Atmospheric Environment

Published by Elsevier
Online ISSN: 1352-2310
Publications
Article
Many studies have identified associations between adverse health effects and short-term exposure to particulate matter less than 2.5 microns in diameter (PM(2.5)). These effects, however, are not consistent across geographical regions. This may be due in part to variations in the chemical make-up of PM(2.5) resulting from unique combinations of sources, both primary and secondary, in different regions. The Denver Aerosol Sources and Health (DASH) study is a multi-year time series study designed to characterize the daily chemical composition of PM(2.5) in Denver, identify the major contributing sources, and investigate associations between sources and a broad array of adverse health outcomes.Measurement methodology, field blank correction, pointwise uncertainty estimation and detection limit consideration are discussed in the context of bulk speciation for the DASH study. Results are presented for the first 4.5 years of mass, inorganic ion and bulk carbon speciation. The derived measurement uncertainties were propagated using the root sum of squares method and show good agreement with precision estimates derived from bi-weekly duplicate samples collected on collocated samplers. Gravimetric mass has the most uncertainty of any measurement and reconstructed mass generated from the sum of the individual species shows less uncertainty than measured mass on average. The methods discussed provide a good framework for PM(2.5) speciation measurements and are generalizable to analysis of other environmental measures.
 
Article
Effects of physical/environmental factors on fine particle (PM2.5) exposure, outdoor-to-indoor transport and air exchange rate (AER) were examined. The fraction of ambient PM2.5 found indoors (FINF) and the fraction to which people are exposed (α) modify personal exposure to ambient PM2.5. Because FINF, α, and AER are infrequently measured, some have used air conditioning (AC) as a modifier of ambient PM2.5 exposure. We found no single variable that was a good predictor of AER. About 50% and 40% of the variation in FINF and α, respectively, was explained by AER and other activity variables. AER alone explained 36% and 24% of the variations in FINF and α, respectively. Each other predictor, including Central AC Operation, accounted for less than 4% of the variation. This highlights the importance of AER measurements to predict FINF and α. Evidence presented suggests that outdoor temperature and home ventilation features affect particle losses as well as AER, and the effects differ.
 
Article
We estimate future wildfire activity over the western United States during the mid-21(st) century (2046-2065), based on results from 15 climate models following the A1B scenario. We develop fire prediction models by regressing meteorological variables from the current and previous years together with fire indexes onto observed regional area burned. The regressions explain 0.25-0.60 of the variance in observed annual area burned during 1980-2004, depending on the ecoregion. We also parameterize daily area burned with temperature, precipitation, and relative humidity. This approach explains ~0.5 of the variance in observed area burned over forest ecoregions but shows no predictive capability in the semi-arid regions of Nevada and California. By applying the meteorological fields from 15 climate models to our fire prediction models, we quantify the robustness of our wildfire projections at mid-century. We calculate increases of 24-124% in area burned using regressions and 63-169% with the parameterization. Our projections are most robust in the southwestern desert, where all GCMs predict significant (p<0.05) meteorological changes. For forested ecoregions, more GCMs predict significant increases in future area burned with the parameterization than with the regressions, because the latter approach is sensitive to hydrological variables that show large inter-model variability in the climate projections. The parameterization predicts that the fire season lengthens by 23 days in the warmer and drier climate at mid-century. Using a chemical transport model, we find that wildfire emissions will increase summertime surface organic carbon aerosol over the western United States by 46-70% and black carbon by 20-27% at midcentury, relative to the present day. The pollution is most enhanced during extreme episodes: above the 84(th) percentile of concentrations, OC increases by ~90% and BC by ~50%, while visibility decreases from 130 km to 100 km in 32 Federal Class 1 areas in Rocky Mountains Forest.
 
Article
School buses contribute substantially to childhood air pollution exposures yet they are rarely quantified in epidemiology studies. This paper characterizes fine particulate matter (PM(2.5)) aboard school buses as part of a larger study examining the respiratory health impacts of emission-reducing retrofits.To assess onboard concentrations, continuous PM(2.5) data were collected during 85 trips aboard 43 school buses during normal driving routines, and aboard hybrid lead vehicles traveling in front of the monitored buses during 46 trips. Ordinary and partial least square regression models for PM(2.5) onboard buses were created with and without control for roadway concentrations, which were also modeled. Predictors examined included ambient PM(2.5) levels, ambient weather, and bus and route characteristics.Concentrations aboard school buses (21 mug/m(3)) were four and two-times higher than ambient and roadway levels, respectively. Differences in PM(2.5) levels between the buses and lead vehicles indicated an average of 7 mug/m(3) originating from the bus's own emission sources. While roadway concentrations were dominated by ambient PM(2.5), bus concentrations were influenced by bus age, diesel oxidative catalysts, and roadway concentrations. Cross validation confirmed the roadway models but the bus models were less robust.These results confirm that children are exposed to air pollution from the bus and other roadway traffic while riding school buses. In-cabin air pollution is higher than roadway concentrations and is likely influenced by bus characteristics.
 
Article
Metabolic functions typically increase with human activity, but optimal methods to characterize activity levels for real-time predictions of ventilation volume (l/min) during exposure assessments have not been available. Could tiny, triaxial accelerometers be incorporated into personal level monitors to define periods of acceptable wearing compliance, and allow the exposures (μg/m(3)) to be extended to potential doses in μg/min/kg of body weight? In a pilot effort, we tested: 1) whether appropriately-processed accelerometer data could be utilized to predict compliance and in linear regressions to predict ventilation volumes in real time as an on-board component of personal level exposure sensor systems, and 2) whether locating the exposure monitors on the chest in the breathing zone, provided comparable accelerometric data to other locations more typically utilized (waist, thigh, wrist, etc.). Prototype exposure monitors from RTI International and Columbia University were worn on the chest by a pilot cohort of adults while conducting an array of scripted activities (all <10 METS), spanning common recumbent, sedentary, and ambulatory activity categories. Referee Wocket accelerometers that were placed at various body locations allowed comparison with the chest-located exposure sensor accelerometers. An Oxycon Mobile mask was used to measure oral-nasal ventilation volumes in-situ. For the subset of participants with complete data (n= 22), linear regressions were constructed (processed accelerometric variable versus ventilation rate) for each participant and exposure monitor type, and Pearson correlations computed to compare across scenarios. Triaxial accelerometer data were demonstrated to be adequately sensitive indicators for predicting exposure monitor wearing compliance. Strong linear correlations (R values from 0.77 to 0.99) were observed for all participants for both exposure sensor accelerometer variables against ventilation volume for recumbent, sedentary, and ambulatory activities with MET values ~<6. The RTI monitors mean R value of 0.91 was slightly higher than the Columbia monitors mean of 0.86 due to utilizing a 20 Hz data rate instead of a slower 1 Hz rate. A nominal mean regression slope was computed for the RTI system across participants and showed a modest RSD of +/-36.6%. Comparison of the correlation values of the exposure monitors with the Wocket accelerometers at various body locations showed statistically identical regressions for all sensors at alternate hip, ankle, upper arm, thigh, and pocket locations, but not for the Wocket accelerometer located at the dominant-side wrist location (R=0.57; p=0.016). Even with a modest number of adult volunteers, the consistency and linearity of regression slopes for all subjects were very good with excellent within-person Pearson correlations for the accelerometer versus ventilation volume data. Computing accelerometric standard deviations allowed good sensitivity for compliance assessments even for sedentary activities. These pilot findings supported the hypothesis that a common linear regression is likely to be usable for a wider range of adults to predict ventilation volumes from accelerometry data over a range of low to moderate energy level activities. The predicted volumes would then allow real-time estimates of potential dose, enabling more robust panel studies. The poorer correlation in predicting ventilation rate for an accelerometer located on the wrist suggested that this location should not be considered for predictions of ventilation volume.
 
