Traffic and Meteorological Impacts on Near-Road Air Quality: Summary of Methods and Trends from the Raleigh Near-Road Study

Abstract

A growing number of epidemiological studies conducted worldwide suggest an increase in the occurrence of adverse health effects in populations living, working, or going to school near major roadways. A study was designed to assess traffic emissions impacts on air quality and particle toxicity near a heavily traveled highway. In an attempt to describe the complex mixture of pollutants and atmospheric transport mechanisms affecting pollutant dispersion in this near-highway environment, several real-time and time-integrated sampling devices measured air quality concentrations at multiple distances and heights from the road. Pollutants analyzed included U.S. Environmental Protection Agency (EPA)-regulated gases, particulate matter (coarse, fine, and ultrafine), and air toxics. Pollutant measurements were synchronized with real-time traffic and meteorological monitoring devices to provide continuous and integrated assessments of the variation of near-road air pollutant concentrations and particle toxicity with changing traffic and environmental conditions, as well as distance from the road. Measurement results demonstrated the temporal and spatial impact of traffic emissions on near-road air quality. The distribution of mobile source emitted gas and particulate pollutants under all wind and traffic conditions indicated a higher proportion of elevated concentrations near the road, suggesting elevated exposures for populations spending significant amounts of time in this microenvironment. Diurnal variations in pollutant concentrations also demonstrated the impact of traffic activity and meteorology on near-road air quality. Time-resolved measurements of multiple pollutants demonstrated that traffic emissions produced a complex mixture of criteria and air toxic pollutants in this microenvironment. These results provide a foundation for future assessments of these data to identify the relationship of traffic activity and meteorology on air quality concentrations and population exposures.     

The effects of roadside structures on the transport and dispersion of ultrafine particles from highways

Understanding local-scale transport and dispersion of pollutants emitted from traffic sources is important for urban planning and air quality assessments. Predicting pollutant concentration patterns in complex environments depends on accurate representations of local features (e.g., noise barriers, trees, buildings) affecting near-field air flows. This study examined the effects of roadside barriers on the flow patterns and dispersion of pollutants from a high-traffic highway in Raleigh, North Carolina, USA. The effects of the structures were analyzed using the Quick Urban & Industrial Complex (QUIC) model, an empirically based diagnostic tool which simulates fine-scale wind field and dispersion patterns around obstacles. Model simulations were compared with the spatial distributions of ultrafine particles (UFP) from vehicular emissions measured using a passenger van equipped with a Differential Mobility Analyzer/Condensation Particle Counter. The field site allowed for an evaluation of pollutant concentrations in open terrain, with a noise barrier present near the road, and with a noise barrier and vegetation present near the road.Results indicated that air pollutant concentrations near the road were generally higher in open terrain situations with no barriers present; however, concentrations for this case decreased faster with distance than when roadside barriers were present. The presence of a noise barrier and vegetation resulted in the lowest downwind pollutant concentrations, indicating that the plume under this condition was relatively uniform and vertically well-mixed. Comparison of the QUIC model with the mobile UFP measurements indicated that QUIC reasonably represented pollutant transport and dispersion for each of the study configurations.     

Road traffic impact on urban water quality: a step towards integrated traffic,air and stormwater modelling

Methods for simulating air pollution due to road traffic and the associated effects on stormwater runoff quality in an urban environment are examined with particular emphasis on the integration of the various simulation models into a consistent modelling chain. To that end, the models for traffic, pollutant emissions, atmospheric dispersion and deposition, and stormwater contamination are reviewed. The present study focuses on the implementation of a modelling chain for an actual urban case study, which is the contamination of water runoff by cadmium (Cd), lead (Pb), and zinc (Zn) in the Grigny urban catchment near Paris, France. First, traffic emissions are calculated with traffic inputs using the COPERT4 methodology. Next, the atmospheric dispersion of pollutants is simulated with the Polyphemus line source model and pollutant deposition fluxes in different subcatchment areas are calculated. Finally, the SWMM water quantity and quality model is used to estimate the concentrations of pollutants in stormwater runoff. The simulation results are compared to mass flow rates and concentrations of Cd, Pb and Zn measured at the catchment outlet. The contribution of local traffic to stormwater contamination is estimated to be significant for Pb and, to a lesser extent, for Zn and Cd; however, Pb is most likely overestimated due to outdated emissions factors. The results demonstrate the importance of treating distributed traffic emissions from major roadways explicitly since the impact of these sources on concentrations in the catchment outlet is underestimated when those traffic emissions are spatially averaged over the catchment area.     

