Grantee Research Project Results
Final Report: Multi-Scale Assessment of Health Effects of Air Pollution Mixtures Using Novel Measurements and Models
EPA Grant Number: R834799Center: The Southeastern Center for Air Pollution and Epidemiology: Multiscale Measurements and Modeling of Mixtures
Center Director: Tolbert, Paige
Title: Multi-Scale Assessment of Health Effects of Air Pollution Mixtures Using Novel Measurements and Models
Investigators: Tolbert, Paige , Sarnat, Stefanie Ebelt , Strickland, Matthew J , Weber, Rodney J. , Odman, Mehmet Talat , Winquist, Andrea , Russell, Armistead G. , Nenes, Athanasios , Flanders, Dana , Diaz-Sanchez, David , Talbott, Evelynn , Chang, Howard , Mulholland, James , Sarnat, Jeremy , Waller, Lance , Darrow, Lyndsey , Bergin, Michael , Klein, Mitchel , Guensler, Randy , Bilonick, Richard , Greenwald, Roby , Barry, Vaughn , Liu, Yang , Hu, Yongtao
Institution: Emory University , Georgia Institute of Technology , Duke University
Current Institution: Emory University , Duke University , Georgia Institute of Technology
EPA Project Officer: Chung, Serena
Project Period: January 1, 2011 through December 31, 2016
Project Amount: $7,999,779
RFA: Clean Air Research Centers (2009) RFA Text | Recipients Lists
Research Category: Climate Change , Air Quality and Air Toxics , Air
Objective:
A multi-institutional, multi-disciplinary Center was established to address critical issues relating to the public health impacts of ambient air pollution. The overarching theme of the Center was a focus on characterizing ambient air pollution mixtures and elucidating their role in human health risks associated with air pollution. Novel measurements and modeling approaches were applied in the context of a tiered multi-scale assessment of the health risks of mixtures characterized based on: 1) biological considerations (oxidants); 2) environmental management (sources); 3) evidence-based considerations (traffic emissions); 4) empirical assessment (data-based approach). Four Research Projects were supported by an Air Quality Core (Core B) and a Biostatistics Core (Core C). The goal of Project 1 was to develop and deploy instrumentation to measure oxidants (including aerosol reactive oxygen species) and other species of interest to better understand their origins and atmospheric transformation and for use in characterizing mixtures for the three health studies. The goal of Project 2 was to make direct use of these measurements and other measurements to confirm associations with markers of oxidative stress in commuters. Projects 3 and 4 used a combination of measurements and modeled air quality estimates in large population studies, with Project 3 investigating questions regarding risks of in utero and early life exposures to air pollutant mixtures in two major new birth cohorts and Project 4 assessing underlying consistencies in morbidity associations across selected cities that had comprehensive daily air pollution characterization. The health projects included assessment of potentially sensitive and vulnerable subpopulations. The Center brought together a productive group of researchers with depth in the relevant disciplines and access to rich air quality and health outcome databases to conduct an integrated and innovative research program to address key gaps in our understanding of air pollution impacts.
Summary/Accomplishments (Outputs/Outcomes):
Center Accomplishments/Outcomes:
Specific findings of each of the projects and accomplishments of the cores are presented separately in the attached Final Project Summaries and Final Core Summaries. Here, we highlight some of the major accomplishments and outcomes.
Project 1:
In Project 1, an instrumentation package was constructed for quantifying trace gas and aerosol species to more fully characterize the various atmospheric mixtures to which individuals are exposed. Measurements were undertaken across a variety of scales and locations to characterize source emissions, their transformation products, and the resultant air pollution mixtures. The resulting dataset, along with other data sources, was used in the detailed air quality analysis and modeling activities (Air Quality Core) that support the three health studies (Projects 2-4). In addition, results of this project provided a better understanding of the source, transformation and fate of pollutants to which populations are exposed. Selected trace gases and the physical and chemical properties of particulate air pollutants were studied using a wide range of existing methods along with new measurement approaches for quantifying aerosol Reactive Oxygen Species (ROS) and aerosol oxidative potential (OP). The suite of instruments was selected to complement and build on a long-term air quality data set collected in Atlanta that has been used extensively in prior epidemiologic studies by the project PIs, and extend measurements taken across areas covered in Projects 2-4. Two instrument packages were assembled along with a group of more advanced methods to chemically speciate pollutants. These sets of instruments were deployed at fixed sites for approximately one-month sampling periods during different seasons and years to allow comparisons between pairs of sites. Sampling locations for this study included a road-side site, a near-road site, a central site representative of the Atlanta urban environment, a rural site representative of the regional environment, and two other urban settings for contrast with Atlanta (Birmingham, AL, and St. Louis, MO). The overall objective was to generate a novel data set that included ROS and OP to quantify gas and aerosol species that may be linked to adverse health outcomes.
To achieve Project 1 goals, four new instruments or automated analytical systems were developed. Through multi-site field studies conducted over a period of nominally 1.5 years, a large data set on OP, quantified with the dithiothreitol (DTT) and ascorbic acid (AA) assays, and detailed aerosol chemical speciation was generated and is publically available. The analysis of these data resulted in a highly comprehensive and consistent assessment of the sources and atmospheric processes contributing to OP in the southeastern US. This includes a new understanding of the particle size resolved characteristics of AA and DTT. SCAPE Project 1 research has substantially extended what had previously been known about aerosol oxidative potential and links to health effects. A key finding was that atmospheric processing involving oxidation of organics (e.g., PAHs to quinones) and transition metals by acid-dissociation greatly increased the oxidative potential of PM2.5. This is true for both water-soluble and insoluble species, such as DTT-active soot particles that become more toxic with age. Large population time series epidemiological studies conducted as part of this Center showed significant associations between water-soluble DTT OP and various cardiorespiratory health endpoints. Notable consistent associations were found with adverse respiratory effects, including asthma exacerbation. In bipollutant models stronger associations for DTT OP compared to PM2.5 mass provided evidence that oxidative potential may be an important and valuable integrative measure of PM2.5 toxicity and should be considered as a key parameter to include in future air pollution studies and network measurement programs. This is especially true as the chemical composition of PM2.5 mass evolves due to changing emissions.
Project 2:
- primary aim of Atlanta Commuters Exposure Study Project 2 (Atlanta Commuters Exposure Study ACE-2) was to examine the effects of exposure to particulate mixtures occurring during automobile commuting and within indoor, non-commuting microenvironments and corresponding measures of oxidative stress-mediated response. Broadly, ACE-2 was designed as a randomized, crossover panel study of 60 young adults (age range: 18-39) with or without asthma in Atlanta, GA, conducted throughout a 1.5-year period. study included three different exposure scenarios: a 2-hr highway commute, a 2-hr surface street commute and a 2-hr clinic session. Each adult participated in two exposure sessions, exactly seven days apart, performing in random order, a highway commute and either a surface street commute or a clinic session. All exposure sessions included the same pre- and post-exposure biomarker measurements. The key difference in participant protocol between the two study days was whether a highway commute, a surface street commute, or a clinic session was scheduled. The commutes and clinic sessions were conducted during weekday mornings, at peak rush hour periods (7 AM – 9 AM).
Major findings were the following:
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Measurements conducted in both of the in-vehicle protocols indicated elevated pollutant levels relative to our indoor clinic, as well as other near-road measurement studies, pointing to the uniqueness of the car commuter microenvironment in terms of its potential to contribute to daily exposures to traffic pollutants.
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Moreover, results provided indication, albeit mixed in some cases, of response by on-road exposure scenario, particularly with regard to acute decrements in lung function and elevated systemic inflammation associated with elemental carbon, organic carbon, and especially copper. Indeed, copper was the only pollutant we measured that was significantly associated with increased exhaled nitric oxide (eNO), lung function decrement, and increased levels of several cytokines.
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Exposures to copper, itself, may be driving the observed health responses; however, we view it equally likely that this pollutant may be signaling exposure to a source or traffic pollutant mixture, namely road dust or brake wear. These findings are consistent with the source apportioned analyses pointing to the effects non-tailpipe sources, namely brake/tire wear and resuspended road dust, on specific endpoints examined.
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While all the observed associations were generally small and transient, returning to pre-exposure levels within several hours in most cases, we view these findings as adding to the growing body of evidence from panel-based air pollution studies showing acute cardiorespiratory response following short-term exposures to traffic pollutant components.
Project 3:
In utero and early life experiences affect physiological development and can influence sensitivity to environmental factors throughout life. In this Project, we explored the interplay between certain early life events, characterizations of air pollutant mixtures developed as part of the Center’s Mixtures Characterization Toolkit, and a range of pediatric health outcomes using two large, population-based birth cohorts. One cohort consisted of roughly 1.7 million Georgia birth records that had been geocoded to the Census block level and linked with pediatric emergency department visits by staff at the Georgia Department of Human Resources. Using this statewide birth cohort, we investigated acute effects of air pollution mixtures on respiratory health outcomes and ear infections in children, and we assessed whether children who were born premature or low birth weight were more sensitive to ambient air pollutant concentrations than their counterparts. Further, we used the statewide birth cohort to investigate whether ambient air pollutant mixtures during pregnancy were associated with the risk of preterm delivery or reduced birth weight. The second birth cohort was comprised of children who were members of the Kaiser Permanente Georgia Health Maintenance Organization in metropolitan Atlanta. In this birth cohort, where comprehensive medical and residential histories were available for each child, we examined whether air pollutant mixtures during the first year of life were associated with the incidence of childhood asthma.