Article
The effect of the characteristics of the surface on the phototransformation of acridine, one of the most abundant azapolycyclic compounds encountered in urban atmospheres, and of one of its principal photoproducts, acridone, was studied when adsorbed onto models of the atmospherice particulate matter. For this purpose, relative photodegradation rates were determined from absorption or emission intensities as a function of irradiation times, and some products were isolated and characterized. The relative photodegradation rates of adsorbed acridine show the tendency (NH(4))(2) SO(4) > MgO > Al(2)O(3) >SiO(2). In general, the rates decrease as the fraction of protonated acridine species on the surface increases in MgO, Al(2)O(3), and SiO(2), except for (NH(4))(2) SO(4) where a fast surface reaction occurs. Oxygen reduces the photodestruction rates by as much as 40 to 60% when compared to an inert atmosphere, implying the participation of an acrideine triplet state in the transformation processes on all surfaces except on (NH(4))(2)SO(4). Acridone, a major product, undergoes a photoinduced tautomerization to 9-hydroxy acridine. The formation of a dihydrodiol, another photoproduct of acridine, is suggested by comparison to reported spectral properties of these compounds. This is formed through a singlet oxygen reaction. Photoproducts showing the absence of the narrow absorption band of 250 nm, characteristic of the pi -->pi* transition in tricyclic aromatics, were detected in small yields but not identified. These results suggest possible photochemical transformation pathways that could lead to the ultimate fate of these pollutants in the environment.
 
Article
We have measured PCBs in 184 air samples collected at 37 sites in the city of Chicago using an innovative system of high-volume air samplers mounted on two health clinic vans. Here we describe results of sampling conducted from November 2006 to November 2007. The samples were analyzed for all 209 PCB congeners using a gas chromatograph with tandem mass spectrometry (GC-MS/MS). The ΣPCBs (sum of 169 peaks) in Chicago ranged from 75 pg m(-3) to 5500 pg m(-3) and primarily varied as a function of temperature. The congener patterns are surprisingly similar throughout the city even though the temperature-corrected concentrations vary by more than an order of magnitude. The average profile resembles a mixture of Aroclor 1242 and Aroclor 1254, and includes many congeners that have been identified as being aryl hydrocarbon receptor (AhR) agonists (dioxin-like) and/or neurotoxins. The toxic equivalence (TEQ) and neurotoxic equivalence (NEQ) in air were calculated and investigated for their spatial distribution throughout the urban-industrial complex of Chicago. The NEQ concentrations are linearly correlated with ΣPCBs while the TEQ concentrations are not predictable. The findings of this study suggest that airborne PCBs in Chicago are widely present and elevated in residential communities; there are multiple sources rather than one or a few locations of very high emissions; the emission includes congeners associated with dioxin-like and neurotoxic effects and congeners associated with unidentified sources.
 
Article
During a total of 11 months, cloud condensation nuclei (CCN at super-saturation S 0.5%) and condensation nuclei (CN) concentrations were measured in the urban background aerosol of Vienna, Austria. For several months, number size distributions between 13.22 nm and 929 nm were also measured with a scanning mobility particle spectrometer (SMPS). Activation ratios (i.e. CCN/CN ratios) were calculated and apparent activation diameters obtained by integrating the SMPS size distributions. Variations in all CCN parameters (concentration, activation ratio, apparent activation diameter) are quite large on timescales of days to weeks. Passages of fronts influenced CCN parameters. Concentrations decreased with the passage of a front. No significant differences were found for fronts from different sectors (for Vienna mainly north to west and south to east). CCN concentrations at 0.5% S ranged from 160 cm(-3) to 3600 cm(-3) with a campaign average of 820 cm(-3). Activation ratios were quite low (0.02-0.47, average: 0.13) and comparable to activation ratios found in other polluted regions (e.g. Cubison et al., 2008). Apparent activation diameters were found to be much larger (campaign average: 169 nm, range: (69-370) nm) than activation diameters for single-salt particles (around 50 nm depending on the salt). Contrary to CN concentrations, which are influenced by source patterns, CCN concentrations did not exhibit distinct diurnal patterns. Activation ratios showed diurnal variations counter-current to the variations of CN concentrations.
 
Article
Land-use regression (LUR) models have been developed to estimate spatial distributions of traffic-related pollutants. Several studies have examined spatial autocorrelation among residuals in LUR models, but few utilized spatial residual information in model prediction, or examined the impact of modeling methods, monitoring site selection, or traffic data quality on LUR performance. This study aims to improve spatial models for traffic-related pollutants using generalized additive models (GAM) combined with cokriging of spatial residuals. Specifically, we developed spatial models for nitrogen dioxide (NO(2)) and nitrogen oxides (NO(x)) concentrations in Southern California separately for two seasons (summer and winter) based on over 240 sampling locations. Pollutant concentrations were disaggregated into three components: local means, spatial residuals, and normal random residuals. Local means were modeled by GAM. Spatial residuals were cokriged with global residuals at nearby sampling locations that were spatially auto-correlated. We compared this two-stage approach with four commonly-used spatial models: universal kriging, multiple linear LUR and GAM with and without a spatial smoothing term. Leave-one-out cross validation was conducted for model validation and comparison purposes. The results show that our GAM plus cokriging models predicted summer and winter NO(2) and NO(x) concentration surfaces well, with cross validation R(2) values ranging from 0.88 to 0.92. While local covariates accounted for partial variance of the measured NO(2) and NO(x) concentrations, spatial autocorrelation accounted for about 20% of the variance. Our spatial GAM model improved R(2) considerably compared to the other four approaches. Conclusively, our two-stage model captured summer and winter differences in NO(2) and NO(x) spatial distributions in Southern California well. When sampling location selection cannot be optimized for the intended model and fewer covariates are available as predictors for the model, the two-stage model is more robust compared to multiple linear regression models.
 
Article
This paper presents a Bayesian hierarchical spatiotemporal method of interpolation, termed as Markov Cube Kriging (MCK). The classical Kriging methods become computationally prohibitive, especially for large datasets due to the O(n(3)) matrix decomposition. MCK offers novel and computationally efficient solutions to address spatiotemporal misalignment, mismatch in the spatiotemporal scales and missing values across space and time in large spatiotemporal datasets. MCK is flexible in that it allows for non-separable spatiotemporal structure and nonstationary covariance at the hierarchical spatiotemporal scales. Employing MCK we developed estimates of daily concentration of fine particulates matter ≤2.5 μm in aerodynamic diameter (PM2.5) at 2.5 km spatial grid for the Cleveland Metropolitan Statistical Area, 2000 to 2009. Our validation and cross-validation suggest that MCK achieved robust prediction of spatiotemporal random effects and underlying hierarchical and nonstationary spatiotemporal structure in air pollution data. MCK has important implications for environmental epidemiology and environmental sciences for exposure quantification and collocation of data from different sources, available at different spatiotemporal scales.
 
Article
This study was conducted to determine both optimal settings applied to the plume dispersion model, AERMOD, and a scalable emission factor for accurately determining the spatial distribution of hydrogen sulfide concentrations in the vicinity of swine concentrated animal feeding operations (CAFOs). These operations emit hydrogen sulfide from both housing structures and waste lagoons. With ambient measurements made at 4 stations within 1 km of large swine CAFOs in Iowa, an inverse-modeling approach applied to AERMOD was used to determine hydrogen sulfide emission rates. CAFO buildings were treated as volume sources whereas nearby lagoons were modeled as area sources. The robust highest concentration (RHC), calculated for both measured and modeled concentrations, was used as the metric for adjusting the emission rate until the ratio of the two RHC levels was unity. Utilizing this approach, an average emission flux rate of 0.57 µg/m(2)-s was determined for swine CAFO lagoons. Using the average total animal weight (kg) of each CAFO, an average emission factor of 6.06 × 10(-7) µg/yr-m(2)-kg was calculated. From studies that measured either building or lagoon emission flux rates, building fluxes, on a floor area basis, were considered equal to lagoon flux rates. The emission factor was applied to all CAFOs surrounding the original 4 sites and surrounding an additional 6 sites in Iowa, producing an average modeled-to-measured RHC ratio of 1.24. When the emission factor was applied to AERMOD to simulate the spatial distribution of hydrogen sulfide around a hypothetical large swine CAFO (1M kg), concentrations 0.5 km from the CAFO were 35 ppb and dropped to 2 ppb within 6 km of the CAFO. These values compare to a level of 30 ppb that has been determined by the State of Iowa as a threshold level for ambient hydrogen sulfide levels.
 