Concentrations of mobile source air pollutants in urban microenvironments

Human exposures to criteria and hazardous air pollutants (HAPs) in urban areas vary greatly due to temporal-spatial variations in emissions, changing meteorology, varying proximity to sources, as well as due to building, vehicle, and other environmental characteristics that influence the amounts of ambient pollutants that penetrate or infiltrate into these microenvironments. Consequently, the exposure estimates derived from central-site ambient measurements are uncertain and tend to underestimate actual exposures. The Exposure Classification Project (ECP) was conducted to measure pollutant concentrations for common urban microenvironments (MEs) for use in evaluating the results of regulatory human exposure models. Nearly 500 sets of measurements were made in three Los Angeles County communities during fall 2008, winter 2009, and summer 2009. MEs included in-vehicle, near-road, outdoor, and indoor locations accessible to the general public. Contemporaneous 1- to 15-min average personal breathing zone concentrations of carbon monoxide (CO), carbon dioxide (CO₂), volatile organic compounds (VOCs), nitric oxide (NO), nitrogen oxides (NO_x), particulate matter (<2.5 μm diameter; PM_2.5) mass, ultrafine particle (UFP; <100 nm diameter) number, black carbon (BC), speciated HAPs (e.g., benzene, toluene, ethylbenzene, xylenes [BTEX], 1,3-butadiene), and ozone (O₃) were measured continuously. In-vehicle and inside/outside measurements were made in various passenger vehicle types and in public buildings to estimate penetration or infiltration factors. A large fraction of the observed pollutant concentrations for on-road MEs, especially near diesel trucks, was unrelated to ambient measurements at nearby monitors. Comparisons of ME concentrations estimated using the median ME/ambient ratio versus regression slopes and intercepts indicate that the regression approach may be more accurate for on-road MEs. Ranges in the ME/ambient ratios among ME categories were generally greater than differences among the three communities for the same ME category, suggesting that the ME proximity factors may be more broadly applicable to urban MEs.

Implications:Estimates of population exposure to air pollutants extrapolated from ambient measurements at ambient fixed site monitors or exposure surrogates are prone to uncertainty. This study measured concentrations of mobile source air toxics (MSAT) and related criteria pollutants within in-vehicle, outdoor near-road, and indoor urban MEs to provide multipollutant ME measurements that can be used to calibrate regulatory exposure models.     

Near-road air pollutant concentrations of CO and PM2.5: A comparison of MOBILE6.2/CALINE4 and generalized additive models

The contribution of vehicular traffic to air pollutant concentrations is often difficult to establish. This paper utilizes both time-series and simulation models to estimate vehicle contributions to pollutant levels near roadways. The time-series model used generalized additive models (GAMs) and fitted pollutant observations to traffic counts and meteorological variables. A one year period (2004) was analyzed on a seasonal basis using hourly measurements of carbon monoxide (CO) and particulate matter less than 2.5 μm in diameter (PM_2.5) monitored near a major highway in Detroit, Michigan, along with hourly traffic counts and local meteorological data. Traffic counts showed statistically significant and approximately linear relationships with CO concentrations in fall, and piecewise linear relationships in spring, summer and winter. The same period was simulated using emission and dispersion models (Motor Vehicle Emissions Factor Model/MOBILE6.2; California Line Source Dispersion Model/CALINE4). CO emissions derived from the GAM were similar, on average, to those estimated by MOBILE6.2. The same analyses for PM_2.5 showed that GAM emission estimates were much higher (by 4–5 times) than the dispersion model results, and that the traffic-PM_2.5 relationship varied seasonally. This analysis suggests that the simulation model performed reasonably well for CO, but it significantly underestimated PM_2.5 concentrations, a likely result of underestimating PM_2.5 emission factors. Comparisons between statistical and simulation models can help identify model deficiencies and improve estimates of vehicle emissions and near-road air quality.     

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.     