Project 3 analyses of short-term changes in pollutant concentrations in relation to pediatric respiratory events support the conclusion that several different pollutants are associated with these diseases. Various approaches to characterize pollutant mixtures, including joint effects modeling, classification and regression trees, source apportionment, and self-organizing maps, were implemented to investigate the health effects of pollutant mixtures. Broadly, we did not observe consistent evidence for positive synergism among pollutants across our studies. More evidence was found to support effect modification of pollutant associations by susceptibility factors such as preterm birth, maternal race, and maternal education. Future work will help to inform the validity of these potentially important susceptibility factors. Our analyses of early life traffic exposures and incident asthma in a racially diverse population provide evidence to further support previous literature on this association. Through this work we have developed an innovative modeling approach to fuse chemical transport model results with dispersion model estimates to better estimate near-roadway impacts, and we found that exposure misclassification due to maternal mobility during pregnancy is not likely to cause a large bias in the effect estimates.
Project 4:
Although associations between ambient air pollution and acute cardiorespiratory outcomes have been observed in numerous studies, questions remain about the degree to which these findings are generalizable between locations and whether the observed health effects are due to the individual pollutants measured or to pollutants acting in combination with other pollutants. In Project 4, we conducted a multi-city time-series study to clarify the impacts of air quality on acute cardiorespiratory morbidity in five US cities (Atlanta, GA; Birmingham, AL; Dallas, TX; Pittsburgh, PA; St. Louis, IL-MO) using novel mixture characterization metrics. Analyses included consideration of factors related to air pollution mixtures, exposure measurement error, concentration-response functions, population susceptibility and vulnerability, and seasonality and climate to help explain heterogeneity in short-term associations between air quality measures and cardiorespiratory emergency department (ED) visits.
In Project 4 analyses, associations of major ambient pollutants and specific air pollution mixtures and cardiorespiratory ED visits were observed across several US cities. Specifically, mixtures related to ozone, secondary organic aerosols, biomass burning, and traffic combustion-related pollution appeared to have impacts on respiratory morbidity; and primary traffic-related pollution mixtures (both tailpipe, combustion-related components as well as tire wear/brake pad related components) were found to be important for cardiovascular morbidity. High ambient temperatures, expressed either as continuous warm-season temperatures or heat waves, were found to have strong impacts on acute morbidity, particularly dehydration and kidney-related outcomes, but also cardiorespiratory morbidity. Heat as an ambient exposure may be important to consider in the broad context of assessing health impacts of atmospheric mixtures. Finally, we found sociodemographic factors (age and socio-economic status) to be important modifiers of air pollution and temperature-related health associations. New work extending this research in additional cities with sufficiently resolved air quality data will contribute to better characterizing the generalizability of these findings.
Air Quality Core (Core B):
The Air Quality Core provided SCAPE researchers with the methods and data to comprehensively characterize air pollutants relevant to the four projects and other cores. Project activities were supported by collecting and managing atmospheric data, developing a “Mixture Characterization Toolkit” for further analyses specific to the projects, and providing the expertise and resources to facilitate the application of the various components of the toolkit. Comprehensive characterization of air pollutants was developed by analyses of the detailed chemical and physical measurements conducted by the Center, along with those available from ambient air quality monitoring networks and special field campaigns. Spatial and temporal characterization of the air pollutant mixtures and emission sources were determined by using extended receptor-oriented models, chemical transport models, regression approaches, hybrid methods, and remote sensing applied over multiple scales. Documentation for the novel models developed for the Center is provided in the “Model Documentation” section of the report.
Biostatistics Core (Core C):
The Biostatistics Core provided data management and quantitative analytic support to all SCAPE Projects and Cores. Core members contributed to the development of novel quantitative methods to address analytic challenges in SCAPE projects including (but not limited to) assessment of statistical performance of multivariate classification algorithms (e.g., self-organizing maps) to explore health effects of pollutant mixtures, expanded statistical assessments of source apportionment, identification and evaluation of potential confounding effects, adjustments for effect modification, and detailed assessment of pediatric health impacts of air pollution. In addition to continuation and expansion of these activities, the Biostatistics Core also explored, assessed, and applied statistical prediction methods for “backcasting” predictions of oxidative potential indices of air quality. Core activities addressed fundamental data analytic challenges arising in the analysis of the health effects of air pollution exposure and illustrates the central role of strong biostatistical and methodological collaboration in large team science efforts to quantify, evaluate, understand, and communicate health risks associated with exposure to air pollution.
Conclusions:
Benefit to the Environment and Human Health:
The Southeastern Center for Air Pollution and Epidemiology (SCAPE) contributed important insights into our understanding of the impact of complex ambient air pollution mixtures on human health. The interdisciplinary team developed innovative methods to measure and model air pollutant mixtures and applied these in studies of health impacts. Ultimately, the insights gained from this work will be critical to optimizing air quality management strategies to protect public health.
Urban air pollution is comprised of a variety of pollutants with varying toxicity. One well-studied component known to have major health effects is fine particulate matter (PM2.5), itself a mixture of species. A key measurement method developed by the SCAPE Center is an automated system for measuring oxidative potential, hypothesized to be an important toxic property of PM2.5. This measurement method provides an integrated index of the species that have high oxidative potential and thus may lead to oxidative stress when inhaled. In addition to this innovative measurement, SCAPE also made advances in air quality modeling methods, including a method to fuse monitor data with emissions-based models to improve spatiotemporal estimation of air quality and a method for optimizing source apportionment to provide insight into which pollution sources are most toxic.
In SCAPE health studies using measurements or modeled estimates of oxidative potential, the oxidative potential indicator was found to be strongly associated with asthma exacerbation and several cardiac problems. These associations persisted even when other correlated pollutants were accounted for in the epidemiologic models. Thus, this is a promising integrative measure of toxicity of air pollution and the automated method can now be used in large-scale epidemiologic studies and, after confirmation of our initial findings, may eventually warrant implementation in routine monitoring. In health studies using the other methods of measuring or modeling air pollutant mixtures, respiratory conditions were associated with mixtures containing ozone, secondary organic carbon, biomass burning and traffic combustion, while cardiac conditions were related to primary traffic emissions (both combustion and emissions from tire/brake wear.) Elemental and organic carbon and certain metals were found to be related to acute lung function decrements and elevated systemic inflammation. Fine particles from traffic were found to be associated with development of pediatric asthma, in addition to asthma exacerbation, and preterm birth was associated with fine particles and several gaseous pollutants. Finally, SCAPE investigators reported stronger respiratory and cardiac air pollution effects in children and the elderly, those with low socio-economic status, and African-American populations, and those born pre-term, providing important evidence regarding vulnerable or susceptible populations.
Future Activities:
Project 1
- Continue to analyze data, complete manuscripts currently in progress, and present results at meetings.
- Develop and verify method for measurement of total DTT on filter samples.
- Refine and re-test method for online DTT measurements.
Project 2
- Complete and submit draft manuscripts currently in preparation.
Project 3
- Finalize and publish the air quality models and epidemiologic results for the Kaiser Permanente cohort.
- Finalize and publish the Georgia-wide birth weight quantile regression paper.
Project 4
- Ensure currently submitted manuscripts are published.
- Submit 3-5 manuscripts currently in preparation and planned.
- Continue several analyses focused on assessment of mixtures and effect modification in the single- and multi-city context.
Core B
- Complete application of the CMAQ-CMB hybrid method to the entire 10 year period (2002-2012) to provide source-specific impact fields for the CONUS.
- Continue exploring the use of the CMAQ-CMB hybrid method for ozone source apportionment.
- Use the CMAQ-Hybrid results and the ROS observations, both using the DTT and AA assays from Project 1, to develop source specific ROS impacts. The resulting associations would then be useful to develop long term, national trends in ROS for use in an acute health association analysis.
- Finish the application of the OBS-CMAQ fusion approach to the NC area as part of the Harvard-GIT-EPA collaboration. Apply to PM2.5 total mass, five major particulate species (OC, EC, SO42-, NO3-, and NH4+), and three gaseous pollutants (CO, NOx, NO2). Use the EC, CO and NO2 results to estimate mobile source impacts using the IMSI approach. Conduct more thorough evaluation of the method and further comparison to the satellite-based approaches.
- Provide further support to Project 3 in terms of using CMAQ, satellite observations and RLINE to develop fine scale fields.
- Provide further support to Project 4 to estimate source impacts at the five SCAPE cities.
- Provide further support to Project 1 to analyze their observational results.
- Continue working with CCAR on the collaborative. We will apply RLINE at a fine scale to provide more detailed multipollutant data for comparison to their observations and to CMAQ.
Core C
- Continue collaborations with investigators across SCAPE as the next generation of research projects builds on SCAPE success.
- Submit multiple publications building on SCAPE success that are currently in development.
- Continue current collaborations relating to environmental epidemiology and methodological research that form the basis of related projects, proposed next steps currently under review, and multiple projects in the formative proposal stage.