Article
No personal aerosol sampler has been evaluated for monitoring aeroallergens in outdoor field conditions and compared to conventional stationary aerobiological samplers. Recently developed Button Personal Inhalable Aerosol Sampler has demonstrated high sampling efficiency for non-biological particles and low sensitivity to the wind direction and velocity. The aim of the present study was to evaluate the Button Sampler for the measurement of outdoor pollen grains and fungal spores side-by-side with the widely used Rotorod Sampler. The sampling was performed for 8 months (spring, summer and fall) at a monitoring station on the roof of a two-storied office building located in the center of the city of Cincinnati. Two identical Button Samplers, one oriented towards the most prevalent wind and the other towards the opposite wind and a Rotorod Sampler were placed side-by-side. The total fungal spore concentration ranged from 129 to 12,980 spores m(-3) (number per cubic meter of air) and the total pollen concentration from 4 to 4536 pollen m(-3). The fungal spore concentrations obtained with the two Button Samplers correlated well (r = 0.95; p<0.0001). The pollen data also showed positive correlation. These findings strongly support the results of earlier studies conducted with non-biological aerosol particles, which demonstrated a low wind dependence of the performance of the Button Sampler compared to other samplers. The Button Sampler's inlet efficiency was found to be more dependent on wind direction when sampling larger sized Pinaceae pollen grains (aerodynamic diameter approximately 65 mum). Compared to Rotorod, both Button Samplers measured significantly higher total fungal spore concentrations. For total pollen count, the Button Sampler facing the prevalent wind showed concentrations levels comparable to that of the Rotorod, but the Button Sampler oriented opposite to the prevalent wind demonstrated lower concentration levels. Overall, it was concluded that the Button Sampler is efficient for the personal sampling of outdoor aeroallergens, and is especially beneficial for aeroallergens of small particle size.
 
Article
Atmospheric remote sensing offers a unique opportunity to compute indirect estimates of air quality, which are critically important for the management and surveillance of air quality in megacities of developing countries, particularly in India and China, which have experienced elevated concentration of air pollution but lack adequate spatial-temporal coverage of air pollution monitoring. This article examines the relationship between aerosol optical depth (AOD) estimated from satellite data at 5 km spatial resolution and the mass of fine particles ≤2.5 μm in aerodynamic diameter (PM(2.5)) monitored on the ground in Delhi Metropolitan where a series of environmental laws have been instituted in recent years.PM(2.5) monitored at 113 sites were collocated by time and space with the AOD computed using the data from Moderate Resolution Imaging Spectroradiometer (MODIS onboard the Terra satellite). MODIS data were acquired from NASA's Goddard Space Flight Center Earth Sciences Distributed Active Archive Center (DAAC). Our analysis shows a significant positive association between AOD and PM(2.5). After controlling for weather conditions, a 1% change in AOD explains 0.52±0.202% and 0.39±0.15% change in PM(2.5) monitored within ±45 and 150 min intervals of AOD data. This relationship will be used to estimate air quality surface for previous years, which will allow us to examine the time-space dynamics of air pollution in Delhi following recent air quality regulations, and to assess exposure to air pollution before and after the regulations and its impact on health.
 
Article
Quantitative assessment of human exposures and health effects due to air pollution involve detailed characterization of impacts of air quality on exposure and dose. A key challenge is to integrate these three components on a consistent spatial and temporal basis taking into account linkages and feedbacks. The current state-of-practice for such assessments is to exercise emission, meteorology, air quality, exposure, and dose models separately, and to link them together by using the output of one model as input to the subsequent downstream model. Quantification of variability and uncertainty has been an important topic in the exposure assessment community for a number of years. Variability refers to differences in the value of a quantity (e.g., exposure) over time, space, or among individuals. Uncertainty refers to lack of knowledge regarding the true value of a quantity. An emerging challenge is how to quantify variability and uncertainty in integrated assessments over the source-to-dose continuum by considering contributions from individual as well as linked components. For a case study of fine particulate matter (PM(2.5)) in North Carolina during July 2002, we characterize variability and uncertainty associated with each of the individual concentration, exposure and dose models that are linked, and use a conceptual framework to quantify and evaluate the implications of coupled model uncertainties. We find that the resulting overall uncertainties due to combined effects of both variability and uncertainty are smaller (usually by a factor of 3-4) than the crudely multiplied model-specific overall uncertainty ratios. Future research will need to examine the impact of potential dependencies among the model components by conducting a truly coupled modeling analysis.
 
Article
Accurate quantification of exposures to traffic-related air pollution in near-highway neighborhoods is challenging due to the high degree of spatial and temporal variation of pollutant levels. The objective of this study was to measure air pollutant levels in a near-highway urban area over a wide range of traffic and meteorological conditions using a mobile monitoring platform. The study was performed in a 2.3-km(2) area in Somerville, Massachusetts (USA), near Interstate I-93, a highway that carries 150,000 vehicles per day. The mobile platform was equipped with rapid-response instruments and was driven repeatedly along a 15.4-km route on 55 days between September 2009 and August 2010. Monitoring was performed in 4-6-hour shifts in the morning, afternoon and evening on both weekdays and weekends in winter, spring, summer and fall. Measurements were made of particle number concentration (PNC; 4-3,000 nm), particle size distribution, fine particle mass (PM(2.5)), particle-bound polycyclic aromatic hydrocarbons (pPAH), black carbon (BC), carbon monoxide (CO), and nitrogen oxides (NO and NO(x)). The highest pollutant concentrations were measured within 0-50 m of I-93 with distance-decay gradients varying depending on traffic and meteorology. The most pronounced variations were observed for PNC. Annual median PNC 0-50 m from I-93 was two-fold higher compared to the background area (>1 km from I-93). In general, PNC levels were highest in winter and lowest in summer and fall, higher on weekdays and Saturdays compared to Sundays, and higher during morning rush hour compared to later in the day. Similar spatial and temporal trends were observed for NO, CO and BC, but not for PM(2.5). Spatial variations in PNC distance-decay gradients were non-uniform largely due to contributions from local street traffic. Hour-to-hour, day-to-day and season-to-season variations in PNC were of the same magnitude as spatial variations. Datasets containing fine-scale temporal and spatial variation of air pollution levels near highways may help to inform exposure assessment efforts.
 
Article
This, the first systematic study, quantifies the health effects of air quality regulations in Delhi, which adopted radical measures to improve air quality, including, for example, the conversion of all commercial vehicles to compressed natural gas (CNG), and the closure of polluting industries in residential areas from 2000 to 2002. Air pollution data, collected at 113 sites (spread across Delhi and its neighboring areas) from July-December 2003, were used to compute exposure at the place of residence of 3,989 subjects. A socio-economic and respiratory health survey was administered in 1,576 households. This survey collected time-use, residence histories, demographic information, and direct measurements of lung function with subjects. The optimal interpolation methods were used to link air pollution and respiratory health data at the place of their residence. Resident histories, in combination with secondary data, were used to impute cumulative exposure prior to the air-quality interventions, and the effects of recent air quality measures on lung function were then evaluated. Three important findings emerge from the analysis. First, the interventions were associated with a significant improvement in respiratory health. Second, the effect of these interventions varied significantly by gender and income. Third, consistent with a causal interpretation of these results, effects were the strongest among those individuals who spend a disproportionate share of their time out-of-doors.
 
Article
The spatial variations of volatile organic compounds (VOCs) were characterized in the Village of Waterfront South neighborhood (WFS), a "hot spot" for air toxics in Camden, NJ. This was accomplished by conducting "spatial saturation sampling" for 11 VOCs using 3500 OVM passive samplers at 22 sites in WFS and 16 sites in Copewood/Davis Streets (CDS) neighborhood, an urban reference area located ∼1000 m east of the WFS. Sampling durations were 24 and 48 h. For all 3 sampling campaigns (2 in summer and 1 in winter), the spatial variations and median concentrations of toluene, ethylbenzene, and xylenes (TEX) were found significantly higher (p < 0.05) in WFS than in CDS, where the spatial distributions of these compounds were relatively uniform. The highest concentrations of methyl tert-butyl ether (MTBE) (maximum of 159 μg m(-3)) were always found at one site close to a car scrapping facility in WFS during each sampling campaign. The spatial variation of benzene in WFS was found to be marginally higher (p = 0.057) than in CDS during one sampling campaign, but similar in the other two sampling periods. The results obtained from the analyses of correlation among all species and the proximity of sampling site to source indicated that local stationary sources in WFS have significant impact on MTBE and BTEX air pollution in WFS, and both mobile sources and some of the stationary sources in WFS contributed to the ambient levels of these species measured in CDS. The homogenous spatial distributions (%RSD < 24%) and low concentrations of chloroform (0.02-0.23 μg m(-3)) and carbon tetrachloride (0.45-0.51 μg m(-3)) indicated no significant local sources in the study areas. Further, results showed that the sampling at the fixed monitoring site may under- or over-estimate air pollutant levels in a "hot spot" area, suggesting that the "spatial saturation sampling" is necessary for conducting accurate assessment of air pollution and personal exposure in a community with a high density of sources.
 