A quantitative approach to the traffic air quality problem: the Traffic Air Quality index

The Traffic Air Quality (TAQ) model is a simple tool to estimate traffic fine particulate emissions on roadways (g/km) and can be used for both real-time analysis and for localized conformity analysis ("hot-spot" analysis for nonattainment areas) as defined by 40 CFR 93.123. This paper is a follow-up to a study published earlier regarding the development of the TAQ model. This paper shows how local air quality levels can be a factor in traffic management in nonattainment areas. Similar to the industrial source quotas measured in tons per year, it is proposed that road segments are to be assigned emission quotas (or TAQ indices) measured in pollutant mass emitted per road length (g/km) above which traffic-measures have to be taken to reduce the fine-particulates emissions on such road links. The TAQ model as well as traffic-rerouting measures along with the Intelligent Transportation System (ITS) protocols can be used to have a real-time control of the traffic conditions along expressways to maintain the fine-particulates emissions below the quota assigned per road link and consequently improving the over all local air quality in nonattainment areas.     

Relative importance of school bus-related microenvironments to children's pollutant exposure

Real-time concentrations of black carbon, particle-bound polycyclic aromatic hydrocarbons, nitrogen dioxide, and fine particulate counts, as well as integrated and real-time fine particulate matter (PM2.5) mass concentrations were measured inside school buses during long commutes on Los Angeles Unified School District bus routes, at bus stops along the routes, at the bus loading/unloading zone in front of the selected school, and at nearby urban "background" sites. Across all of the pollutants, mean concentrations during bus commutes were higher than in any other microenvironment. Mean exposures (mean concentration times time spent in a particular microenvironment) in bus commutes were between 50 and 200 times greater than those for the loading/unloading microenvironment, and 20-40 times higher than those for the bus stops, depending on the pollutant. Although the analyzed school bus commutes represented only 10% of a child's day, on average they contributed one-third of a child's 24-hr overall black carbon exposure during a school day. For species closely related to vehicle exhaust, the within- cabin exposures were generally dominated by the effect of surrounding traffic when windows were open and by the bus's own exhaust when windows were closed. Low-emitting buses generally exhibited high concentrations only when traveling behind a diesel vehicle, whereas high-emitting buses exhibited high concentrations both when following other diesel vehicles and when idling without another diesel vehicle in front of the bus. To reduce school bus commute exposures, we recommend minimizing commute times, avoiding caravanning with other school buses, using the cleanest buses for the longest bus routes, maintaining conventional diesel buses to eliminate visible emissions, and transitioning to cleaner fuels and advanced particulate control technologies as soon as possible.     

A Quantitative Approach to the Traffic Air Quality Problem: The Traffic Air Quality Index

Abstract

The Traffic Air Quality (TAQ) model is a simple tool to estimate traffic fine particulate emissions on roadways (g/km) and can be used for both real-time analysis and for localized conformity analysis (“hot-spot” analysis for nonattainment areas) as defined by 40 CFR 93.123. This paper is a follow-up to a study published earlier regarding the development of the TAQ model. This paper shows how local air quality levels can be a factor in traffic management in nonattainment areas. Similar to the industrial source quotas measured in tons per year, it is proposed that road segments are to be assigned emission quotas (or TAQ indices) measured in pollutant mass emitted per road length (g/km) above which traffic-measures have to be taken to reduce the fine-particulates emissions on such road links. The TAQ model as well as traffic-rerouting measures along with the Intelligent Transportation System (ITS) protocols can be used to have a real-time control of the traffic conditions along expressways to maintain the fine-particulates emissions below the quota assigned per road link and consequently improving the over all local air quality in nonattainment areas.     

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.     

Air Quality Measurements for the Aerosol Research and Inhalation Epidemiology Study

Abstract

Measurements of pollutant gases, airborne particulate matter mass and composition, and meteorology have been made at a core site near downtown Atlanta, GA, since August 1998 in support of the Aerosol Research and Inhalation Epidemiology Study (ARIES). This site is one of eight in the Southeastern Aerosol Research and Characterization network. The measurement objective is to provide a long-term, multivariate dataset suitable for investigating statistical associations of respiratory and cardiovascular disease with airborne particulate matter composition, meteorology, and copollutant gases through epidemiologic modeling. Measurements are expected to continue through 2010. Ancillary multiyear measurements at additional sites in the Atlanta metropolitan area and in short-term exposure assessments have been used to estimate the exposure/measurement error associated with using data from a central site to approximate human exposures for the entire area. To date, 13-, 25-, and 53-month air quality datasets have been used in epidemiologic analyses.     

