2011 Progress Report: Multi-Scale Assessment of Health Effects of Air Pollution Mixtures Using Novel Measurements and Models

EPA Grant Number: R834799
Center: 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: Weber, Rodney J. , Bergin, Michael , Mulholland, James , Nenes, Athanasios , Sarnat, Stefanie Ebelt , Sarnat, Jeremy , Strickland, Matthew J
Current Investigators: Tolbert, Paige , Barry, Vaughn , Bergin, Michael , Bilonick, Richard , Chang, Howard , Darrow, Lyndsey , Diaz-Sanchez, David , Flanders, Dana , Greenwald, Roby , Guensler, Randy , Hu, Yongtao , Klein, Mitchel , Liu, Yang , Mulholland, James , Nenes, Athanasios , Odman, Mehmet Talat , Russell, Armistead G. , Sarnat, Stefanie Ebelt , Sarnat, Jeremy , Strickland, Matthew J , Talbott, Evelynn , Waller, Lance , Weber, Rodney J. , Winquist, Andrea
Institution: Georgia Institute of Technology , Emory 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 Period Covered by this Report: January 1, 2011 through July 31,2011
Project Amount: $7,999,779
RFA: Clean Air Research Centers (2009) RFA Text |  Recipients Lists
Research Category: Global Climate Change , Air Quality and Air Toxics , Air

Objective:

Air Quality Core
The primary mission of the Air Quality Core (AQC) is to provide Center researchers the information and methods to comprehensively characterize air pollutant mixtures relevant to their projects and to support project activities by collecting and managing data, developing a “Mixture Characterization Toolkit” (MC Toolkit) for further analyses specific to the projects, and providing the expertise and resources to facilitate the application of MC Toolkit components. An additional mission of the AQC is to facilitate transmission of atmospheric data and methods to potential users outside of the Center. The more comprehensive characterization is developed, first, by analyses of the detailed chemical and physical measurements produced by the Center along with those available from other routine and special studies. Further spatial and temporal characterization of the air pollutant mixtures, and the sources involved, will come from the use of extended receptor-oriented and chemical transport models (CTM) applied over multiple scales. The MC Toolkit is being developed to include a range of both source- and receptor-oriented air quality models, regression approaches and hybrid methods. In support of the four Research Projects and other Cores within the Center, the AQC has six functions: (1) atmospheric data collection and management; (2) development of the MC Toolkit to support Center projects; (3) support of project teams using the MC Toolkit; (4) application of the extended Models 3/CMAQ; (5) integration of satellite remote sensing into health studies and air pollutant mixture characterization; and (6) assessment of exposure misclassification. In addition to these functions, the AQC team assists in the preparation of reports and journal publications resulting from Center activities.

Biostatistics Core
The primary objective of the Biostatistics Core is to provide statistical support to the Center and to the associated projects. The five primary functions of the Biostatistics Core are to: (1) provide guidance and support to all projects for design issues; (2) provide guidance and support to all projects for epidemiologic modeling, including identification and characterization of mixtures and their health effects; (3) perform methodological development, including identification of model mis-specification, analyses of time series based on LASSO and CART, and identification of mixtures that associate with health outcomes; (4) develop and provide support and guidance for addressing the impact of measurement error; and (5) archive, document, and assure security of analytic data files.

Project 1: Development and Deployment of an Instrumentation Suite for Comprehensive Air Quality Characterization Including Aerosol ROS

Develop method(s) for measuring ROS online and semi-continuously, acquire instrumentation, and organize the measurement program. Undertake an extensive measurement campaign that will characterize aerosol spatial distributions of key air quality parameters to inform the SCAPE modeling and health studies.

Project 2: Examining In-Vehicle Pollution and Oxidative Stress in a Cohort of Daily Commuters
To examine the effects of exposure to particulate mixtures occurring during automobile commuting and within indoor, non-commuting microenvironments (μE's) and corresponding measures of oxidative stress-mediated response.

Project 3: Novel Estimates of Pollutant Mixtures and Pediatric Health in Two Birth Cohorts
Explore the interplay between certain early life events, characterizations of air pollutant mixtures developed as part of the Center’s MC Toolkit, and a range of pediatric health outcomes using two large, population-based birth cohorts.