Article
In recent years, geostatistical modeling has been used to inform air pollution health studies. In this study, distributions of daily ambient concentrations were modeled over space and time for 12 air pollutants. Simulated pollutant fields were produced for a 6-year time period over the 20-county metropolitan Atlanta area using the Stanford Geostatistical Modeling Software (SGeMS). These simulations incorporate the temporal and spatial autocorrelation structure of ambient pollutants, as well as season and day-of-week temporal and spatial trends; these fields were considered to be the true ambient pollutant fields for the purposes of the simulations that followed. Simulated monitor data at the locations of actual monitors were then generated that contain error representative of instrument imprecision. From the simulated monitor data, four exposure metrics were calculated: central monitor and unweighted, population-weighted, and area-weighted averages. For each metric, the amount and type of error relative to the simulated pollutant fields are characterized and the impact of error on an epidemiologic time-series analysis is predicted. The amount of error, as indicated by a lack of spatial autocorrelation, is greater for primary pollutants than for secondary pollutants and is only moderately reduced by averaging across monitors; more error will result in less statistical power in the epidemiologic analysis. The type of error, as indicated by the correlations of error with the monitor data and with the true ambient concentration, varies with exposure metric, with error in the central monitor metric more of the classical type (i.e., independent of the monitor data) and error in the spatial average metrics more of the Berkson type (i.e., independent of the true ambient concentration). Error type will affect the bias in the health risk estimate, with bias toward the null and away from the null predicted depending on the exposure metric; population-weighting yielded the least bias.
 
Article
The past 50 years have seen rapid development of new building materials, furnishings, and consumer products and a corresponding explosion in new chemicals in the built environment. While exposure levels are largely undocumented, they are likely to have increased as a wider variety of chemicals came into use, people began spending more time indoors, and air exchange rates decreased to improve energy efficiency. As a result of weak regulatory requirements for chemical safety testing, only limited toxicity data are available for these chemicals. Over the past 15 years, some chemical classes commonly used in building materials, furnishings, and consumer products have been shown to be endocrine disrupting chemicals-that is they interfere with the action of endogenous hormones. These include PCBs, used in electrical equipment, caulking, paints and surface coatings; chlorinated and brominated flame retardants, used in electronics, furniture, and textiles; pesticides, used to control insects, weeds, and other pests in agriculture, lawn maintenance, and the built environment; phthalates, used in vinyl, plastics, fragrances, and other products; alkylphenols, used in detergents, pesticide formulations, and polystyrene plastics; and parabens, used to preserve products like lotions and sunscreens. This paper summarizes reported indoor and outdoor air concentrations, chemical use and sources, and toxicity data for each of these chemical classes. While industrial and transportation-related pollutants have been shown to migrate indoors from outdoor sources, it is expected that indoor sources predominate for these consumer product chemicals; and some studies have identified indoor sources as the predominant factor influencing outdoor ambient air concentrations in densely populated areas. Mechanisms of action, adverse effects, and dose-response relationships for many of these chemicals are poorly understood and no systematic screening of common chemicals for endocrine disrupting effects is currently underway, so questions remain as to the health impacts of these exposures.
 
Article
A number of recent toxicity studies have highlighted the increased potency of oxygen analogs (oxons) of several organophosphorus (OP) pesticides. These findings were a major concern after environmental oxons were identified in environmental samples from air and surfaces following agricultural spray applications in California and Washington State. This paper reports on the validity of oxygen analog measurements in air samples for the OP pesticide, chlorpyrifos. Controlled environmental and laboratory experiments were used to examine artificial formation of chlorpyrifos-oxon using OSHA Versatile Sampling (OVS) tubes as recommended by NIOSH method 5600. Additionally, we compared expected chlorpyrifos-oxon attributable to artificial transformation to observed chlorpyrifos-oxon in field samples from a 2008 Washington State Department of Health air monitoring study using non-parametric statistical methods. The amount of artificially transformed oxon was then modeled to determine the amount of oxon present in the environment. Toxicity equivalency factors (TEFs) for chlorpyrifos-oxon were used to calculate chlorpyrifos-equivalent air concentrations. The results demonstrate that the NIOSH-recommended sampling matrix (OVS tubes with XAD-2 resin) was found to artificially transform up to 30% of chlorpyrifos to chlorpyrifos-oxon, with higher percentages at lower concentrations (< 30 ng/m3) typical of ambient or residential levels. Overall, the 2008 study data had significantly greater oxon than expected by artificial transformation, but the exact amount of environmental oxon in air remains difficult to quantify with the current sampling method. Failure to conduct laboratory analysis for chlorpyrifos-oxon may result in underestimation of total pesticide concentration when using XAD-2 resin matrices for occupational or residential sampling. Alternative methods that can accurately measure both OP pesticides and their oxygen analogs should be used for air sampling, and a toxicity equivalent factor approach should be used to determine potential health risks from exposures.
 
Article
We observed elevated air pollutant concentrations, especially of ultrafine particles (UFP), black carbon (BC) and NO, across the residential neighborhood of the Boyle Heights Community (BH) of Los Angeles, California. Using an electric vehicle mobile platform equipped with fast response instruments, real-time air pollutant concentrations were measured in BH in spring and summer of 2008. Pollutant concentrations varied significantly in the two seasons, on different days, and by time of day, with an overall average UFP concentration in the residential areas of ~33 000 cm(-3). The averaged UFP, BC, and NO concentrations measured on Soto St, a major surface street in BH, were 57 000 cm(-3), 5.1 µg m(-3), and 67 ppb, respectively. Concentrations of UFP across the residential areas in BH were nearly uniform spatially, in contrast to other areas in the greater metropolitan area of Los Angeles where UFP concentrations exhibit strong gradients downwind of roadways. We attribute this "UFP cloud" to high traffic volumes, including heavy duty diesel trucks on the freeways which surround and traverse BH, and substantial numbers of high-emitting vehicles (HEVs) on the surface streets traversing BH. Additionally, the high density of stop signs and lights and short block lengths, requiring frequent accelerations of vehicles, may contribute. The data also support a role for photochemical production of UFP in the afternoon. UFP concentration peaks (5 s average) of up to 9 million particles cm(-3) were also observed immediately behind HEVs when they accelerated from stop lights in the BH neighborhood and areas immediately adjacent. Although encounters with HEV during mornings accounted for only about 6% and 17% of time spent monitoring residential areas and major surface streets, HEV contributed to about 28% and 53% of total ultrafine particles measured on the route, respectively. The observation of elevated pollutant number concentrations across the Boyle Heights community highlights how multiple factors combine to create high pollutant levels, and has important human exposure assessment implications, including the potential utility of our data as inputs to epidemiological studies.
 
Article
BACKGROUND: Epidemiological studies that assess the health effects of long-term exposure to ambient air pollution are used to inform public policy. These studies rely on exposure models that use data collected from pollution monitoring sites to predict exposures at subject locations. Land use regression (LUR) and universal kriging (UK) have been suggested as potential prediction methods. We evaluate these approaches on a dataset including measurements from three seasons in Los Angeles, CA. METHODS: The measurements of gaseous oxides of nitrogen (NOx) used in this study are from a "snapshot" sampling campaign that is part of the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air). The measurements in Los Angeles were collected during three two-week periods in the summer, autumn, and winter, each with about 150 sites. The design included clusters of monitors on either side of busy roads to capture near-field gradients of traffic-related pollution. LUR and UK prediction models were created using geographic information system (GIS)-based covariates. Selection of covariates was based on 10-fold cross-validated (CV) R(2) and root mean square error (RMSE). Since UK requires specialized software, a computationally simpler two-step procedure was also employed to approximate fitting the UK model using readily available regression and GIS software. RESULTS: UK models consistently performed as well as or better than the analogous LUR models. The best CV R(2) values for season-specific UK models predicting log(NOx) were 0.75, 0.72, and 0.74 (CV RMSE 0.20, 0.17, and 0.15) for summer, autumn, and winter, respectively. The best CV R(2) values for season-specific LUR models predicting log(NOx) were 0.74, 0.60, and 0.67 (CV RMSE 0.20, 0.20, and 0.17). The two-stage approximation to UK also performed better than LUR and nearly as well as the full UK model with CV R(2) values 0.75, 0.70, and 0.70 (CV RMSE 0.20, 0.17, and 0.17) for summer, autumn, and winter, respectively. CONCLUSION: High quality LUR and UK prediction models for NOx in Los Angeles were developed for the three seasons based on data collected for MESA Air. In our study, UK consistently outperformed LUR. Similarly, the 2-step approach was more effective than the LUR models, with performance equal to or slightly worse than UK.
 