Collaborative Project 2
Data from 28 passive badges deployed during the intensive sampling will be evaluated to assess pollutant gradients and compare to RLINE estimated near-road gradients. The passive badge data were continuously collected from September 5, 2013, 11 am local time to September 18, 2013, 9 pm. The two-week measurements passive badge data will be used to help evaluate RLINE estimates.
Journal Articles: 136 Displayed | Download in RIS Format
Other center views: | All 338 publications | 139 publications in selected types | All 135 journal articles |
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Abrams JY, Weber RJ, Klein M, Samat SE, Chang HH, Strickland MJ, Verma V, Fang T, Bates JT, Mulholland JA, Russell AG, Tolbert PE. Associations between ambient fine particulate oxidative potential and cardiorespiratory emergency department visits. Environmental Health Perspectives 2017;125(10):107008. |
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Alhanti BA, Chang HH, Winquist A, Mulholland JA, Darrow LA, Sarnat SE. Ambient air pollution and emergency department visits for asthma: a multi-city assessment of effect modification by age. Journal of Exposure Science & Environmental Epidemiology 2016;26(2):180-188. |
R834799 (2015) R834799 (2016) R834799 (Final) R834799C004 (2015) R834799C004 (Final) R829213 (Final) |
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Balachandran S, Pachon JE, Hu Y, Lee D, Mulholland JA, Russell AG. Ensemble-trained source apportionment of fine particulate matter and method uncertainty analysis. Atmospheric Environment 2012;61:387-394. |
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Balachandran S, Chang HH, Pachon JE, Holmes HA, Mulholland JA, Russell AG. Bayesian-based ensemble source apportionment of PM2.5. Environmental Science & Technology 2013;47(23):13511-13518. |
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Balachandran S, Pachon JE, Lee S, Oakes MM, Rastogi N, Shi W, Tagaris E, Yan B, Davis A, Zhang X, Weber RJ, Mulholland JA, Bergin MH, Zheng M, Russell AG. Particulate and gas sampling of prescribed fires in South Georgia, USA. Atmospheric Environment 2013;81:125-135. |
R834799 (2015) R834799 (2016) R834799 (Final) R833866 (Final) |
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Bates JT, Weber RJ, Abrams J, Verma V, Fang T, Klein M, Strickland MJ, Sarnat SE, Chang HH, Mulholland JA, Tolbert PE, Russell AG. Reactive oxygen species generation linked to sources of atmospheric particulate matter and cardiorespiratory effects. Environmental Science & Technology 2015;49(22):13605-13612. |
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Baxter LK, Dionisio KL, Burke J, Sarnat SE, Sarnat JA, Hodas N, Rich DQ, Turpin BJ, Jones RR, Mannshardt E, Kumar N, Beevers SD, Ozkaynak H. Exposure prediction approaches used in air pollution epidemiology studies: key findings and future recommendations. Journal of Exposure Science & Environmental Epidemiology 2013;23(6):654-659. |
R834799 (2014) R834799 (2015) R834799 (2016) R834799 (Final) R834799C004 (2013) R834799C004 (2014) R834799C004 (2015) R834799C004 (Final) R833865 (Final) |
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Bergin MH, Tripathi SN, Jai Devi J, Gupta T, Mckenzie M, Rana KS, Shafer MM, Villalobos AM, Schauer JJ. The discoloration of the Taj Mahal due to particulate carbon and dust deposition. Environmental Science & Technology 2015;49(2):808-812. |
R834799 (2015) R834799 (2016) R834799 (Final) R834799C002 (2015) R834799C002 (Final) R835039 (Final) |
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Boyd CM, Sanchez J, Xu L, Eugene AJ, Nah T, Tuet WY, Guzman MI, Ng NL. Secondary organic aerosol formation from the β-pinene+NO3 system: effect of humidity and peroxy radical fate. Atmospheric Chemistry and Physics 2015;15(13):7497-7522. |
R834799 (Final) R835403 (2014) R835403 (2015) R835403 (Final) |
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Brock CA, Wagner NL, Anderson BE, Attwood AR, Beyersdorf A, Campuzano-Jost P, Carlton AG, Day DA, Diskin GS, Gordon TD, Jimenez JL, Lack DA, Liao J, Markovic MZ, Middlebrook AM, Ng NL, Perring AE, Richardson MS, Schwarz JP, Washenfelder RA, Welti A, Xu L, Ziemba LD, Murphy DM. Aerosol optical properties in the southeastern United States in summer--Part 1: Hygroscopic growth. Atmospheric Chemistry and Physics 2016;16(8):4987-5007. |
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Brown MS, Sarnat SE, DeMuth KA, Brown LAS, Whitlock DR, Brown SW, Tolbert PE, Fitzpatrick AM. Residential proximity to a major roadway is associated with features of asthma control in children. PLoS ONE 2012;7(5):e37044 ( pp.). |
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Budisulistiorini SH, Canagaratna MR, Croteau PL, Baumann K, Edgerton ES, Kollman MS, Ng NL, Verma V, Shaw SL, Knipping EM, Worsnop DR, Jayne JT, Weber RJ, Surratt JD. Intercomparison of an Aerosol Chemical Speciation Monitor (ACSM) with ambient fine aerosol measurements in downtown Atlanta, Georgia. Atmospheric Measurement Techniques 2014;7(7):1929-1941. |
R834799 (2015) R834799 (2016) R834799 (Final) R834799C001 (2015) R834799C001 (Final) |
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Chang HH, Reich BJ, Miranda ML. A spatial time-to-event approach for estimating associations between air pollution and preterm birth. Journal of the Royal Statistical Society--Series C (Applied Statistics) 2013;62(2):167-179. |
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Chang HH, Hu X, Liu Y. Calibrating MODIS aerosol optical depth for predicting daily PM2.5 concentrations via statistical downscaling. Journal of Exposure Science & Environmental Epidemiology 2014;24(4):398-404. |
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Chang HH, Hao H, Sarnat SE. A statistical modeling framework for projecting future ambient ozone and its health impact due to climate change. Atmospheric Environment 2014;89:290-297. |
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Chang HH, Warren JL, Darrow LA, Reich BJ, Waller LA. Assessment of critical exposure and outcome windows in time-to-event analysis with application to air pollution and preterm birth study. Biostatistics 2015;16(3):509-521. |
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Chen T, Sarnat SE, Grundstein AJ, Winquist A, Chang HH. Time-series analysis of heat waves and emergency department visits in Atlanta, 1993 to 2012. Environmental Health Perspectives 2017;125(5):057009 (9 pp.). |
R834799 (2016) R834799 (Final) R834799C004 (Final) R829213 (Final) |
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Darrow LA, Hess J, Rogers CA, Tolbert PE, Klein M, Sarnat SE. Ambient pollen concentrations and emergency department visits for asthma and wheeze. Journal of Allergy and Clinical Immunology 2012;130(3):630-638. |
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Darrow LA, Klein M, Flanders WD, Mulholland JA, Tolbert PE, Strickland MJ. Air pollution and acute respiratory infections among children 0-4 years: an 18-year time-series study. American Journal of Epidemiology 2014;180(10):968-977. |
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Dionisio KL, Isakov V, Baxter LK, Sarnat JA, Sarnat SE, Burke J, Rosenbaum A, Graham SE, Cook R, Mulholland J, Ozkaynak H. Development and evaluation of alternative approaches for exposure assessment of multiple air pollutants in Atlanta, Georgia. Journal of Exposure Science & Environmental Epidemiology 2013;23(6):581-592. |
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Dionisio KL, Baxter LK, Chang HH. An empirical assessment of exposure measurement error and effect attenuation in bipollutant epidemiologic models. Environmental Health Perspectives 2014;122(11):1216-1224. |
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Dionisio KL, Chang HH, Baxter LK. A simulation study to quantify the impacts of exposure measurement error on air pollution health risk estimates in copollutant time-series models. Environmental Health 2016;15(1):114 (10 pp.). |
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Fang T, Verma V, Guo H, King LE, Edgerton ES, Weber RJ. A semi-automated system for quantifying the oxidative potential of ambient particles in aqueous extracts using the dithiothreitol (DTT) assay: results from the Southeastern Center for Air Pollution and Epidemiology (SCAPE). Atmospheric Measurement Techniques 2015;8(1):471-482. |
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Fang T, Guo H, Verma V, Peltier RE, Weber RJ. PM2.5 water-soluble elements in the southeastern United States: automated analytical method development, spatiotemporal distributions, source apportionment, and implications for heath studies. Atmospheric Chemistry and Physics 2015;15(20):11667-11682. |
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Fang T, Verma V, Bates JT, Abrams J, Klein M, Strickland MJ, Sarnat SE, Chang HH, Mulholland JA, Tolbert PE, Russell AG, Weber RJ. Oxidative potential of ambient water-soluble PM2.5 in the southeastern United States: contrasts in sources and health associations between ascorbic acid (AA) and dithiothreitol (DTT) assays. Atmospheric Chemistry and Physics 2016;16(6):3865-3879. |