In utero and early life experiences affect physiological development and can influence sensitivity to environmental factors throughout life. In this project, we will explore the interplay between certain early life events, characterizations of air pollutant mixtures developed as part of the Center’s MC Toolkit, and a range of pediatric health outcomes using two large, population-based birth cohorts. One cohort consists of roughly 2.3 million Georgia birth records that have been geocoded and linked with pediatric emergency department visits by staff at the Georgia Department of Human Resources. Using this statewide birth cohort, we will investigate acute effects of air pollution mixtures on respiratory health outcomes and ear infections in children, and we will assess whether children who were born premature or low birth weight are more sensitive to ambient air pollutant concentrations than their counterparts. Further, we will use the statewide birth cohort to investigate whether ambient air pollutant mixtures during pregnancy are associated with the risk of preterm delivery or reduced birth weight. The second birth cohort is 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 are available for each study subject, we will examine whether air pollutant mixtures during the first year of life are associated with the incidence of childhood asthma.

Project 4: A Multi-City Time-Series Study of Pollutant Mixtures and Acute Morbidity

Conduct a multi-city time-series study to clarify the impacts of air quality on acute cardiorespiratory morbidity in five U.S. cities using novel mixture characterization metrics.

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 are conducting a multi-city time-series study to clarify the impacts of air quality on acute cardiorespiratory morbidity in five U.S. cities using novel mixture characterization metrics. Our overarching hypothesis is that factors related to air pollution mixtures, seasonality and climate, concentration-response functions, exposure measurement error, and population susceptibility and vulnerability can help explain apparent between-city heterogeneity in short-term associations between air quality measures and cardiorespiratory emergency department (ED) visits and hospitalizations.

Progress Summary:

Air Quality Core
1. Developing the MC Toolkit for further analyses specific to the projects.
2. Gathering air quality-related data for areas where studies are planned.
3. Applying various receptor modeling approaches to air quality data in Atlanta, Dallas, and St. Louis.
4. Applying a new, hybrid ensemble source apportionment approach to air quality data in Atlanta.
5. Developing and applying a new, hybrid chemical transport model-chemical mass balance (CMB) based approach with results available for six cities.
6. Conducting analyses to develop a better understanding of how air quality observations can best be used to estimate population exposure and how exposure measurement error can impact epidemiologic results (Strickland, et al., 2011).

The AQC has been actively engaged in beginning the development of MC Toolkit and the foundational methods upon which the methods rely. Further, we are gathering air quality-related data for the areas where studies are planned, first concentrating on collecting air quality and emissions data for Georgia, Dallas, and St. Louis. A password-protected website has been established for sharing data between the research teams.

We have applied various receptor modeling approaches (CMB-based, PMF, ensemble) to Atlanta, Dallas, and St. Louis. We are further applying a new, hybrid, ensemble source apportionment approach to Atlanta with an emphasis on characterizing the level of uncertainty in the more traditional methods used. A new, hybrid, chemical transport model CMB-based approach has been developed and applied, with results available for six cities at present.

Work is continuing on developing a better understanding of how air quality observations can best be used to estimate population exposures and how exposure measurement error can impact epidemiologic results. One study was completed characterizing measurement error due to instrument imprecision and spatial variability as multiplicative (i.e., additive on the log scale) and modeling it over a range of error types to assess impacts on risk ratio estimates both on a per measurement unit basis and on a per interquartile range basis in a time-series study in Atlanta. Building on this work, a second study simulated pollutant fields over a 6-year time period over the 20-county metropolitan Atlanta area. These pollutant fields were developed to mimic the statistical properties of the actual observations. Error type was characterized, and the impact of error on the epidemiologic analysis was predicted. Measurement error due to spatial variability alone was found to be largely Berkson, suggesting reductions in significance but minimal risk attenuation in time-series risk estimates due to this error source. However, total measurement error, consisting of spatial variability error and error associated with instrument imprecision and location, results in substantial attenuation of the risk estimate, particularly for primary pollutants.

Biostatistics Core

1. Initiated conversations on the conceptual nature of mixtures across Clean Air Research Centers and completed a first draft of a manuscript to summarize these ideas.
2. Continued work on methods for the identification of model mis-specification, particularly due to confounding. A manuscript for application of the Core’s approach to spatial studies, entitled “A method for detection of residual confounding in spatial and other observational studies” and led by Dr. Flanders, has been accepted in Epidemiology.
3. Considered the impact of Berkson type error and the relationship with use of the population weighted average to measure levels of an air pollutant. Identified clearly how bias occurs with Berkson error in Poisson regression (with the usual log-link function) and derived a correction approach for use with Poisson regression when one uses population weighted averages.
4. Provided support for Center Projects with regard to design issues.