Article
In this paper we have coupled the CMAQ and ADMS air quality models to predict hourly concentrations of NO X , NO2 and O3 for London at a spatial scale of 20 m × 20 m. Model evaluation has demonstrated reasonable agreement with measurements from 80 monitoring sites in London. For NO2 the model evaluation statistics gave 73% of the hourly concentrations within a factor of two of observations, a mean bias of -4.7 ppb and normalised mean bias of -0.17, a RMSE value of 17.7 and an r value of 0.58. The equivalent results for O3 were 61% (FAC2), 2.8 ppb (MB), 0.15 (NMB), 12.1 (RMSE) and 0.64 (r). Analysis of the errors in the model predictions by hour of the week showed the need for improvements in predicting the magnitude of road transport related NO X emissions as well as the hourly emissions scaling in the model. These findings are consistent with recent evidence of UK road transport NO X emissions, reported elsewhere. The predictions of wind speed using the WRF model also influenced the model results and contributed to the daytime over prediction of NO X concentrations at the central London background site at Kensington and Chelsea. An investigation of the use of a simple NO-NO2-O3 chemistry scheme showed good performance close to road sources, and this is also consistent with previous studies. The coupling of the two models raises an issue of emissions double counting. Here, we have put forward a pragmatic solution to this problem with the result that a median double counting error of 0.42% exists across 39 roadside sites in London. Finally, whilst the model can be improved, the current results show promise and demonstrate that the use of a combination of regional scale and local scale models can provide a practical modelling tool for policy development at intergovernmental, national and local authority level, as well as for use in epidemiological studies.
 
Article
In this study, the culturability of indoor and outdoor airborne fungi was determined through long-term sampling (24-h) using a Button Personal Inhalable Aerosol Sampler. The air samples were collected during three seasons in six Cincinnati area homes that were free from moisture damage or visible mold. Cultivation and total microscopic enumeration methods were employed for the sample analysis. The geometric means of indoor and outdoor culturable fungal concentrations were 88 and 102 colony-forming units (CFU) m(-3), respectively, with a geometric mean of the I/O ratio equal to 0.66. Overall, 26 genera of culturable fungi were recovered from the indoor and outdoor samples. For total fungal spores, the indoor and outdoor geometric means were 211 and 605 spores m(-3), respectively, with a geometric mean of I/O ratio equal to 0.32. The identification revealed 37 fungal genera from indoor and outdoor samples based on the total spore analysis. Indoor and outdoor concentrations of culturable and total fungal spores showed significant correlations (r = 0.655, p<0.0001 and r = 0.633, p<0.0001, respectively). The indoor and outdoor median viabilities of fungi were 55% and 25%, respectively, which indicates that indoor environment provides more favorable survival conditions for the aerosolized fungi. Among the seasons, the highest indoor and outdoor culturability of fungi was observed in the fall. Cladosporium had a highest median value of culturability (38% and 33% for indoor and outdoor, respectively) followed by Aspergillus/Penicillium (9% and 2%) among predominant genera of fungi. Increased culturability of fungi inside the homes may have important implications because of the potential increase in the release of allergens from viable spores and pathogenicity of viable fungi on immunocompromised individuals.
 
Article
Allergic airway diseases represent a complex health problem which can be exacerbated by the synergistic action of pollen particles and air pollutants such as ozone. Understanding human exposures to aeroallergens requires accurate estimates of the spatial distribution of airborne pollen levels as well as of various air pollutants at different times. However, currently there are no established methods for estimating allergenic pollen emissions and concentrations over large geographic areas such as the United States. A mechanistic modeling system for describing pollen emissions and transport over extensive domains has been developed by adapting components of existing regional scale air quality models and vegetation databases. First, components of the Biogenic Emissions Inventory System (BEIS) were adapted to predict pollen emission patterns. Subsequently, the transport module of the Community Multiscale Air Quality (CMAQ) modeling system was modified to incorporate description of pollen transport. The combined model, CMAQ-pollen, allows for simultaneous prediction of multiple air pollutants and pollen levels in a single model simulation, and uses consistent assumptions related to the transport of multiple chemicals and pollen species. Application case studies for evaluating the combined modeling system included the simulation of birch and ragweed pollen levels for the year 2002, during their corresponding peak pollination periods (April for birch and September for ragweed). The model simulations were driven by previously evaluated meteorological model outputs and emissions inventories for the eastern United States for the simulation period. A semi-quantitative evaluation of CMAQ-pollen was performed using tree and ragweed pollen counts in Newark, NJ for the same time periods. The peak birch pollen concentrations were predicted to occur within two days of the peak measurements, while the temporal patterns closely followed the measured profiles of overall tree pollen. For the case of ragweed pollen, the model was able to capture the patterns observed during September 2002, but did not predict an early peak; this can be associated with a wider species pollination window and inadequate spatial information in current land cover databases. An additional sensitivity simulation was performed to comparatively evaluate the dispersion patterns predicted by CMAQ-pollen with those predicted by the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model, which is used extensively in aerobiological studies. The CMAQ estimated concentration plumes matched the equivalent pollen scenario modeled with HYSPLIT. The novel pollen modeling approach presented here allows simultaneous estimation of multiple airborne allergens and other air pollutants, and is being developed as a central component of an integrated population exposure modeling system, the Modeling Environment for Total Risk studies (MENTOR) for multiple, co-occurring contaminants that include aeroallergens and irritants.
 
Article
The "Cincinnati Childhood Allergy and Air Pollution Study (CCAAPS)" is underway to determine if infants who are exposed to diesel engine exhaust particles are at an increased risk for atopy and atopic respiratory disorders, and to determine if this effect is magnified in a genetically at risk population. In support of this study, a methodology has been developed to allocate local traffic source contributions to ambient PM(2.5) in the Cincinnati airshed. As a first step towards this allocation, UNMIX was used to generate factors for ambient PM(2.5) at two sites near at interstate highway. Procedures adopted to collect, analyze and prepare the data sets to run UNMIX are described. The factors attributed to traffic sources were similar for the two sites. These factors were also similar to locally measured truck engine-exhaust enriched ambient profiles. The temporal variation of the factors was analyzed with clear differences observed between factors attributed to traffic sources and combustion-related regional secondary sources.
 
Article
A method for estimating in-vehicle PM(2.5) exposure as part of a scenario-based population simulation model is developed and assessed. In existing models, such as the Stochastic Exposure and Dose Simulation model for Particulate Matter (SHEDS-PM), in-vehicle exposure is estimated using linear regression based on area-wide ambient PM(2.5) concentration. An alternative modeling approach is explored based on estimation of near-road PM(2.5) concentration and an in-vehicle mass balance. Near-road PM(2.5) concentration is estimated using a dispersion model and fixed site monitor (FSM) data. In-vehicle concentration is estimated based on air exchange rate and filter efficiency. In-vehicle concentration varies with road type, traffic flow, windspeed, stability class, and ventilation. Average in-vehicle exposure is estimated to contribute 10 to 20 percent of average daily exposure. The contribution of in-vehicle exposure to total daily exposure can be higher for some individuals. Recommendations are made for updating exposure models and implementation of the alternative approach.
 