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Fang T, Zeng L, Gao D, Verma V, Stefaniak AB, Weber RJ. Ambient size distributions and lung deposition of aerosol dithiothreitol-measured oxidative potential: Contrast between soluble and insoluble particles. Environmental Science & Technology 2017;51(12):6802-6811. |
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Fang T, Guo H, Zeng L, Verma V, Nenes A, Weber RJ. Highly acidic ambient particles, soluble metals, and oxidative potential: A link between sulfate and aerosol toxicity. Environmental Science & Technology 2017;51(5):2611-2620. |
R834799 (Final) |
Exit |
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Flanders WD, Klein M, Darrow LA, Strickland MJ, Sarnat SE, Sarnat JA, Waller LA, Winquist A, Tolbert PE. A method for detection of residual confounding in time-series and other observational studies. Epidemiology 2011;22(1):59-67. |
R834799 (2013) R834799 (2014) R834799 (2015) R834799 (2016) R834799 (Final) R834799C003 (2015) R834799C003 (Final) R834799C004 (2013) R834799C004 (2014) R834799C004 (2015) R834799C004 (Final) R833626 (Final) |
Exit |
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Flanders WD, Klein M, Darrow LA, Strickland MJ, Sarnat SE, Sarnat JA, Waller LA, Winquist A, Tolbert PE. A method to detect residual confounding in spatial and other observational studies. Epidemiology 2011;22(6):823-826. |
R834799 (2012) R834799 (2013) R834799 (2014) R834799 (2015) R834799 (2016) R834799 (Final) R834799C003 (2013) R834799C003 (2014) R834799C003 (2015) R834799C003 (Final) R834799C004 (2013) R834799C004 (2014) R834799C004 (2015) R834799C004 (Final) R833626 (Final) |
Exit |
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Flanders WD, Klein M. A general, multivariate definition of causal effects in epidemiology. Epidemiology 2015;26(4):481-489. |
R834799 (2016) R834799 (Final) |
Exit |
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Flanders WD, Klein M. Rejoinder. Epidemiology 2015;26(4):496-497. |
R834799 (2016) R834799 (Final) |
Exit |
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Flanders WD, Klein M, Mirabelli MC. Conditions for valid estimation of causal effects on prevalence in cross-sectional and other studies. Annals of Epidemiology 2016;26(6):389-394.e2. |
R834799 (2016) R834799 (Final) |
Exit |
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Flanders WD, Strickland MJ, Klein M. A new method for partial correction of residual confounding in time-series and other observational studies. American Journal of Epidemiology 2017;185(10):941-949. |
R834799 (2016) R834799 (Final) R834799C003 (Final) |
Exit |
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Friberg MD, Zhai X, Holmes HA, Chang HH, Strickland MJ, Sarnat SE, Tolbert PE, Russell AG, Mulholland JA. Method for fusing observational data and chemical transport model simulations to estimate spatiotemporally resolved ambient air pollution. Environmental Science & Technology 2016;50(7):3695-3705. |
R834799 (2016) R834799 (Final) R834799C003 (Final) R834799C004 (2015) R834799C004 (Final) |
Exit Exit Exit |
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Friberg MD, Kahn RA, Holmes HA, Chang HH, Sarnat SE, Tolbert PE, Russell AG, Mulholland JA. Daily ambient air pollution metrics for five cities: evaluation of data-fusion-based estimates and uncertainties. Atmospheric Environment 2017;158:36-50. |
R834799 (2016) R834799 (Final) R834799C004 (Final) |
Exit Exit Exit |
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Gao D, Fang T, Verma V, Zeng L, Weber RJ. A method for measuring total aerosol oxidative potential (OP) with the dithiothreitol (DTT) assay and comparisons between an urban and roadside site of water-soluble and total OP. Atmospheric Measurement Techniques 2017;10(8):2821-2835. |
R834799 (Final) |
Exit Exit |
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Gass K, Klein M, Chang HH, Flanders WD, Strickland MJ. Classification and regression trees for epidemiologic research: an air pollution example. Environmental Health 2014;13(1):17 (10 pp.). |
R834799 (2014) R834799 (2015) R834799 (2016) R834799 (Final) R834799C003 (2013) R834799C003 (2014) R834799C003 (2015) R834799C003 (Final) R834799C004 (2013) R834799C004 (2014) R834799C004 (2015) R834799C004 (Final) |
Exit Exit Exit |
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Gass K, Balachandran S, Chang HH, Russell AG, Strickland MJ. Ensemble-based source apportionment of fine particulate matter and emergency department visits for pediatric asthma. American Journal of Epidemiology 2015;181(7):504-512. |
R834799 (2015) R834799 (2016) R834799 (Final) R834799C003 (2015) R834799C003 (Final) R833866 (Final) |
Exit Exit |
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Gass K, Klein M, Sarnat SE, Winquist A, Darrow LA, Flanders WD, Chang HH, Mulholland JA, Tolbert PE, Strickland MJ. Associations between ambient air pollutant mixtures and pediatric asthma emergency department visits in three cities: a classification and regression tree approach. Environmental Health 2015;14:58 (14 pp.). |
R834799 (2015) R834799 (2016) R834799 (Final) R834799C003 (2015) R834799C003 (Final) R834799C004 (2014) R834799C004 (2015) R834799C004 (Final) |
Exit Exit Exit |
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Golan R, Ladva C, Greenwald R, Krall JR, Raysoni AU, Kewada P, Winquist A, Flanders WD, Liang D-H, Sarnat JA. Acute pulmonary and inflammatory response in young adults following a scripted car commute. Air Quality, Atmosphere & Health 2018;11(2):123-136. |
R834799 (Final) |
Exit |
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Goldman GT, Mulholland JA, Russell AG, Strickland MJ, Klein M, Waller LA, Tolbert PE. Impact of exposure measurement error in air pollution epidemiology: effect of error type in time-series studies. Environmental Health 2011;10:61 (11 pp.). |
R834799 (2011) R834799 (2013) R834799 (2014) R834799 (2015) R834799 (2016) R834799 (Final) R834799C003 (2011) R834799C003 (2013) R834799C003 (2014) R834799C003 (2015) R834799C003 (Final) R834799C004 (2013) R834799C004 (2014) R834799C004 (2015) R834799C004 (Final) R829213 (Final) R833866 (Final) |
Exit Exit |
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Goldman GT, Mulholland JA, Russell AG, Gass K, Strickland MJ, Tolbert PE. Characterization of ambient air pollution measurement error in a time-series health study using a geostatistical simulation approach. Atmospheric Environment 2012;57:101-108. |
R834799 (2012) R834799 (2013) R834799 (2014) R834799 (2015) R834799 (2016) R834799 (Final) R834799C003 (2012) R834799C003 (2013) R834799C003 (2014) R834799C003 (2015) R834799C003 (Final) R834799C004 (2013) R834799C004 (2014) R834799C004 (2015) R834799C004 (Final) R829213 (Final) R833626 (Final) R833866 (Final) |
Exit Exit Exit |
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Greenwald R, Bergin MH, Yip F, Boehmer T, Kewada P, Shafer MM, Schauer JJ, Sarnat JA. On-roadway in-cabin exposure to particulate matter: measurement results using both continuous and time-integrated sampling approaches. Aerosol Science and Technology 2014;48(6):664-675. |
R834799 (2014) R834799 (2015) R834799 (2016) R834799 (Final) R834799C002 (2014) R834799C002 (2015) R834799C002 (Final) |
Exit Exit Exit |
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Guo H, Xu L, Bougiatioti A, Cerully KM, Capps SL, Hite Jr. JR, Carlton AG, Lee S-H, Bergin MH, Ng NL, Nenes A, Weber RJ. Fine-particle water and pH in the southeastern United States. Atmospheric Chemistry and Physics 2015;15(9):5211-5228. |
R834799 (2015) R834799 (2016) R834799 (Final) R834799C001 (2015) R834799C001 (Final) R835041 (2015) R835041 (Final) R835410 (2013) R835410 (2014) R835410 (2015) R835410 (Final) |
Exit Exit Exit |
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Hao H, Chang HH, Holmes HA, Mulholland JA, Klein M, Darrow LA, Strickland MJ. Air pollution and preterm birth in the U.S. state of Georgia (2002-2006): associations with concentrations of 11 ambient air pollutants estimated by combining Community Multiscale Air Quality Model (CMAQ) simulations with stationary monitor measurements. Environmental Health Perspectives 2016;124(6):875-880. |
R834799 (2015) R834799 (2016) R834799 (Final) R834799C003 (2015) R834799C003 (Final) |
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Heidari L, Winquist A, Klein M, O’Lenick CR, Grundstein A, Sarnat SE. Susceptibility to heat-related fluid and electrolyte imbalance emergency department visits in Atlanta, Georgia, USA. International Journal of Environmental Research and Public Health 2016;13(10):982 (17 pp.). |
R834799 (2016) R834799 (Final) R834799C004 (Final) R829213 (Final) |
Exit Exit Exit |
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Henneman LRF, Holmes HA, Mulholland JA, Russell AG. Meteorological detrending of primary and secondary pollutant concentrations: Method application and evaluation using long-term (2000–2012) data in Atlanta. Atmospheric Environment 2015;119(Suppl C):201-210. |