In this first period, we have performed a number of activities.
1. We have considered the conceptual nature of mixtures. The goal is to clarify the different conceptual issues that are often raised in discussing mixtures so that they can be identified and addressed more clearly. We have initiated conversations across the EPA Clean Air Research Centers on this topic and written a first draft of a manuscript to summarize these ideas.
2. We continued our work on methods for the identification of model mis-specification, particularly that due to confounding. A manuscript on application of our approach to spatial studies is now accepted for publication in Epidemiology.
3. We have made progress in considering the impact of Berkson type error, and the relationship with use of the population weighted average to measure levels of an air pollutant. We have identified clearly how bias occurs with Berkson error in Poisson regression (with the usual log-link function). We have also derived a correction approach for use with Poisson regression when one uses population weighted averages.
4. We participated in meetings and provided support for Center projects with regard to design issues.

Project 1:  Development and Deployment of an Instrumentation Suite for Comprehensive Air Quality Characterization Including Aerosol ROS

The first reporting period for Project 1 focused on two major areas: (1) developing online semi-continuous methods to quantify reactive oxygen species (ROS) in aerosol particles, and (2) acquiring and preparing instrumentation for field studies in years 2 and 3. More specifically, the following tasks were undertaken:
1. Testing three different chemical probes (DCFH/HRP, Amplex Red, and DDT Assay) for ROS. Experiments have been completed for the DCFH probe and testing for the latter two probes will be completed this year.
2. Tested two methods for collecting ambient particles into water for ROS analysis, including a particle-into-liquid-sampler and a Mist Chamber. These experiments resulted in selection of the Mist Chamber, and two Mist Chambers have been constructed.
3. Preliminary ambient field testing of a Mist Chamber/DCFH system have been undertaken and first results suggest a viable online ROS method.
4. Various instruments have been acquired and assembled in preparation for the upcoming intensive field study.

The first reporting period of the project focused on two major areas: 1) developing online semi-continuous methods to quantify ROS in aerosol particles, and 2) acquiring and preparing instrumentation for field studies in years 2 and 3. Each aspect is discussed separately.

ROS Instrument Development
A number of tasks have been undertaken in the development of an online ROS method. This includes testing three different chemical probes and testing two methods for collecting ambient particles into water for ROS analysis. The three probes tested were:
1. DCFH/HRP – which is reported to provide a chemically comprehensive measure of ROS in ambient particles (Venkatachari and Hopke, 2008).
2. Amplex Red – which is reported to provide a more chemically specific measurement of ROS, specifically sensitive to H2O2 (Yan, et al., 2005).
3. DDT Assay – a probe that will provide a measure of the capability of ambient particles to oxidize cellular anti-oxidants and is referred to as a measure of oxidative potential/oxidative activity/redox activity (Cho, et al., 2005).

Our approach was to first test the characteristics of the three probes to various operational parameters by measuring response to H2O2 standards to determine suitability and requirements for the online system. The parameters tested were:
1. Chemical source (vendor) of probe (most important for DCFH).
2. Chemical stability of probes when in appropriate solutions needed for the measurement (i.e., how often do we have to make new solutions).
3. Considerations required for handling probe solutions (i.e., how light sensitive, what type of dark room is needed and what needs to be prepared in the dark).
4. Probe response to various concentrations of H2O2 as a function of method for mixing probe and standard (e.g., or ambient sample) through comparisons of online mixing schemes (e.g., super serpentine reactors of various length) vs. mixing in a vial.
5. Response as a function of mix incubation temperature.

6. Response as a function of mix incubation time.
7. A determination of the probe sensitivity to H2O2 (slope of response vs. H2O2 concentration). 
8. Determination of method blanks and estimation of detection limits.

These experiments have been completed for the DCFH probe and are still in progress for the Amplex Red and DDT Assay; the latter two will be completed this year.