Article
Generation of reactive oxygen species (ROS) - including superoxide ((•)O(2) (-)), hydrogen peroxide (HOOH), and hydroxyl radical ((•)OH) - has been suggested as one mechanism underlying the adverse health effects caused by ambient particulate matter (PM). In this study we compare HOOH and (•)OH production from fine and coarse PM collected at an urban (Fresno) and rural (Westside) site in the San Joaquin Valley (SJV) of California, as well as from laboratory solutions containing dissolved copper or iron. Samples were extracted in a cell-free, phosphate-buffered saline (PBS) solution containing 50 μM ascorbate (Asc). In our laboratory solutions we find that Cu is a potent source of both HOOH and (•)OH, with approximately 90% of the electrons that can be donated from Asc ending up in HOOH and (•)OH after 4 h. In contrast, in Fe solutions there is no measurable HOOH and only a modest production of (•)OH. Soluble Cu in the SJV PM samples is also a dominant source of HOOH and (•)OH. In both laboratory copper solutions and extracts of ambient particles we find much more production of HOOH compared to (•)OH: e.g., HOOH generation is approximately 30 - 60 times faster than (•)OH generation. The formation of HOOH and (•)OH are positively correlated, with roughly 3 % and 8 % of HOOH converted to (•)OH after 4 and 24 hr of extraction, respectively. Although the SJV PM produce much more HOOH than (•)OH, since (•)OH is a much stronger oxidant it is unclear which species might be more important for oxidant-mediated toxicity from PM inhalation.
 
Article
An integrated exposure model was developed that estimates nitrogen dioxide (NO(2)) concentration at residences using geographic information systems (GIS) and variables derived within residential buffers representing traffic volume and landscape characteristics including land use, population density and elevation. Multiple measurements of NO(2) taken outside of 985 residences in Connecticut were used to develop the model. A second set of 120 outdoor NO(2) measurements as well as cross-validation were used to validate the model. The model suggests that approximately 67% of the variation in NO(2) levels can be explained by: traffic and land use primarily within 2 km of a residence; population density; elevation; and time of year. Potential benefits of this model for health effects research include improved spatial estimations of traffic-related pollutant exposure and reduced need for extensive pollutant measurements. The model, which could be calibrated and applied in areas other than Connecticut, has importance as a tool for exposure estimation in epidemiological studies of traffic-related air pollution.
 
Article
Ozone (O3) fluxes above a temperate mountain grassland were measured by means of the eddy covariance (EC) method using a slow-response O3 analyser. The resultant flux loss was corrected for by a series of transfer functions which model the various sources of high- and, in particular, low-pass filtering. The resulting correction factors varied on average between 1.7 and 3.5 during night and day time, respectively. A cospectral analysis confirmed the accuracy of this approach. O3 fluxes were characterised by a comparatively large random uncertainty, which during daytime typically amounted to 60 %. EC O3 fluxes were compared against O3 flux measurements made concurrently with the flux-gradient (FG) method. The two methods generally agreed well, except for a period between sun rise and early afternoon, when the FG method was suspected of being affected by the presence of photochemical sources/sinks. O3 flux magnitudes and deposition velocities determined with the EC method compared nicely with the available literature from grassland studies. We conclude that our understanding of the causes and consequences of various sources of flux loss (associated with any EC system) has sufficiently matured so that also less-than-ideal instrumentation may be used in EC flux applications, albeit at the cost of relatively large empirical corrections.
 
Article
Many cohort studies in environmental epidemiology require accurate modeling and prediction of fine scale spatial variation in ambient air quality across the U.S. This modeling requires the use of small spatial scale geographic or "land use" regression covariates and some degree of spatial smoothing. Furthermore, the details of the prediction of air quality by land use regression and the spatial variation in ambient air quality not explained by this regression should be allowed to vary across the continent due to the large scale heterogeneity in topography, climate, and sources of air pollution. This paper introduces a regionalized national universal kriging model for annual average fine particulate matter (PM2.5) monitoring data across the U.S. To take full advantage of an extensive database of land use covariates we chose to use the method of Partial Least Squares, rather than variable selection, for the regression component of the model (the "universal" in "universal kriging") with regression coefficients and residual variogram models allowed to vary across three regions defined as West Coast, Mountain West, and East. We demonstrate a very high level of cross-validated accuracy of prediction with an overall R (2) of 0.88 and well-calibrated predictive intervals. In accord with the spatially varying characteristics of PM2.5 on a national scale and differing kriging smoothness parameters, the accuracy of the prediction varies by region with predictive intervals being notably wider in the West Coast and Mountain West in contrast to the East.
 
Article
Inhalation of ambient particulate matter causes morbidity and mortality in humans. One hypothesized mechanism of toxicity is the particle-induced formation of reactive oxygen species (ROS) - including the highly damaging hydroxyl radical ((·)OH) - followed by inflammation and a variety of diseases. While past studies have found correlations between ROS formation and a variety of metals, there are no quantitative measurements of (·)OH formation from transition metals at concentrations relevant to 24-hour ambient particulate exposure. This research reports specific and quantitative measurements of (·)OH formation from 10 individual transition metals (and several mixtures) in a cell-free surrogate lung fluid (SLF) with four antioxidants: ascorbate, citrate, glutathione, and uric acid. We find that Fe and Cu can produce (·)OH under all antioxidant conditions as long as ascorbate is present and that mixtures of the two metals synergistically increase (·)OH production. Manganese and vanadium can also produce (·)OH under some conditions, but given that their ambient levels are typically very low, these metals are not likely to chemically produce significant levels of (·)OH in the lung fluid. Cobalt, chromium, nickel, zinc, lead, and cadmium do not produce (·)OH under any of our experimental conditions. The antioxidant composition of our SLF significantly affects (·)OH production from Fe and Cu: ascorbate is required for (·)OH formation, citrate increases (·)OH production from Fe, and both citrate and glutathione suppress (·)OH production from Cu. MINTEQ ligand speciation modeling indicates that citrate and glutathione affect (·)OH production by changing metal speciation, altering the reactivity of the metals. In the most realistic SLF (i.e., with all four antioxidants), Fe generates approximately six times more (·)OH than does the equivalent amount of Cu. Since levels of soluble Fe in PM are typically higher than those of Cu, our results suggest that Fe dominates the chemical generation of (·)OH from deposited particles in the lungs.
 
Article
Particulate matter less than 2.5 microns in diameter (PM2.5) has been linked with a wide range of adverse health effects. Determination of the sources of PM2.5 most responsible for these health effects could lead to improved understanding of the mechanisms of such effects and more targeted regulation. This has provided the impetus for the Denver Aerosol Sources and Health (DASH) study, a multi-year source apportionment and health effects study relying on detailed inorganic and organic PM2.5 speciation measurements.
 
Article
Prescribed burning, in combination with mechanical thinning, is a successful method for reducing heavy fuel loads from forest floors and thereby lowering the risk of catastrophic wildfire. However, an undesirable consequence of managed fire is the production of fine particulate matter or PM(2.5) (particles ≤2.5 µm in aerodynamic diameter). Wood-smoke particulate data from 21 prescribed burns are described, including results from broadcast and slash-pile burns. All PM(2.5) samples were collected in situ on day 1 (ignition) or day 2. Samples were analyzed for mass, polycyclic aromatic hydrocarbons (PAHs), inorganic elements, organic carbon (OC), and elemental carbon (EC). Results were characteristic of low intensity, smoldering fires. PM(2.5) concentrations varied from 523 to 8357 µg m(-3) and were higher on day 1. PAH weight percents (19 PAHs) were higher in slash-pile burns (0.21 ± 0.08% OC) than broadcast burns (0.07 ± 0.03% OC). The major elements were K, Cl, S, and Si. OC and EC values averaged 66 ± 7 and 2.8 ± 1.4% PM(2.5), respectively, for all burns studied, in good agreement with literature values for smoldering fires.
 
Article
Coal consumption is one important contributor to energy production, and is regarded as one of the most important sources of air pollutants that have considerable impacts on human health and climate change. Emissions of polycyclic aromatic hydrocarbons (PAHs) from coal combustion were studied in a typical stove. Emission factors (EFs) of 16 EPA priority PAHs from tested coals ranged from 6.25 ± 1.16 mg kg(-1) (anthracite) to 253 ± 170 mg kg(-1) (bituminous), with NAP and PHE dominated in gaseous and particulate phases, respectively. Size distributions of particulate phase PAHs from tested coals showed that they were mostly associated with particulate matter (PM) with size either between 0.7 and 2.1 μm or less than 0.4 μm (PM0.4). In the latter category, not only were more PAHs present in PM0.4, but also contained higher fractions of high molecular weight PAHs. Generally, there were more than 89% of total particulate phase PAHs associated with PM2.5. Gas-particle partitioning of freshly emitted PAHs from residential coal combustions were thought to be mainly controlled by absorption rather than adsorption, which is similar to those from other sources. Besides, the influence of fuel properties and combustion conditions was further investigated by using stepwise regression analysis, which indicated that almost 57 ± 10% of total variations in PAH EFs can be accounted for by moisture and volatile matter content of coal in residential combustion.
 