R834799 (Final) |
Exit Exit |
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Hu X, Waller LA, Al-Hamdan MZ, Crosson WL, Estes Jr. MG, Estes SM, Quattrochi DA, Sarnat JA, Liu Y. Estimating ground-level PM2.5 concentrations in the southeastern U.S. using geographically weighted regression. Environmental Research 2013;121:1-10. |
R834799 (2013) R834799 (2014) R834799 (2015) R834799 (2016) R834799 (Final) R834799C003 (2013) R834799C003 (2014) R834799C003 (2015) R834799C003 (Final) |
Exit Exit Exit |
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Hu X, Waller LA, Lyapustin A, Wang Y, Al-Hamdan MZ, Crosson WL, Estes Jr. MG, Estes SM, Quattrochi DA, Puttaswamy SJ, Liu Y. Estimating ground-level PM2.5 concentrations in the Southeastern United States using MAIAC AOD retrievals and a two-stage model. Remote Sensing of Environment 2014;140:220-232. |
R834799 (2014) R834799 (2015) R834799 (2016) R834799 (Final) R834799C003 (2013) R834799C003 (2014) R834799C003 (2015) R834799C003 (Final) |
Exit Exit Exit |
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Hu X, Waller LA, Lyapustin A, Wang Y, Liu Y. 10-year spatial and temporal trends of PM2.5 concentrations in the southeastern US estimated using high-resolution satellite data. Atmospheric Chemistry and Physics 2014;14(12):6301-6314. |
R834799 (2014) R834799 (2015) R834799 (2016) R834799 (Final) R834799C003 (2014) R834799C003 (2015) R834799C003 (Final) |
Exit Exit |
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Hu X, Waller LA, Lyapustin A, Wang Y, Liu Y. Improving satellite-driven PM2.5 models with Moderate Resolution Imaging Spectroradiometer fire counts in the southeastern U.S. Journal of Geophysical Research: Atmospheres 2014;119(19):11375-11386. |
R834799 (2015) R834799 (2016) R834799 (Final) |
Exit Exit |
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Hu Y, Balachandran S, Pachon JE, Baek J, Ivey C, Holmes H, Odman MT, Mulholland JA, Russell AG. Fine particulate matter source apportionment using a hybrid chemical transport and receptor model approach. Atmospheric Chemistry and Physics 2014;14(11):5415-5431. |
R834799 (2015) R834799 (2016) R834799 (Final) |
Exit Exit |
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Hu Y, Odman MT, Chang ME, Russell AG. Operational forecasting of source impacts for dynamic air quality management. Atmospheric Environment 2015;116:320-322. |
R834799 (2015) R834799 (2016) R834799 (Final) R833866 (Final) R835217 (2014) R835217 (Final) |
Exit Exit Exit |
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Huang R, Zhai X, Ivey CE, Friberg MD, Hu X, Liu Y, Qian Di, Schwartz J, Mulholland JA, Russel AG. Air pollutant exposure field modeling using air quality model-data fusion methods and comparison with satellite AOD-derived fields: application over North Carolina, USA. Air Quality, Atmosphere & Health 2018;11(1):11-22. |
R834799 (Final) |
Exit |
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Ivey CE, Holmes HA, Hu YT, Mulholland JA, Russell AG. Development of PM2.5 source impact spatial fields using a hybrid source apportionment air quality model. Geoscientific Model Development 2015;8(7):2153-2165. |
R834799 (2015) R834799 (2016) R834799 (Final) |
Exit Exit |
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Ivey CE, Holmes HA, Hu Y, Mulholland JA, Russell AG. A method for quantifying bias in modeled concentrations and source impacts for secondary particulate matter. Frontiers of Environmental Science & Engineering 2016;10:14. |
R834799 (2016) R834799 (Final) |
Exit Exit |
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Ivey C, Holmes H, Shi G, Balachandran S, Hu Y, Russell AG. Development of PM2.5 source profiles using a hybrid chemical transport-receptor modeling approach. Environmental Science & Technology 2017;51(23):13788-13796. |
R834799 (Final) R833626 (Final) R833866 (Final) |
Exit Exit Exit |
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Keller JP, Chang HH, Strickland MJ, Szpiro AA. Measurement error correction for predicted spatiotemporal air pollution exposures. Epidemiology 2017;28(3):338-345. |
R834799 (2016) R834799 (Final) R834799C003 (Final) R834796 (2016) R834796 (Final) |
Exit Exit |
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Keller JP, Chang HH, Strickland MJ, Szpiro AA. Measurement error correction for predicted spatiotemporal air pollution exposures. Epidemiology 2017;28(3):338-345. |
R834799 (Final) R834796 (Final) |
Exit Exit |
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Keller JP, Chang HH, Strickland MJ, Szpiro AA. Measurement error correction for predicted spatiotemporal air pollution exposures. Epidemiology 2017;28(3):338-345. |
R834799 (2016) R834799 (Final) R834799C003 (Final) R834796 (2016) R834796 (Final) |
Exit Exit |
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King LE, Weber RJ. Development and testing of an online method to measure ambient fine particulate Reactive Oxygen Species (ROS) based on the 2’,7’-dichlorofluorescin (DCFH) assay. Atmospheric Measurement Techniques 2013;6(7):1647-1658. |
R834799 (2013) R834799 (2014) R834799 (2015) R834799 (2016) R834799 (Final) R834799C001 (2013) R834799C001 (2014) R834799C001 (2015) R834799C001 (Final) |
Exit Exit |
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Krall JR, Chang HH, Sarnat SE, Peng RD, Waller LA. Current methods and challenges for epidemiological studies of the associations between chemical constituents of particulate matter and health. Current Environmental Health Reports 2015;2(4):388-398. |
R834799 (2016) R834799 (Final) R834799C004 (2015) R834799C004 (Final) |
Exit Exit Exit |
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Krall JR, Mulholland JA, Russell AG, Balachandran S, Winquist A, Tolbert PE, Waller LA, Sarnat SE. Associations between source-specific fine particulate matter and emergency department visits for respiratory disease in four U.S. cities. Environmental Health Perspectives 2017;125(1):97-103. |
R834799 (2016) R834799 (Final) R834799C004 (2015) R834799C004 (Final) R829213 (Final) R833866 (Final) |
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Krall Jenna R, Chandresh N, Ladva Armistead G, Russell Rachel Golan, Xing Peng, Guoliang Shi, Roby Greenwald, Amit U. Raysoni, Lance A. Waller, and Jeremy A. Sarnat. “Source-Specific Pollution Exposure and Associations with Pulmonary Response in the Atlanta Commuters Exposure Studies.” Journal of Exposure Science & Environmental Epidemiology 28, no. 4 (June 2018):337–47. |
R834799 (Final) |
Exit Exit |
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Ladva CN, Golan R, Greenwald R, Yu T, Sarnat SE, Flanders WD, Uppal K, Walker DI, Tran V, Liang D, Jones DP, Sarnat JA. Metabolomic profiles of plasma, exhaled breath condensate, and saliva are correlated with potential for air toxics detection. Journal of Breath Research 2017;12(1):016008. |
R834799 (Final) |
Exit |
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Lawson AB. Commentary: Assessment of chance should be central in investigation of cancer clusters. International Journal of Epidemiology 2013;42(2):448-449. |
R834799 (Final) |
Exit Exit |
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Li W, Xu L, Liu X, Zhang J, Lin Y, Yao X, Gao H, Zhang D, Chen J, Wang W, Harrison RM, Zhang X, Shao L, Fu P, Nenes A, Shi Z. Air pollution–aerosol interactions produce more bioavailable iron for ocean ecosystems. Science Advances 2017;3(3):e1601749 (7 pp.). |
R834799 (Final) |
Exit Exit |
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Liang, Donghai, Rachel Golan, Jennifer L. Moutinho, Howard H. Chang, Roby Greenwald, Stefanie E. Sarnat, Armistead G. Russell, and Jeremy A. Sarnat. “Errors Associated with the Use of Roadside Monitoring in the Estimation of Acute Traffic Pollutant-Related Health Effects.” Environmental Research 165 (August 1, 2018):210–19. |
R834799 (Final) |
Exit Exit Exit |
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Liu J, Bergin M, Guo H, King L, Kotra N, Edgerton E, Weber RJ. Size-resolved measurements of brown carbon in water and methanol extracts and estimates of their contribution to ambient fine-particle light absorption. Atmospheric Chemistry and Physics 2013;13(24):12389-12404. |
R834799 (2014) R834799 (2015) R834799 (2016) R834799 (Final) R834799C001 (2013) R834799C001 (2014) R834799C001 (2015) R834799C001 (Final) |
Exit Exit Exit |
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Liu J, Scheuer E, Dibb J, Ziemba LD, Thornhill KL, Anderson BE, Wisthaler A, Mikoviny T, Devi JJ, Bergin M, Weber RJ. Brown carbon in the continental troposphere. Geophysical Research Letters 2014;41(6):2191-2195. |
R834799 (2014) R834799 (2015) R834799 (2016) R834799 (Final) R834799C001 (2014) R834799C001 (2015) R834799C001 (Final) R835039 (Final) |
Exit Exit Exit |
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Lv B, Hu Y, Chang HH, Russell AG, Bai Y. Improving the accuracy of daily PM2.5 distributions derived from the fusion of ground-level measurements with aerosol optical depth observations, a case study in North China. Environmental Science & Technology 2016;50(9):4752-4759. |