Two automated particle collection methods were tested; a PILS (particle-into-liquid-sampler) and a Mist Chamber. These experiments resulted in the selection of a Mist Chamber over the PILS for the following reasons:
1. The Mist Chamber operates in a batch mode and extensive mixing of probe and sample is achieved during sample collection. PILS operates in a continuous collection mode and requires mixing of probe and sample as a separate component. Thus, the Mist Chamber was operationally a simpler device.
2. Concerns associated with possible loss of volatile ROS components in the steam-based vapor condensation collection system of the PILS (sample heated to 100°C) compared to the scrubbing/wetted filter (which actually cools sample due to latent heat of evaporating water) approach of the Mist Chamber.
3. Potential for a smaller, simpler more robust design with the Mist Chamber.

Two Mist Chambers have been constructed by the Georgia Tech glass shop at a cost of roughly $100/collector. Preliminary ambient field-testing of a Mist Chamber/DCFH system has been undertaken. Difficulties with liquid pumping systems are currently being resolved, but first results suggest a viable online ROS method.

Field deployment preparation
In preparation for the upcoming intensive field study the following has been performed.
1. Development of Project 1 Quality Assurance Project Plan (QAPP).
2. Writing of SOPs for the 18 instruments/analysis methods to be deployed.
3. Development of a preliminary deployment schedule.
4. Acquiring and assembling the various instruments.

Project 2:  Examining In-Vehicle Pollution and Oxidative Stress in a Cohort of Daily Commuters

1. Evaluating protocol proof-of-concept based on the ongoing results from the Centers for Disease Control and Prevention-funded Atlanta Commuter Exposure (ACE) study. As a result of this initial evaluation, design modifications have begun for the vehicle pollutant sampler, pollutant analytical protocols, and database management systems to meet Project 2 research aims.
2. Commenced a sub-analysis examining in-vehicle noise as a potential confounder of any observed pollutant-related health effects.

Work on Project 2 during the first reporting period has focused on: (a) developing and finalizing the project QAPP, SOPs, and technician manuals; (b) establishing proof-of-concept for the measurement methods to be used during field sampling; and (c) conducting a targeted sub-analysis aimed at examining the potential for confounding in the commuter study.

A draft of the Project 2 QAPP has been written and reviewed by the quality assurance team. In addition, we have written and compiled all SOPs, technician guidance documents and operation manuals to be used during the field data collection and analysis phase of the project. During this reporting period, we have continued to evaluate protocol proof-of-concept based on the ongoing results from our Centers for Disease Control and Prevention-funded Atlanta Commuters Exposure (ACE) study. The ACE study concluded field sampling during June 2011. In total, there were 40 subjects (20 physician-diagnosed adult asthmatics and 20 healthy adults) who participated in ACE. While the hypotheses and design of Project 2 differ from the ACE study in its focus on pollutant mixtures and oxidative stress-associated mechanistic pathways, the ACE study has served as a critical means of evaluating the proposed Project 2 protocol and methods. As a result of initial proof-of-concept evaluation from the ACE study, we have begun to design modifications to the in-vehicle pollutant sampler used in the ACE study, the pollutant analytical protocols, and database management systems to meet the Project 2 research aims. Specifically, the Project 2 in-vehicle sampler will use two DC-powered rocking piston pumps instead of the vacuum pumps used for ACE. These pumps will provide similar flow rates (100 LPM) while emitting less noise during the commutes. Using our initial ACE results as a guide, we have also switched our proposed method for characterizing particle count concentrations from a TSI P-TRAK Ultrafine Particle Counter to a TSI Condensation Particle Counter (Model 3006).

Few previous studies have quantified concurrent in-vehicle noise levels and corresponding pollutant concentrations. This is a significant omission for understanding the link between traffic exposures and human health, given results showing strong associations between traffic noise and numerous health endpoints, including cardiovascular outcomes 1-3. This finding has led some to claim that health effects attributed to PM may be confounded by factors such as noise. To address this issue, we have commenced a Project 2 sub-analysis examining in-vehicle noise as a potential confounder of any observed pollutant-related health effects. During July - September 2012, we will be conducting sampling in a variety of commuter exposure settings to characterize correlation patterns between measured noise and corresponding in-vehicle concentrations of size-resolved particle mass, particle counts, black carbon, and particle-bound polycyclic aromatic hydrocarbons.