Article
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.
 
Article
The lack of scientific evidence on the constituents, properties, and health effects of second-hand waterpipe smoke has fueled controversy over whether public smoking bans should include the waterpipe. The purpose of this study was to investigate and compare emissions of ultrafine particles (UFP, <100 nm), carcinogenic polyaromatic hydrocarbons (PAH), volatile aldehydes, and carbon monoxide (CO) for cigarettes and narghile (shisha, hookah) waterpipes. These smoke constituents are associated with a variety of cancers, and heart and pulmonary diseases, and span the volatility range found in tobacco smoke.Sidestream cigarette and waterpipe smoke was captured and aged in a 1 m(3) Teflon-coated chamber operating at 1.5 air changes per hour (ACH). The chamber was characterized for particle mass and number surface deposition rates. UFP and CO concentrations were measured online using a fast particle spectrometer (TSI 3090 Engine Exhaust Particle Sizer), and an indoor air quality monitor. Particulate PAH and gaseous volatile aldehydes were captured on glass fiber filters and DNPH-coated SPE cartridges, respectively, and analyzed off-line using GC-MS and HPLC-MS. PAH compounds quantified were the 5- and 6-ring compounds of the EPA priority list. Measured aldehydes consisted of formaldehyde, acetaldehyde, acrolein, methacrolein, and propionaldehyde.We found that a single waterpipe use session emits in the sidestream smoke approximately four times the carcinogenic PAH, four times the volatile aldehydes, and 30 times the CO of a single cigarette. Accounting for exhaled mainstream smoke, and given a habitual smoker smoking rate of 2 cigarettes per hour, during a typical one-hour waterpipe use session a waterpipe smoker likely generates ambient carcinogens and toxicants equivalent to 2-10 cigarette smokers, depending on the compound in question. There is therefore good reason to include waterpipe tobacco smoking in public smoking bans.
 
Article
To improve our understanding of indoor and outdoor personal exposures to common environmental toxicants released into the environment, new technologies that can monitor and quantify the toxicants anytime anywhere are needed. This paper presents a wearable sensor to provide such capabilities. The sensor can communicate with a common smart phone and provides accurate measurement of volatile organic compound concentration at a personal level in real time, providing environmental toxicants data every three minutes. The sensor has high specificity and sensitivity to aromatic, alkyl, and chlorinated hydrocarbons with a resolution as low as 4 parts per billion (ppb), with a detection range of 4 ppb to 1000 ppm (parts per million). The sensor's performance was validated using Gas Chromatography and Selected Ion Flow Tube - Mass Spectrometry reference methods in a variety of environments and activities with overall accuracy higher than 81% (r(2) > 0.9). Field tests examined personal exposure in various scenarios including: indoor and outdoor environments, traffic exposure in different cities which vary from 0 to 50 ppmC (part-per-million carbon from hydrocarbons), and pollutants near the 2010 Deepwater Horizon's oil spill. These field tests not only validated the performance but also demonstrated unprecedented high temporal and spatial toxicant information provided by the new technology.
 
Article
The 1,6 and 1,8-dinitropyrenes (DNP) isomers are strong mutagens and carcinogens encountered in diesel exhaust and airborne particles. Relative photodegradation rates were determined and some products were characterized when these isomers were irradiated adsorbed onto models of the atmospheric matter. These are compared to their photochemical behavior in a polar nonprotic solvent. The 1,8-DNP isomer is three times more reactive than the 1,6-DNP when irradiated adsorbed onto silica gel surfaces, while the reverse order is observed in solution, demonstrating the influence of structural differences and environmental effects on the photoreactivity. Oxygen is a key factor in the formation of pyrenediones from 1,8-DNP in solution and on silica gel which is not the case for 1,6-DNP. The average pore diameter (2.5 versus 6.0 nm) of the silica surfaces induces a significant change in the product distribution and relative yields of 1,8-DNP because pyrenediones or 8-hydroxy-1-nitropyrene are not produced in the smaller pore silica. A 6-hydroxy-1-nitropyrene product is observed both in acidic alumina and silica (6.0 nm) surfaces. On acidic alumina the rates of phototransformation of the isomers are equal, a significant increase in the relative yield of the hydroxynitropyrene product is observed compared to the silica and unidentified products in which the absence of NO2 and pyrene absorption bands were observed, demonstrating the surface effect on the photodegradation. Overall, the presence of some products indicates the occurrence of a nitro-nitrite rearrangement on the surface with the participation of a pyrenoxy radical as their precursor.
 
Article
Using the data on all live births (~400,000) and criteria pollutants from the Chicago Metropolitan Statistical Area (MSA) between 2000 and 2004, this paper empirically demonstrates how mismatches in the spatiotemporal scales of health and air pollution data can result in inconsistency and uncertainty in the linkages between air pollution and birth outcomes. This paper suggests that the risks of low birth weight associated with air pollution exposure changes significantly as the distance interval (around the monitoring stations) used for exposure estimation changes. For example, when the analysis was restricted within 3 miles distance of the monitoring stations the odds of LBW (births < 2500g) increased by a factor of 1.045 (±0.0285 95% CI) with a unit increase in the average daily exposure to PM(10) (in μg/m(3)) during the gestation period; the value dropped to 1.028 when the analysis was restricted within 6 miles distance of air pollution monitoring stations. The effect of PM(10) exposure on LBW became null when controlled for confounders. But PM(2.5) exposure showed a significant association with low birth weight when controlled for confounders. These results must be interpreted with caution, because the distance to monitoring station does not influence the risks of adverse birth outcomes, but uncertainty in exposure increases with the increase in distance from the monitoring stations, especially for coarse particles such as PM(10) that settle with gravity within short distance and time interval. The results of this paper have important implications for the research design of environmental epidemiological studies, and the way air pollution (and potentially other environmental) and health data are collocated to compute exposure. The paper also calls for time-space resolved estimate of air pollution to minimize uncertainty in exposure estimation.
 
Article
Emission from field burning of crop residue, a common practice in many parts of the world today, has potential effects on air quality, atmosphere and climate. This study provides a comprehensive size and compositional characterization of particulate matter (PM) emission from rice straw (RS) burning using both in situ experiments (11 spread field burning) and laboratory hood experiments (3 pile and 6 spread burning) that were conducted during 2003-2006 in Thailand. The carbon balance and emission ratio method was used to determine PM emission factors (EF) in the field experiments. The obtained EFs varied from field to hood experiments reflecting multiple factors affecting combustion and emission. In the hood experiments, EFs were found to be depending on the burning types (spread or pile), moisture content and the combustion efficiency. In addition, in the field experiments, burning rate and EF were also influenced by weather conditions, i.e. wind. Hood pile burning produced significantly higher EF (20±8 g kg(-1) RS) than hood spread burning (4.7±2.2 g kg(-1) RS). The majority of PM emitted from the field burning was PM(2.5) with EF of 5.1±0.7 g m(-2) or 8.3±2.7 g kg(-1) RS burned. The coarse PM fraction (PM(10-2.5)) was mainly generated by fire attention activities and was relatively small, hence the resulting EF of PM(10) (9.4±3.5 g kg(-1) RS) was not significantly higher than PM(2.5). PM size distribution was measured across 8 size ranges (from <0.4 μm to >9.0 μm). The largest fractions of PM, EC and OC were associated with PM(1.1). The most significant components in PM(2.5) and PM(10) include OC, water soluble ions and levoglucosan. Relative abundance of some methoxyphenols (e.g., acetylsyringone), PAHs (e.g., fluoranthene and pyrene), organochlorine pesticides and PCBs may also serve as additional signatures for the PM emission. Presence of these toxic compounds in PM of burning smoke increases the potential toxic effects of the emission. For illustration, an estimation of the annual RS field burning in Thailand was made using the obtained in situ field burning EFs and preliminary burning activity data.
 