Air quality measurements for the aerosol research and inhalation epidemiology study

Measurements of pollutant gases, airborne particulate matter mass and composition, and meteorology have been made at a core site near downtown Atlanta, GA, since August 1998 in support of the Aerosol Research and Inhalation Epidemiology Study (ARIES). This site is one of eight in the Southeastern Aerosol Research and Characterization network. The measurement objective is to provide a long-term, multivariate dataset suitable for investigating statistical associations of respiratory and cardiovascular disease with airborne particulate matter composition, meteorology, and copollutant gases through epidemiologic modeling. Measurements are expected to continue through 2010. Ancillary multiyear measurements at additional sites in the Atlanta metropolitan area and in short-term exposure assessments have been used to estimate the exposure/measurement error associated with using data from a central site to approximate human exposures for the entire area. To date, 13-, 25-, and 53-month air quality datasets have been used in epidemiologic analyses.     

Plume analysis from field evaluations of a portable air quality monitoring system

ABSTRACT

Near-road measurements in Rochester, NY with a Portable Air Quality Monitoring System indicate a significant plume control of PM_2.5 black carbon (BC) concentrations. This study evaluates the performance of two portable air quality enclosures deployed at collocated research sites to determine their accuracy and usefulness in field deployments, and specifically in pollution plume analysis. One system deployed collocated sensors for measurement of particulate matter mass concentration (Thermo pDR 1500 against Tapered Element Oscillating Microbalance (TEOM) measurement) and the second system deployed sensors for measurement of black carbon (Magee AE33 aethalometer and Brechtel Tricolor Absorption Photometer) in ambient and near-road locations in Rochester, New York, respectively. While the optical PM_2.5 sensors tended to be biased in their determination of concentration by ~15%, they followed changes and trends in concentration very well. The black carbon sensors in the portable systems agreed very well with each other and with the collocated sensor. As a case study to determine the contribution from statistically significant short-lived excursions of pollutant concentration, Morlet wavelet analysis was performed on data from the portable system sensors. Black carbon was found to be strongly influenced by plume behavior with significant plume excursions representing just over 12% of all data points and contributing on average 1 µg/m³ of black carbon above ambient concentrations.

Implications: This paper first evaluates two air pollutant monitoring enclosures with wide applicability including near-road detection of pollutants. Then, we present a novel method to designate isolate statistically significant excursions in air pollution concentration which can be used to determine the impact of pollutant plumes as observed in PM and black carbon behavior near road.     

Fine particulate matter and carbon monoxide exposure concentrations in urban street transport microenvironments

Personal exposure studies are crucial alongside microenvironment and ambient studies in order to get a better understanding of the health risks posed by fine particulate matter and carbon monoxide in the urban transport microenvironment and for making informed decisions to manage and reduce the health risks. Studies specifically assessing the PM_2.5, ultrafine particle count and carbon monoxide personal exposure concentrations of adults in an urban transport microenvironment have steadily increased in number over the last decade. However, no recent collective summary is available, particularly one which also considers ultrafine particles; therefore, we present a review of the personal exposure concentration studies for the above named pollutants on different modes of surface transportation (walking, cycling, bus, car and taxi) in the urban transport microenvironment. Comparisons between personal exposure measurements and concentrations recorded at fixed monitoring sites are considered in addition to the factors influencing personal exposure in the transport microenvironment.In general, the exposure studies examined revealed pedestrians and cyclists to experience lower fine particulate matter and CO exposure concentrations in comparison to those inside vehicles—the vehicle shell provided no protection to the passengers. Proximity to the pollutant sources had a significant impact on exposure concentration levels experienced, consequently individuals should be encouraged to use back street routes. Fixed monitoring stations were found to be relatively poor predictors of CO and PM_2.5 exposure concentration levels experienced by individuals in the urban transport microenvironment. Although the mode of transport, traffic and meteorology parameters were commonly identified as significant factors influencing exposure concentrations to the different pollutants under examination, a large amount of the exposure concentration variation in the exposure studies remained unexplained.     

Binational school-based monitoring of traffic-related air pollutants in El Paso, Texas (USA) and Ciudad Juárez, Chihuahua (México)

Paired indoor and outdoor concentrations of fine and coarse particulate matter (PM), PM2.5 reflectance [black carbon(BC)], and nitrogen dioxide (NO₂) were determined for sixteen weeks in 2008 at four elementary schools (two in high and two in low traffic density zones) in a U.S.-Mexico border community to aid a binational health effects study. Strong spatial heterogeneity was observed for all outdoor pollutant concentrations. Concentrations of all pollutants, except coarse PM, were higher in high traffic zones than in the respective low traffic zones. Black carbon and NO₂ appear to be better traffic indicators than fine PM. Indoor air pollution was found to be well associated with outdoor air pollution, although differences existed due to uncontrollable factors involving student activities and building/ventilation configurations. Results of this study indicate substantial spatial variability of pollutants in the region, suggesting that children’s exposures to these pollutants vary based on the location of their school.     

