissions data; and the required rate constants. However, other complex systems have been successfully approximated using artificial neural networks (ANNs). In this paper, ANNs are used to model and predict ambient O3 concentrations based on a limited number of measured hydrocarbon species, NOx compounds, temperature, and radiant energy. In order to examine the utility of these approaches, data from the Coastal Oxidant Assessment for Southeast Texas (COAST) program in Houston, TX, have been used. In this study, 53 hydrocarbon compounds, along with O3, nitrogen oxides, and meteorological data were continuously measured during summer 1993. Steady-state ANN models were developed to examine the ability of these models to predict current O3 concentrations from measured VOC and NOx concentrations. To predict the future concentrations of O3, dynamic models were also explored and were used for extraction of chemical information such as reactivity estimations for the VOC species. The steady-state model produced an approximation of O3 data and demonstrated the functional relationship between O3 and VOC-NOx concentrations. The dynamic models were able to the adequately predict the O3 concentration and behavior of VOC-NOx-O3 system a number of hourly intervals into the future. For 3 hr into the future, O3 concentration could be predicted with a root-mean squared error (RMSE) of 8.21 ppb. Extending the models further in time led to an RMSE of 11.46 ppb for 5-hr-ahead values. This prediction capability could be useful in determining when control actions are needed to maintain measured concentrations within acceptable value ranges.     

Characteristics and source apportionment of VOCs measured in Shanghai,China

Volatile organic compounds (VOCs) were measured from 2007 to 2010 at the center of Shanghai, China. Because VOCs are important precursors for ozone photochemical formation, detailed information of VOC sources needs to be investigated. The results show that the measured VOC concentrations in Shanghai are dominated by alkanes (43%) and aromatics (30%), following by halo-hydrocarbons (14%) and alkenes (6%). Based on the measured VOC concentrations, a receptor model (PMF; positive matrix factorization) coupled with the information related to VOC sources (the distribution of major industrial complex, meteorological conditions, etc.) is applied to identify the major VOC sources in Shanghai. The result shows that seven major VOC sources are identified by the PMF method, including (1) vehicle related source which contributes to 25% of the measured VOC concentrations, (2) solvent based industrial source to 17%, (3) fuel evaporation to 15%, (4) paint solvent usage to 15%, (5) steel related industrial production to 12%, (6) biomass/biofuel burning to 9%, and (7) coal burning to 7%. Furthermore, ozone formation potential related to VOC sources is calculated by the MIR (maximum incremental reactivity) technique. The most significant VOC source for ozone formation potential is solvent based industrial sources (27%), paint solvent usage (24%), vehicle related emissions (17%), steel related industrial productions (14%), fuel evaporations (9%), coal burning (6%), and biomass/biofuel burning (3%). The weekend effect on the VOC concentrations shows that VOC concentrations are generally higher in the weekdays than in the weekends at the sampling site, suggesting that traffic conditions and human activities have important impacts on the VOC emissions in Shanghai.     

Particulate air quality model predictions using prognostic vs. diagnostic meteorology in central California

Comparisons were made between three sets of meteorological fields used to support air quality predictions for the California Regional Particulate Air Quality Study (CRPAQS) winter episode from December 15, 2000 to January 6, 2001. The first set of fields was interpolated from observations using an objective analysis method. The second set of fields was generated using the WRF prognostic model without data assimilation. The third set of fields was generated using the WRF prognostic model with the four-dimensional data assimilation (FDDA) technique. The UCD/CIT air quality model was applied with each set of meteorological fields to predict the concentrations of airborne particulate matter and gaseous species in central California. The results show that the WRF model without data assimilation over-predicts surface wind speed by ～30% on average and consequently yields under-predictions for all PM and gaseous species except sulfate (S(VI)) and ozone(O₃). The WRF model with FDDA improves the agreement between predicted and observed wind and temperature values and consequently yields improved predictions for all PM and gaseous species. Overall, diagnostic meteorological fields produced more accurate air quality predictions than either version of the WRF prognostic fields during this episode. Population-weighted average PM_2.5 exposure is 40% higher using diagnostic meteorological fields compared to prognostic meteorological fields created without data assimilation. These results suggest diagnostic meteorological fields based on a dense measurement network are the preferred choice for air quality model studies during stagnant periods in locations with complex topography.     

Innovative Approach for Estimating Fugitive Gaseous Fluxes Using Computed Tomography and Remote Optical Sensing Techniques

ABSTRACT

This paper presents a new approach to quantify emissions from fugitive gaseous air pollution sources. The authors combine Computed Tomography (CT) with Path-Integrated Optical Remote Sensing (PI-ORS) concentration data in a new field beam geometry. Path-integrated concentrations are sampled in a vertical plane downwind from the source along several radial beam paths. An innovative CT technique, which applies the Smooth Basis Function Minimization method to the beam data in conjunction with measured wind data, is used to estimate the total flux from the fugitive source. The authors conducted a synthetic data study to evaluate the proposed methodology under different meteorological conditions, beam geometry configurations, and simulated measurement errors. The measurement errors were simulated based on data collected with an Open-Path Fourier Transform Infra-Red system. This approach was found to be robust for the simulated errors and for a wide range of fluctuating wind directions. In the very sparse beam geometry examined (eight beam paths), successful emission rates were retrieved over a 70° range of wind directions under extremely large measurement error conditions.     