Article
We monitored two Seattle school buses to quantify the buses' self pollution using the dual tracers (DT), lead vehicle (LV), and chemical mass balance (CMB) methods. Each bus drove along a residential route simulating stops, with windows closed or open. Particulate matter (PM) and its constituents were monitored in the bus and from a LV. We collected source samples from the tailpipe and crankcase emissions using an on-board dilution tunnel. Concentrations of PM(1), ultrafine particle counts, elemental and organic carbon (EC/OC) were higher on the bus than the LV. The DT method estimated that the tailpipe and the crankcase emissions contributed 1.1 and 6.8 mug/m(3) of PM(2.5) inside the bus, respectively, with significantly higher crankcase self pollution (SP) when windows were closed. Approximately two-thirds of in-cabin PM(2.5) originated from background sources. Using the LV approach, SP estimates from the EC and the active personal DataRAM (pDR) measurements correlated well with the DT estimates for tailpipe and crankcase emissions, respectively, although both measurements need further calibration for accurate quantification. CMB results overestimated SP from the DT method but confirmed crankcase emissions as the major SP source. We confirmed buses' SP using three independent methods and quantified crankcase emissions as the dominant contributor.
 
Article
Nearly half of the world's population is exposed to household air pollution (HAP) due to long hours spent in close proximity to unvented cooking fires. We aimed to use PM2.5 and CO measurements to characterize exposure to cookstove generated woodsmoke in real time among control (n=10) and intervention (n=9) households in San Marcos, Cajamarca Region, Peru. Real time personal particulate matter with an aerodynamic diameter ≤2.5 µm (PM2.5), and personal and kitchen carbon monoxide (CO) samples were taken. Control households used a number of stoves including open fire and chimney stoves while intervention households used study-promoted chimney stoves. Measurements were categorized into lunch (9am - 1pm) and dinner (3pm - 7pm) periods, where applicable, to adjust for a wide range of sampling periods (2.8- 13.1hrs). During the 4-h time periods, mean personal PM2.5 exposures were correlated with personal CO exposures during lunch (r=0.67 p=0.024 n=11) and dinner (r=0.72 p=0.0011 n=17) in all study households. Personal PM2.5 exposures and kitchen CO concentrations were also correlated during lunch (r=0.76 p=0.018 n=9) and dinner (r=0.60 p=0.018 n=15). CO may be a useful indicator of PM during 4-h time scales measured in real time, particularly during high woodsmoke exposures, particularly during residential biomass cooking.
 
Article
Previous studies have identified associations between traffic-related air pollution and adverse health effects. Most have used measurements from a few central ambient monitors and/or some measure of traffic as indicators of exposure, disregarding spatial variability and factors influencing personal exposure-ambient concentration relationships. This study seeks to utilize publicly available data (i.e., central site monitors, geographic information system, and property assessment data) and questionnaire responses to predict residential indoor concentrations of traffic-related air pollutants for lower socioeconomic status (SES) urban households.
 
Article
Particulate matter less than 2.5 microns in diameter (PM(2.5)) has been shown to have a wide range of adverse health effects and consequently is regulated in accordance with the US-EPA's National Ambient Air Quality Standards. PM(2.5) originates from multiple primary sources and is also formed through secondary processes in the atmosphere. It is plausible that some sources form PM(2.5) that is more toxic than PM(2.5) from other sources. Identifying the responsible sources could provide insight into the biological mechanisms causing the observed health effects and provide a more efficient approach to regulation. This is the goal of the Denver Aerosol Sources and Health (DASH) study, a multi-year PM(2.5) source apportionment and health study.The first step in apportioning the PM(2.5) to different sources is to determine the chemical make-up of the PM(2.5). This paper presents the methodology used during the DASH study for organic speciation of PM(2.5). Specifically, methods are covered for solvent extraction of non-polar and semi-polar organic molecular markers using gas chromatography-mass spectrometry (GC-MS). Vast reductions in detection limits were obtained through the use of a programmable temperature vaporization (PTV) inlet along with other method improvements. Results are presented for the first 1.5 years of the DASH study revealing seasonal and source-related patterns in the molecular markers and their long-term correlation structure. Preliminary analysis suggests that point sources are not a significant contributor to the organic molecular markers measured at our receptor site. Several motor vehicle emission markers help identify a gasoline/diesel split in the ambient data. Findings show both similarities and differences when compared with other cities where similar measurements and assessments have been made.
 
Time series measurements tire-fire related species: a) OC, EC (left axis) and OC:EC (right axis) at IA-AMS, b) PM 2.5 measured by mobile and stationary monitors, and close up view May 30-June 5 measurements of c) PM 2.5 ,d)SO 2 and CO 2 , and e) particle number and wind direction. The landfill is located at a bearing of 24 relative to the BDR site and at a bearing of 240 relative to the IA-AMS site.  
Time series measurements of PAH and B[a]P during background (MayeJune 2011) and the tire fire period in 2012.  
Distribution of PAH observed in a) PM 2.5 impacted by the tire fire plume in Iowa City, b) soot following a tire fire in Quebec, Canada, and c) gas and particles in a laboratory study.
Molecular structures of azaarenes and oxy-PAH detected in the tire fire plume.  
Time series of ambient PM 10 metals concentrations (bars, left axis) and mass fraction (squares, right axis) at IA-AMS.  
Article
In summer 2012, a landfill liner comprising an estimated 1.3 million shredded tires burned in Iowa City, Iowa. During the fire, continuous monitoring and laboratory measurements were used to characterize the gaseous and particulate emissions and to provide new insights into the qualitative nature of the smoke and the quantity of pollutants emitted. Significant enrichments in ambient concentrations of CO, CO2, SO2, particle number (PN), fine particulate (PM2.5) mass, elemental carbon (EC), and polycyclic aromatic hydrocarbons (PAH) were observed. For the first time, PM2.5 from tire combustion was shown to contain PAH with nitrogen heteroatoms (a.k.a. azaarenes) and picene, a compound previously suggested to be unique to coal-burning. Despite prior laboratory studies' findings, metals used in manufacturing tires (i.e. Zn, Pb, Fe) were not detected in coarse particulate matter (PM10) at a distance of 4.2 km downwind. Ambient measurements were used to derive the first in situ fuel-based emission factors (EF) for the uncontrolled open burning of tires, revealing substantial emissions of SO2 (7.1 g kg(-1)), particle number (3.5×10(16) kg(-1)), PM2.5 (5.3 g kg(-1)), EC (2.37 g kg(-1)), and 19 individual PAH (totaling 56 mg kg(-1)). A large degree of variability was observed in day-to-day EF, reflecting a range of flaming and smoldering conditions of the large-scale fire, for which the modified combustion efficiency ranged from 0.85-0.98. Recommendations for future research on this under-characterized source are also provided.
 
Article
Chronic epidemiological studies of airborne particulate matter (PM) have typically characterized the chronic PM exposures of their study populations using city- or countywide ambient concentrations, which limit the studies to areas where nearby monitoring data are available and which ignore within-city spatial gradients in ambient PM concentrations. To provide more spatially refined and precise chronic exposure measures, we used a Geographic Information System (GIS)-based spatial smoothing model to predict monthly outdoor PM(10) concentrations in the northeastern and midwestern United States. This model included monthly smooth spatial terms and smooth regression terms of GIS-derived and meteorological predictors. Using cross-validation and other pre-specified selection criteria, terms for distance to road by road class, urban land use, block group and county population density, point- and area-source PM(10) emissions, elevation, wind speed, and precipitation were found to be important determinants of PM(10) concentrations and were included in the final model. Final model performance was strong (cross-validation R(2)=0.62), with little bias (-0.4 mug m(-3)) and high precision (6.4 mug m(-3)). The final model (with monthly spatial terms) performed better than a model with seasonal spatial terms (cross-validation R(2)=0.54). The addition of GIS-derived and meteorological predictors improved predictive performance over spatial smoothing (cross-validation R(2)=0.51) or inverse distance weighted interpolation (cross-validation R(2)=0.29) methods alone and increased the spatial resolution of predictions. The model performed well in both rural and urban areas, across seasons, and across the entire time period. The strong model performance demonstrates its suitability as a means to estimate individual-specific chronic PM(10) exposures for large populations.
 
Top-cited authors
Roy M Harrison
  • University of Birmingham
Xavier Querol
  • Spanish National Research Council, in Barcelona, Spain
Andres Alastuey
  • Spanish National Research Council
John G Watson
  • Desert Research Institute
Philip K Hopke
  • Clarkson University