Relative Importance of School Bus-Related Microenvironments to Children’s Pollutant Exposure

Abstract

Real‐time concentrations of black carbon, particle‐bound polycyclic aromatic hydrocarbons, nitrogen dioxide, and fine particulate counts, as well as integrated and real‐time fine particulate matter (PM_2.5) mass concentrations were measured inside school buses during long commutes on Los Angeles Unified School District bus routes, at bus stops along the routes, at the bus loading/unloading zone in front of the selected school, and at nearby urban “background” sites. Across all of the pollutants, mean concentrations during bus commutes were higher than in any other microenvironment. Mean exposures (mean concentration times time spent in a particular microenvironment) in bus commutes were between 50 and 200 times greater than those for the loading/unloading microenvironment, and 20–40 times higher than those for the bus stops, depending on the pollutant. Although the analyzed school bus commutes represented only 10% of a child’s day, on average they contributed one‐third of a child’s 24‐hr overall black carbon exposure during a school day. For species closely related to vehicle exhaust, the within‐cabin exposures were generally dominated by the effect of surrounding traffic when windows were open and by the bus’s own exhaust when windows were closed. Low‐emitting buses generally exhibited high concentrations only when traveling behind a diesel vehicle, whereas high‐emitting buses exhibited high concentrations both when following other diesel vehicles and when idling without another diesel vehicle in front of the bus. To reduce school bus commute exposures, we recommend minimizing commute times, avoiding caravanning with other school buses, using the cleanest buses for the longest bus routes, maintaining conventional diesel buses to eliminate visible emissions, and transitioning to cleaner fuels and advanced particulate control technologies as soon as possible.     

Relative roles of emissions and meteorology in the diurnal pattern of urban PM10: analysis of the daylight saving time effect

Daylight saving time (DST) is a common practice in many countries, in which Official Time (OT) is abruptly shifted 1 hour with respect to solar time on two occasions every year (in fall and spring). All anthropogenic emitting processes tied to OT like job and school commuting traffic, abruptly change in this moment their timing with respect to solar time, inducing a sudden shift between emissions and the meteorological factors that control the dispersion and transport of air pollutants. Analyzing 13 years of hourly particulate matter (PM10) concentrations measured in Santiago, Chile, we demonstrate that the DST practice has observable non-trivial effects in the PM10 diurnal cycle. The clearest impact is in the morning peak of PM10 during the fall DST change, which occurs later and has on average a significant smaller magnitude in the days after the DST change as compared to the days before it. This decrease in magnitude is most remarkable because it occurs in a period of the year when overall PM10 concentrations increase due to generally worsening of the dispersion conditions. Results are shown for seven monitoring stations around the city, and for the fall and spring DST changes. They show clearly the interplay of emissions and meteorology in conditioning urban air pollution problems, highlighting the role of the morning and evening transitions of the atmospheric boundary layer in shaping the diurnal pattern of urban air pollutant concentrations.     

Impact of emissions from natural gas production facilities on ambient air quality in the Barnett Shale area: A pilot study

Rapid and extensive development of shale gas resources in the Barnett Shale region of Texas in recent years has created concerns about potential environmental impacts on water and air quality. The purpose of this study was to provide a better understanding of the potential contributions of emissions from gas production operations to population exposure to air toxics in the Barnett Shale region. This goal was approached using a combination of chemical characterization of the volatile organic compound (VOC) emissions from active wells, saturation monitoring for gaseous and particulate pollutants in a residential community located near active gas/oil extraction and processing facilities, source apportionment of VOCs measured in the community using the Chemical Mass Balance (CMB) receptor model, and direct measurements of the pollutant gradient downwind of a gas well with high VOC emissions. Overall, the study results indicate that air quality impacts due to individual gas wells and compressor stations are not likely to be discernible beyond a distance of approximately 100 m in the downwind direction. However, source apportionment results indicate a significant contribution to regional VOCs from gas production sources, particularly for lower-molecular-weight alkanes (<C6). Although measured ambient VOC concentrations were well below health-based safe exposure levels, the existence of urban-level mean concentrations of benzene and other mobile source air toxics combined with soot to total carbon ratios that were high for an area with little residential or commercial development may be indicative of the impact of increased heavy-duty vehicle traffic related to gas production