Modeling effects of moisture content and advection on odor causing vocs volatilization from stored swine manure

Abstract

Two models for evaluating the contents and advection of manure moisture on odor causing volatile organic compounds (VOC‐odor) volatilization from stored swine manure were studied for their ability to predict the volatilization rate (indoor air concentration) and cumulative exposure dose: a MJ‐I model and a MJ‐II model. Both models simulating depletion of source contaminant via volatilization and degradation based on an analytical model adapted from the behavior assessment model of Jury et al. In the MJ‐I model, manure moisture movement was negligible, whereas in the MJ‐II model, time‐dependent indoor air concentrations was a function of constant manure moisture contents and steady‐state moisture advection. Predicted indoor air concentrations and inhaled doses for the study VOC‐odors of p‐cresol, toluene, and p‐xylene varied by up to two to three orders of magnitude depending on the manure moisture conditions. The sensitivity analysis of both models suggests that when manure moisture movement exists, simply MJ‐I model is inherently not sufficient to represent a more generally volatilization process, which can even become stringent as moisture content increases. The conclusion illustrates how one needs to include a wide variety of manure moisture values in order to fully assess the complex volatilization mechanisms that are present in a real situation.     

Effect of outside air ventilation rate on volatile organic compound concentrations in a call center

A study of the relationship between outside air ventilation rate and concentrations of volatile organic compounds (VOCs) generated indoors was conducted in a call center office building. The building, with two floors and a total floor area of 4600 m², is located in the San Francisco Bay Area, CA. Ventilation rates were manipulated with the building's four air handling units (AHUs). VOC and CO₂ concentrations in the AHU returns were measured on 7 days during a 13-week period. VOC emission factors were determined for individual zones on days when they were operating at near steady-state conditions. The emission factor data were subjected to principal component (PC) analysis to identify groups of co-varying compounds. Potential sources of the PC vectors were ascribed based on information from the literature. The per occupant CO₂ generation rates were 0.0068–0.0092 l s⁻¹. The per occupant isoprene generation rates of 0.2–0.3 mg h⁻¹ were consistent with the value predicted by mass balance from breath concentration and exhalation rate. The relationships between indoor minus outdoor VOC concentrations and ventilation rate were qualitatively examined for eight VOCs. Of these, acetaldehyde and hexanal, which likely were associated with material sources, and decamethylcyclopentasiloxane, associated with personal care products, exhibited general trends of higher concentrations at lower ventilation rates. For other compounds, a clear inverse relationship between VOC concentrations and ventilation was not observed. The net concentration of 2,2,4-trimethyl-1,3-pentanediol monoisobutyrate isomers, examples of low-volatility compounds, changed very little with ventilation likely due to sorption and re-emission effects. These results illustrate that the efficacy of ventilation for controlling VOC concentrations can vary considerably depending upon the operation of the building, the pollutant sources and the physical and chemical processes affecting the pollutants. Thus, source control measures, in addition to adequate ventilation, are required to limit concentrations of VOCs in office buildings.     

Interlaboratory Study of a Test Method Measuring Total Volatile Organic Compound Content of Consumer Products

Abstract

Consumer products are potentially significant sources of volatile organic compounds (VOCs), which are precursors to the formation of ozone in photochemical smog. To address the problem of ozone formation in ambient air, the U.S. Environmental Protection Agency (EPA) has been involved in the development of test methods for measuring the VOC content of consumer products. This paper describes results of an interlaboratory study to estimate the repeatability (precision of analyses performed by a single laboratory) and reproducibility (precision of analyses performed by different laboratories) of the consumer products’ VOC measurement method based on EPA Method 24 (for VOCs in surface coatings).

The mean method repeatability was 2.7 wt % VOC, and the mean method reproducibility was 4.8 wt % VOC. Method repeatability ranged from 0.2 to 4.4 wt % VOC, and reproducibility ranged from 0.6 to 11.9 weight percent VOC. The precision of the VOC method for consumer

products is similar to the precision of EPA Method 24 for surface coatings.     

Concentrations and Source Characteristics of Airborne Carbonyl Compounds Measured Outside Urban Residences

Abstract

This paper presents the analysis of ambient air concentrations of 10 carbonyl compounds (aldehydes and ketones) measured in the yards of 87 residences in the city of Elizabeth, NJ, throughout 1999–2001. Most of these residences were measured twice in different seasons; the sampling duration was 48 hr each time. The authors observed higher concentrations for most of the measured carbonyl compounds on warmer days, reflecting larger contributions of photochemical reactions on warmer days. The estimated contributions of photochemical production varied substantially across the measured carbonyl compounds and could be as high as 60%. Photochemical activity, however, resulted in a net loss for formaldehyde. The authors used stepwise multiple linear regression models to evaluate the impact of traffic sources and meteorological conditions on carbonyl concentrations using the data collected on colder days (with lower photochemical activities). They found that the concentrations of formal-dehyde, acetaldehyde, acrolein, propionaldehyde, crotonaldehyde, benzaldehyde, glyoxal, and methylglyoxal significantly decreased with increasing distance between a measured residence and one or more major roadways. They also found significant negative associations between concentrations for most of the measured carbonyl compounds and each of the following meteorological parameters: mixing height, wind speed, and precipitation.