R834799 (Final) R833866 (Final) R835217 (Final) |
Exit Exit Exit |
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Ma Z, Hu X, Huang L, Bi J, Liu Y. Estimating ground-level PM2.5 in China using satellite remote sensing. Environmental Science & Technology 2014;48(13):7436-7444. |
R834799 (2014) R834799 (2015) R834799 (2016) R834799 (Final) R834799C003 (2014) R834799C003 (2015) R834799C003 (Final) |
Exit Exit Exit |
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Ma Z, Hu X, Sayer AM, Levy R, Zhang Q, Xue Y, Tong S, Bi J, Huang L, Liu Y. Satellite-based spatiotemporal trends in PM2.5 concentrations: China, 2004-2013. Environmental Health Perspectives 2016;124(2):184-192. |
R834799 (2015) R834799 (2016) R834799 (Final) |
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Maier ML, Balachandran S, Sarnat SE, Turner JR, Mulholland JA, Russell AG. Application of an ensemble-trained source apportionment approach at a site impacted by multiple point sources. Environmental Science & Technology 2013;47(8):3743-3751. |
R834799 (2013) R834799 (2014) R834799 (2015) R834799 (2016) R834799 (Final) R834799C004 (2013) R834799C004 (2014) R834799C004 (2015) R834799C004 (Final) R833626 (Final) R833866 (Final) |
Exit Exit Exit |
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McGuinn LA, Ward-Caviness C, Neas LM, Schneider A, Di Q, Chudnovsky A, Schwartz J, Koutrakis P, Russell AG, Garcia V, Kraus WE, Hauser ER, Cascio W, Diaz-Sanchez D, Devlin RB. Fine particulate matter and cardiovascular disease: comparison of assessment methods for long-term exposure. Environmental Research 2017;159:16-23. |
R834799 (Final) R835872 (2016) |
Exit Exit Exit |
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Mirabelli MC, Golan R, Greenwald R, Raysoni AU, Holguin F, Kewada P, Winquist A, Flanders WD, Sarnat JA. Modification of traffic-related respiratory response by asthma control in a population of car commuters. Epidemiology 2015;26(4):546-555. |
R834799 (2015) R834799 (2016) R834799 (Final) R834799C002 (2015) R834799C002 (Final) |
Exit |
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Neelon B, Chang HH, Ling Q, Hastings NS. Spatiotemporal hurdle models for zero-inflated count data: exploring trends in emergency department visits. Statistical Methods in Medical Research 2014 [Epub ahead of print]. |
R834799 (2014) R834799 (2015) R834799 (2016) |
Exit |
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Neelon B, Chang HH, Ling Q, Hastings NS. Spatiotemporal hurdle models for zero-inflated count data: Exploring trends in emergency department visits. Statistical Methods in Medical Research 2016;25(6):2558-2576. |
R834799 (Final) |
Exit |
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O'Lenick CR, Winquist A, Mulholland JA, Friberg MD, Chang HH, Kramer MR, Darrow LA, Sarnat SE. Assessment of neighbourhood-level socioeconomic status as a modifier of air pollution-asthma associations among children in Atlanta. Journal of Epidemiology and Community Health 2017;71(2):129-136. |
R834799 (2016) R834799 (Final) R834799C004 (Final) R829213 (Final) |
Exit |
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O'Lenick CR, Winquist A, Chang HH, Kramer MR, Mulholland JA, Grundstein A, Sarnat SE. Evaluation of individual and area-level factors as modifiers of the association between warm-season temperature and pediatric asthma morbidity in Atlanta, GA. Environmental Research 2017;156:132-144. |
R834799 (2016) R834799 (Final) R834799C004 (Final) |
Exit Exit Exit |
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O’Lenick CR, Chang HH, Kramer MR, Winquist A, Mulholland JA, Friberg MD, Sarnat SE. Ozone and childhood respiratory disease in three US cities: evaluation of effect measure modification by neighborhood socioeconomic status using a Bayesian hierarchical approach. Environmental Health 2017;16(1):36 (15 pp.). |
R834799 (2016) R834799 (Final) R834799C004 (Final) R829213 (Final) |
Exit Exit Exit |
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Pachon JE, Balachandran S, Hu Y, Mulholland JA, Darrow LA, Sarnat JA, Tolbert PE, Russell AG. Development of outcome-based, multipollutant mobile source indicators. Journal of the Air & Waste Management Association 2012;62(4):431-442. |
R834799 (2012) R834799 (2013) R834799 (2014) R834799 (2015) R834799 (2016) R834799 (Final) R834799C003 (2013) R834799C003 (2014) R834799C003 (2015) R834799C003 (Final) R834799C004 (2013) R834799C004 (2014) R834799C004 (2015) R834799C004 (Final) R833626 (Final) R833866 (Final) |
Exit Exit Exit |
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Pachon JE, Weber RJ, Zhang X, Mulholland JA, Russell AG. Revising the use of potassium (K) in the source apportionment of PM2.5. Atmospheric Pollution Research 2013;4(1):14-21. |
R834799 (2014) R834799 (2015) R834799 (2016) R834799 (Final) R834799C004 (2013) R834799C004 (2014) R834799C004 (2015) R833626 (Final) R833866 (Final) |
Exit Exit Exit |
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Park S-K, Russell AG. Regional adjustment of emission strengths via four dimensional data assimilation. Asia-Pacific Journal of Atmospheric Sciences 2013;49(3):361-374. |
R834799 (2015) R834799 (2016) R834799 (Final) R831076 (Final) |
Exit |
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Park S-K, Marmur A, Russell AG. Environmental risk assessment: comparison of receptor and air quality models for source apportionment. Human and Ecological Risk Assessment 2013;19(5):1385-1403. |
R834799 (2015) R834799 (2016) R834799 (Final) R831076 (Final) |
Exit |
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Pearce JL, Waller LA, Chang HH, Klein M, Mulholland JA, Sarnat JA, Sarnat SE, Strickland MJ, Tolbert PE. Using self-organizing maps to develop ambient air quality classifications: a time series example. Environmental Health 2014;13:56. |
R834799 (2014) R834799 (2015) R834799 (2016) R834799 (Final) R834799C003 (2015) R834799C003 (Final) R834799C004 (2014) R834799C004 (2015) R834799C004 (Final) |
Exit Exit Exit |
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Pearce JL, Waller LA, Mulholland JA, Sarnat SE, Strickland MJ, Chang HH, Tolbert PE. Exploring associations between multipollutant day types and asthma morbidity: epidemiologic applications of self-organizing map ambient air quality classifications. Environmental Health 2015;14:55 (12 pp.). |
R834799 (2015) R834799 (2016) R834799 (Final) R834799C003 (2013) R834799C003 (2015) R834799C003 (Final) R834799C004 (2013) R834799C004 (2015) R834799C004 (Final) |
Exit Exit Exit |
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Pearce JL, Waller LA, Sarnat SE, Chang HH, Klein M, Mulholland JA, Tolbert PE. Characterizing the spatial distribution of multiple pollutants and populations at risk in Atlanta, Georgia. Spatial and Spatio-temporal Epidemiology 2016;18:13-23. |
R834799 (2016) R834799 (Final) R834799C004 (Final) |
Exit Exit Exit |
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Pennington AF, Strickland MJ, Freedle KA, Klein M, Drews-Botsch C, Hansen C, Darrow LA. Evaluating early-life asthma definitions as a marker for subsequent asthma in an electronic medical record setting. Pediatric Allergy and Immunology 2016;27(6):591-596. |
R834799 (2016) R834799 (Final) |
Exit |
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Pennington AF, Strickland MJ, Klein M, Zhai X, Russell AG, Hansen C, Darrow LA. Measurement error in mobile source air pollution exposure estimates due to residential mobility during pregnancy. Journal of Exposure Science and Environmental Epidemiology 2017;27(5):513-520. |
R834799 (2016) R834799 (Final) R834799C003 (Final) |
Exit |
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Pennington AF, Strickland MJ, Klein M, Zhai X, Bates JT, Drews-Botsch C, Hansen C, Russell AG, Tolbert PE, Darrow LA. Exposure to mobile source air pollution in early-life and childhood asthma incidence: the Kaiser Air Pollution and Pediatric Asthma Study. Epidemiology 2018;29(1):22-30. |
R834799 (Final) |
Exit |
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Pennington A, Strickland M, Gass K, Klein M, Sarnat S, Tolbert P, Balachandran S, Change H, Russel A, Mulholland J, Darrow L. Source-Apportioned PM2.5 and Cardiorespiratory Emergency Department Visits Accounting for Source Contribution Uncertainty. EPIDEMIOLOGY 2019;30(6):789-798. |
R834799 (Final) R833866 (Final) |
Exit |
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Qin M, Hu Y, Wang X, Vasilakos P, Boyd CM, Xu L, Song Y, Ng NL, Nenes A, Russell AG. Modeling biogenic secondary organic aerosol (BSOA) formation from monoterpene reactions with NO3:a case study of the SOAS campaign using CMAQ. Atmospheric Environment 2018;184:146-155. |
R834799 (Final) R835403 (Final) |
Exit Exit Exit |
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Redman JD, Holmes HA, Balachandran S, Maier ML, Zhai X, Ivey C, Digby K, Mulholland JA, Russell AG. Development and evaluation of a daily temporal interpolation model for fine particulate matter species concentrations and source apportionment. Atmospheric Environment 2016;140:529-538. |