ImplicationsRapid and extensive development of shale gas resources in recent years has created concerns about potential environmental impacts on water and air quality. This study focused on directly measuring the ambient air pollutant levels occurring at residential properties located near natural gas extraction and processing facilities, and estimating the relative contributions from gas production and motor vehicle emissions to ambient VOC concentrations. Although only a small-scale case study, the results may be useful for guidance in planning future ambient air quality studies and human exposure estimates in areas of intensive shale gas production.     

Microenvironmental characteristics important for personal exposures to aldehydes in Sacramento,CA, and Milwaukee,WI

Oxygenated additives in gasoline are designed to decrease the ozone-forming hydrocarbons and total air toxics, yet they can increase the emissions of aldehydes and thus increase human exposure to these toxic compounds. This paper describes a study conducted to characterize targeted aldehydes in microenvironments in Sacramento, CA, and Milwaukee, WI, and to improve our understanding of the impact of the urban environment on human exposure to air toxics. Data were obtained from microenvironmental concentration measurements, integrated, 24-h personal measurements, indoor and outdoor pollutant monitors at the participants' residences, from ambient pollutant monitors at fixed-site locations in each city, and from real-time diaries and questionnaires completed by the technicians and participants. As part of this study, a model to predict personal exposures based on individual time/activity data was developed for comparison to measured concentrations. Predicted concentrations were generally within 25% of the measured concentrations. The microenvironments that people encounter daily provide for widely varying exposures to aldehydes. The activities that occur in those microenvironments can modulate the aldehyde concentrations dramatically, especially for environments such as “indoor at home.” By considering personal activity, location (microenvironment), duration in the microenvironment, and a knowledge of the general concentrations of aldehydes in the various microenvironments, a simple model can do a reasonably good job of predicting the time-averaged personal exposures to aldehydes, even in the absence of monitoring data. Although concentrations of aldehydes measured indoors at the participants' homes tracked well with personal exposure, there were instances where personal exposures and indoor concentrations differed significantly. Key to the ability to predict exposure based on time/activity data is the quality and completeness of the microenvironmental characterizations for the chemicals of interest. Consistent with many earlier studies, personal exposures are difficult to predict using data from regional outdoor monitors.     

Development of a distance-to-roadway proximity metric to compare near-road pollutant levels to a central site monitor

The primary objective of the Detroit Exposure and Aerosol Research Study (DEARS) was to compare air pollutant concentrations measured at various neighborhoods, or exposure monitoring areas (EMAs), throughout a major metropolitan area to levels measured at a central site or community monitor. One of the EMAs was located near a busy freeway (annual average daily traffic (AADT) of ～130,000) so that impacts of mobile sources could be examined. Air pollution concentrations from the roadway-proximate sites were compared to the central site monitor. The volatile organic compounds (VOCs) selected (benzene, toluene, ethylbenzene, m,p- and o-xylene, 1,3 butadiene, 1,3,5-trimethylbenzene and 4-ethyltoluene) are typically associated with mobile sources. Gradients were also evident that demonstrated the amplification of pollutant levels near the roadway compared to the community monitor. A novel distance-to-roadway proximity metric was developed to plot the measurements and model these gradients. Effective distance represents the actual distance an air parcel travels from the middle of a roadway to a site and varies as a function of wind direction, whereas perpendicular distance is a fixed distance oriented normal to the roadway. Perpendicular distance is often used as a proxy for exposures to traffic emissions in epidemiological studies.Elevated concentrations of all the compounds were found for both a summer and winter season. Effective distance was found to be a statistically significant (p < 0.05) univariate predictor for concentrations of toluene, ethylbenzene, m,p-xylene and o-xylene for summer 2005. For each of these pollutants, effective distance yielded lower p-values than the corresponding perpendicular distance models, and model fit improved. Results demonstrate that this near-road EMA had elevated levels of traffic-related VOCs compared to the community monitor, and that effective distance was a more accurate predictor of the degree to which they were elevated as a function of distance. Effective distance produced a range of distance-to-roadway values for a single site based on wind direction, thus increasing the number and range of values that could be used to plot and predict relative differences in pollutant concentrations between two sites.