R834799 (2016) R834799 (Final) R833626 (Final) R833866 (Final) |
Exit Exit Exit |
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Reich BJ, Chang HH, Strickland MJ. Spatial health effects analysis with uncertain residential locations. Statistical Methods in Medical Research 2014;23(2):156-168. |
R834799 (2012) R834799 (2013) R834799 (2014) R834799 (2015) R834799 (2016) R834799 (Final) R834799C003 (2012) R834799C003 (2013) R834799C003 (2014) R834799C003 (2015) R834799C003 (Final) R833863 (2011) |
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Reich BJ, Chang HH, Foley KM. A spectral method for spatial downscaling. Biometrics 2014;70(4):932-942. |
R834799 (2014) R834799 (2015) R834799 (2016) R834799 (Final) R835228 (2013) R835228 (2014) R835228 (Final) |
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Sarnat JA, Sarnat SE, Flanders WD, Chang HH, Mulholland J, Baxter L, Isakov V, Ozkaynak H. Spatiotemporally resolved air exchange rate as a modifier of acute air pollution-related morbidity in Atlanta. Journal of Exposure Science & Environmental Epidemiology 2013;23(6):606-615. |
R834799 (2013) R834799 (2014) R834799 (2015) R834799 (2016) R834799 (Final) R834799C002 (2013) R834799C002 (2014) R834799C002 (2015) R834799C002 (Final) R834799C004 (2013) R834799C004 (2014) R834799C004 (2015) R834799C004 (Final) |
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Sarnat JA, Golan R, Greenwald R, Raysoni AU, Kewada P, Winquist A, Sarnat SE, Flanders WD, Mirabelli MC, Zora JE, Bergin MH, Yip F. Exposure to traffic pollution, acute inflammation and autonomic response in a panel of car commuters. Environmental Research 2014;133:66-76. |
R834799 (2014) R834799 (2015) R834799 (2016) R834799 (Final) R834799C002 (2014) R834799C002 (2015) R834799C002 (Final) |
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Sarnat SE, Sarnat JA, Mulholland J, Isakov V, Ozkaynak H, Chang HH, Klein M, Tolbert PE. Application of alternative spatiotemporal metrics of ambient air pollution exposure in a time-series epidemiological study in Atlanta. Journal of Exposure Science & Environmental Epidemiology 2013;23(6):593-605. |
R834799 (2014) R834799 (2015) R834799 (2016) R834799 (Final) R834799C004 (2013) R834799C004 (2014) R834799C004 (2015) R834799C004 (Final) |
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Sarnat SE, Winquist A, Schauer JJ, Turner JR, Sarnat JA. Fine particulate matter components and emergency department visits for cardiovascular and respiratory diseases in the St. Louis, Missouri-Illinois, metropolitan area. Environmental Health Perspectives 2015;123(5):437-444. |
R834799 (2015) R834799 (2016) R834799 (Final) R834799C004 (2014) R834799C004 (2015) R834799C004 (Final) |
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Sarnat SE, Chang HH, Weber RJ. Ambient PM2.5 and health: does PM2.5 oxidative potential play a role? American Journal of Respiratory and Critical Care Medicine 2016;194(5):530-531. |
R834799 (2016) R834799 (Final) R834799C001 (Final) R834799C004 (Final) |
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Shi G, Xu J, Peng X, Xiao Z, Chen K, Tian Y, Guan X, Feng Y, Yu H, Nenes A, Russell AG. pH of aerosols in a polluted atmosphere:source contributions to highly acidic Aerosol. Environmental Science & Technology 2017;51(8):4289-4296. |
R834799 (Final) |
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Shi G, Peng X, Huangfu Y, Wang W, Xu J, Tian Y, Feng Y, Ivey CE, Russell AG. Quantification of source impact to PM using three-dimensional weighted factor model analysis on multi-site data. Atmospheric Environment 2017;160:89-96. |
R834799 (Final) |
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Strickland MJ, Darrow LA, Mulholland JA, Klein M, Flanders WD, Winquist A, Tolbert PE. Implications of different approaches for characterizing ambient air pollutant concentrations within the urban airshed for time-series studies and health benefits analyses. Environmental Health 2011;10:36 (9 pp.). |
R834799 (2011) R834799 (2013) R834799 (2014) R834799 (2015) R834799 (2016) R834799 (Final) R834799C003 (2011) R834799C003 (2013) R834799C003 (2014) R834799C003 (2015) R834799C003 (Final) R834799C004 (2013) R834799C004 (2014) R834799C004 (2015) R834799C004 (Final) R829213 (Final) |
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Strickland MJ, Marsh CA, Darrow LA. Gestational age-specific associations between infantile acute bronchiolitis and asthma after age five. Pediatric and Perinatal Epidemiology 2014;28(6):521-526. |
R834799 (2015) R834799 (2016) R834799 (Final) R834799C003 (2015) R834799C003 (Final) |
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Strickland MJ, Klein M, Flanders WD, Chang HH, Mulholland JA, Tolbert PE, Darrow LA. Modification of the effect of ambient air pollution on pediatric asthma emergency visits: susceptible subpopulations. Epidemiology 2014;25(6):843-850. |
R834799 (2014) R834799 (2015) R834799 (2016) R834799 (Final) R834799C003 (2014) R834799C003 (2015) R834799C003 (Final) |
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Strickland MJ, Gass KM, Goldman GT, Mulholland JA. Effects of ambient air pollution measurement error on health effect estimates in time-series studies: a simulation-based analysis. Journal of Exposure Science & Environmental Epidemiology 2015;25(2):160-166. |
R834799 (2013) R834799 (2014) R834799 (2015) R834799 (2016) R834799 (Final) R834799C003 (2013) R834799C003 (2014) R834799C003 (2015) R834799C003 (Final) |
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Strickland MJ, Hao H, Hu X, Chang HH, Darrow LA, Liu Y. Pediatric emergency visits and short-term changes in PM2.5 concentrations in the U.S. state of Georgia. Environmental Health Perspectives 2016;124(5):690-696. |
R834799 (2015) R834799 (2016) R834799 (Final) R834799C003 (2015) R834799C003 (Final) |
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Strickland MJ, Lin Y, Darrow LA, Warren JL, Mulholland JA, Chang HH. Associations between ambient air pollutant concentrations and birth weight:A quantile regression analysis.Epidemiology 2019;30:624. |
R834799 (Final) |
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Tuet WY, Fok S, Verma V, Tagle Rodriguez MS, Grosberg A, Champion JA, Ng NL. Dose-dependent intracellular reactive oxygen and nitrogen species (ROS/RNS) production from particulate matter exposure: comparison to oxidative potential and chemical composition. Atmospheric Environment 2016;144:335-344. |
R834799 (Final) |
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Verma V, Rico-Martinez R, Kotra N, King L, Liu J, Snell TW, Weber RJ. Contribution of water-soluble and insoluble components and their hydrophobic/hydrophilic subfractions to the reactive oxygen species-generating potential of fine ambient aerosols. Environmental Science & Technology 2012;46(20):11384-11392. |
R834799 (2012) R834799 (2013) R834799 (2014) R834799 (2015) R834799 (2016) R834799 (Final) R834799C001 (2012) R834799C001 (2013) R834799C001 (2014) R834799C001 (2015) R834799C001 (Final) |
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Verma V, Rico-Martinez R, Kotra N, Rennolds C, Liu J, Snell TW, Weber RJ. Estimating the toxicity of ambient fine aerosols using freshwater rotifer Brachionus calyciflorus (Rotifera: Monogononta). Environmental Pollution 2013;182:379-384. |
R834799 (2014) R834799 (2015) R834799 (2016) R834799 (Final) R834799C001 (2013) R834799C001 (2014) R834799C001 (2015) R834799C001 (Final) |
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Verma V, Fang T, Guo H, King L, Bates JT, Peltier RE, Edgerton E, Russell AG, Weber RJ. Reactive oxygen species associated with water-soluble PM2.5 in the southeastern United States: spatiotemporal trends and source apportionment. Atmospheric Chemistry and Physics 2014;14(23):12915-12930. |
R834799 (2015) R834799 (2016) R834799 (Final) R834799C001 (2015) R834799C001 (Final) |
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Verma V, Fang T, Xu L, Peltier RE, Russell AG, Ng NL, Weber RJ. Organic aerosols associated with the generation of reactive oxygen species (ROS) by water-soluble PM2.5. Environmental Science & Technology 2015;49(7):4646-4656. |
R834799 (2015) R834799 (2016) R834799 (Final) R834799C001 (2015) R834799C001 (Final) |
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Verma V, Wang Y, El-Afifi R, Fang T, Rowland J, Russell AG, Weber RJ. Fractionating ambient humic-like substances (HULIS) for their reactive oxygen species activity—assessing the importance of quinones and atmospheric aging. Atmospheric Environment 2015;120:351-359. |
R834799 (2015) R834799 (2016) R834799 (Final) R834799C001 (Final) |
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Vreeland H, Weber R, Bergin M, Greenwald R, Golan R, Russell AG, Verma V, Sarnat JA. Oxidative potential of PM2.5 during Atlanta rush hour: Measurements of in-vehicle dithiothreitol (DTT) activity. Atmospheric Environment 2017;165:169-178. |
R834799 (Final) |
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Waller LA. Commentary: regarding assessments of chance in investigations of ‘cluster series.’ International Journal of Epidemiology 2013;42(2):449-452. |
R834799 (2013) R834799 (2014) R834799 (2015) R834799 (2016) R834799 (Final) R834799C003 (2013) R834799C003 (2014) R834799C003 (2015) R834799C003 (Final) |
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Weber RJ, Guo H, Russell AG, Nenes A. High aerosol acidity despite declining atmospheric sulfate concentrations over the past 15 years. Nature Geoscience 2016;9:282-285. |
R834799 (2016) R834799 (Final) R834799C001 (Final) R835410 (2013) R835410 (2014) R835410 (2015) R835410 (Final) |
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Winquist A, Klein M, Tolbert P, Sarnat SE. Power estimation using simulations for air pollution time-series studies. Environmental Health 2012;11:68 (12 pp.). |
R834799 (2012) R834799 (2013) R834799 (2014) R834799 (2015) R834799 (2016) R834799 (Final) R834799C004 (2012) R834799C004 (2013) R834799C004 (2014) R834799C004 (2015) R834799C004 (Final) |
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Winquist A, Klein M, Tolbert P, Flanders WD, Hess J, Sarnat SE. Comparison of emergency department and hospital admissions data for air pollution time-series studies. Environmental Health 2012;11:70 (14 pp.). |
R834799 (2012) R834799 (2013) R834799 (2014) R834799 (2015) R834799 (2016) R834799 (Final) R834799C004 (2012) R834799C004 (2013) R834799C004 (2014) R834799C004 (2015) R834799C004 (Final) |
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Winquist A, Kirrane E, Klein M, Strickland M, Darrow LA, Sarnat SE, Gass K, Mulholland J, Russell A, Tolbert P. Joint effects of ambient air pollutants on pediatric asthma emergency department visits in Atlanta, 1998-2004. Epidemiology 2014;25(5):666-673. |
R834799 (2014) R834799 (2015) R834799 (2016) R834799 (Final) R834799C003 (2014) R834799C003 (2015) R834799C003 (Final) R834799C004 (2014) R834799C004 (2015) R834799C004 (Final) |
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Winquist A, Schauer JJ, Turner JR, Klein M, Sarnat SE. Impact of ambient fine particulate matter carbon measurement methods on observed associations with acute cardiorespiratory morbidity. Journal of Exposure Science & Environmental Epidemiology 2015;25(2):215-221. |
R834799 (2014) R834799 (2015) R834799 (2016) R834799 (Final) R834799C004 (2014) R834799C004 (2015) R834799C004 (Final) |
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Winquist A, Grundstein A, Chang HH, Hess J, Sarnat SE. Warm season temperature and emergency department visits in Atlanta, Georgia. Environmental Research 2016;147:314-323. |
R834799 (2016) R834799 (Final) R834799C004 (Final) |
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Xiao Q, Ma Z, Li S, Liu Y. The impact of winter heating on air pollution in China. PLoS One 2015;10(1):e0117311 (11 pp.). |
R834799 (Final) |
Exit Exit |
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Xiao Q, Liu Y, Mulholland JA, Russell AG, Darrow LA, Tolbert PE, Strickland MJ. Pediatric emergency department visits and ambient air pollution in the U.S. state of Georgia: a case-crossover study. Environmental Health 2016;15(1):115. |
R834799 (2016) R834799 (Final) R834799C003 (Final) |
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Xu L, Guo H, Boyd CM, Klein M, Bougiatioti A, Cerully KM, Hite JR, Isaacman-VanWertz G, Kreisberg NM, Knote C, Olson K, Koss A, Goldstein AH, Hering SV, de Gouw JA, Baumann K, Lee S-H, Nenes A, Weber RJ, Ng NL. Effects of anthropogenic emissions on aerosol formation from isoprene and monoterpenes in the southeastern United States. Proceedings of the National Academy of Sciences of the United States of America 2015;112(1):37-42. |
R834799 (2015) R834799 (2016) R834799 (Final) R834799C001 (2015) R834799C001 (Final) R835403 (2014) R835403 (2015) R835403 (Final) R835410 (2013) R835410 (2014) R835410 (2015) R835410 (Final) |
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Xu L, Suresh S, Guo H, Weber RJ, Ng NL. Aerosol characterization over the southeastern United States using high resolution aerosol mass spectrometry: spatial and seasonal variation of aerosol composition, sources, and organic nitrates. Atmospheric Chemistry and Physics 2015;15(15):7307-7336. |
R834799 (2015) R834799 (2016) R834799 (Final) |
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Ye D, Klein M, Chang HH, Sarnat JA, Mulholland JA, Edgerton ES, Winquist A, Tolbert PE, Sarnat SE. Estimating acute cardiorespiratory effects of ambient volatile organic compounds. Epidemiology 2017;28(2):197-206. |
R834799 (2016) R834799 (Final) R834799C004 (Final) |
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Ye D, Klein M, Mulholland JA, Russell AG, Weber R, Edgerton ES, Chang HH, Sarnat JA, Tolbert PE, Sarnat SE. Estimating acute cardiovascular effects of ambient PM2.5 metals. Environmental Health Perspectives 2018;126:027007 (10 pp.). |
R834799 (Final) R829213 (Final) |
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Yu C, Di Girolamo L, Chen L, Zhang X, Liu Y. Statistical evaluation of the feasibility of satellite-retrieved cloud parameters as indicators of PM2.5 levels. Journal of Exposure Science & Environmental Epidemiology 2015;25(5):457-466. |
R834799 (2014) R834799 (2015) R834799 (2016) R834799 (Final) R834799C003 (2014) R834799C003 (2015) R834799C003 (Final) |
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Yu W, Liu Y, Ma Z, Bi J. Improving satellite-based PM2.5 estimates in China using Gaussian processes modeling in a Bayesian hierarchical setting. Scientific Reports 2017;7(1):7048 (9 pp.). |
R834799 (Final) |
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Zhai X, Russell AG, Sampath P, Mulholland JA, Kim B-U, Kim Y, D'Onofrio D. Calibrating R-LINE model results with observational data to develop annual mobile source air pollutant fields at fine spatial resolution: Application in Atlanta. Atmospheric Environment 2016;147:446-457. |
R834799 (Final) |
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Zhai X, Mulholland JA, Russell AG, Holmes HA. Spatial and temporal source apportionment of PM2.5 in Georgia, 2002 to 2013. Atmospheric Environment 2017;161:112-121. |
R834799 (Final) |
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Zhang T, Gong W, Wang W, Ji Y, Zhu Z, Huang Y. Ground level PM(2.5) estimates over China using satellite-based geographically weighted regression (GWR) models are improved by including NO(2) and enhanced vegetation index (EVI). International Journal of Environmental Research and Public Health 2016;13(12):E1215 (12 pp). |
R834799 (Final) |
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Zhang W, Trail MA, Hu Y, Nenes A, Russell AG. Use of high-order sensitivity analysis and reduced-form modeling to quantify uncertainty in particulate matter simulations in the presence of uncertain emissions rates: A case study in Houston. Atmospheric Environment 2015;122:103-113. |
R834799 (Final) |
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Zhang Z, Manjourides J, Cohen T, Hu Y, Jiang Q. Spatial measurement errors in the field of spatial epidemiology. International Journal of Health Geographics 2016;15(1):21 (12 pp.). |
R834799 (Final) |
Exit Exit |
Supplemental Keywords:
aerosol, air quality, air quality modeling, ambient air, atmosphere, biostatistics, chemical transport modeling, children, confounder control, cumulative effects, data analysis, dose-response, elemental carbon, epidemiology, exposure, exposure measurement error, GA, Georgia, health effects, human health, infants, inflammation, measurement methods, metals, mobile sources, monitoring, organics, oxidants, oxidative potential, oxidative stress, ozone, PAH, PAHs, particulates, PM2.5, public policy, reactive oxygen species, receptor modeling, risk, ROS, sensitive populations, source characterization, Southeast, study design, sulfates, susceptibility, vulnerability, Health, Scientific Discipline, Health Risk Assessment, Risk Assessments, Biochemistry, children's health, particulate matter, ambient air monitoring, climate change, air pollution, airshed modeling, ambient particle health effects, human health riskRelevant Websites:
Southeastern Center for Air Pollution Exit
Progress and Final Reports:
Original Abstract Subprojects under this Center: (EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).
R834799C001 Development and Deployment of an Instrumentation Suite for Comprehensive Air Quality Characterization Including Aerosol ROS
R834799C002 Examining In-Vehicle Pollution and Oxidative Stress in a Cohort of Daily Commuters
R834799C003 Novel Estimates of Pollutant Mixtures and Pediatric Health in Two Birth Cohorts
R834799C004 A Multi-City Time-Series Study of Pollutant Mixtures and Acute Morbidity
The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.
Project Research Results
- 2016 Progress Report
- 2015 Progress Report
- 2014 Progress Report
- 2013 Progress Report
- 2012 Progress Report
- 2011 Progress Report
- Original Abstract
135 journal articles for this center