Project 3: Novel Estimates of Pollutant Mixtures and Pediatric Health in Two Birth Cohorts

1. Obtained individual-level birth data from 1994-2006 from the Office of Health Indicators and Policy, Georgia Division of Public Health.
2. Obtained individual-level pediatric emergency department data from the Georgia Hospital Association for 1999-2010.
3. Evaluating data quality, creating analytic datasets, and describing the distribution of outcomes in space and time.

We have been successful in obtaining the health data for this project. In June 2011 we received individual-level birth data from 1994-2006 from the Office of Health Indicators and Policy, Georgia Division of Public Health. These statewide data have daily temporal resolution, are geocoded to the 2000 Census Block Group level, and have a longitudinal ID that can be linked to the emergency department data. In July 2011 we received individual-level pediatric emergency department data from the Georgia Hospital Association for 1999-2010. These data have daily temporal resolution and are geocoded to the ZIP code level. To this point we have not used any of these data in air pollution analyses. Our focus has been to evaluate the quality of the data, create analytic datasets, describe the distribution of outcomes in space and time, etc.

Several different products from the Center’s Air Quality Core will be available for use in Project 3. Efforts have been made to collect all the air quality and emissions data from Georgia. Various receptor modeling approaches are under development using these Georgia data. Work on the consequences of measurement error in time-series studies (using data from Atlanta) is ongoing and includes both simulation-based work as well as theoretical work.

Project 4: A Multi-City Time-Series Study of Pollutant Mixtures and Acute Morbidity

Project 4 has focused on assessment of the specific cities to be included in the study and initiation of the health and air quality data collection phase of the project. Progress made on obtaining data for each city is described below:
1. For Atlanta, GA, existing emergency department (ED) visit and hospital admission (HA) databases covering the 1993-2004 time period were extended through 2009 with data acquired from the Georgia Hospital Association. These data are currently being processed and validated for use in epidemiologic analyses. Air quality (AQ) monitoring data for the extended time period have been acquired from state and federal monitoring networks, and data from local intensive monitoring programs has been requested.
2. For St. Louis, MO-IL, all ED visit, hospitalization, and AQ monitoring were acquired previously. The AQ data have been shared among the project team for use in the mixture characterization metrics development.
3. For Dallas, TX, negotiations with a central health data source have progressed and a data use agreement is currently under review. Data transfer to Emory investigators is anticipated by September 2011. All relevant AQ data for Dallas have been acquired and population-weighted metrics have been created.
4. For Pittsburgh, PA, progress has been made on developing the required collaboration with the University of Pittsburgh investigators and assessing the feasibility of including data from this study in the current project (e.g., with respect to anticipated data availability, timeline, and data sharing matters).
5. For Birmingham, progress has been made on acquiring the relevant AQ monitoring data and initiation of hospital recruitment activities.
6. Considering the feasibility of including a limited number of additional cities to this study.

During the current reporting period (1/1/2011-7/31/2011), work on Project 4 has focused on development of the project QAPP and associated data management activities, assessment of the specific cities to be included in the study, and initiation of the health and air quality data collection phase of the project. The specific cities proposed for this study were largely chosen based on availability of at least two years of daily speciated particulate matter (PM) data and availability of individual-level ED visit and/or hospitalization data for the corresponding time period. We have ongoing studies in Atlanta, GA; Dallas, TX; and St. Louis, MO-IL that meet these criteria. Data collection for these cities has progressed throughout the reporting period. For Atlanta, GA, existing ED visit and HA databases covering the 1993-2004 time period were extended through 2009 with data acquired from the Georgia Hospital Association. These data are currently being processed and validated for use in epidemiologic analyses. Air quality (AQ) monitoring data for the extended time period have been acquired from state and federal monitoring networks, and data from local intensive monitoring programs [e.g., the SouthEastern Aerosol Research and Characterization (SEARCH) network] has been requested. For St. Louis, MO-IL, all ED visit, hospitalization, and AQ monitoring data have been acquired previously. The AQ data have been shared among the project team for use in the mixture characterization metrics development. For Dallas, TX, negotiations with a central health data source have progressed and a data use agreement is currently under review. Data transfer to Emory investigators is anticipated by September 2011. All relevant AQ data for Dallas have been acquired and population-weighted metrics have been created. Pittsburgh, PA, was selected as a city of interest because of a relevant ongoing study conducted by the University of Pittsburgh. Progress has been made on developing the required collaboration with the University of Pittsburgh investigators and assessing the feasibility of including data from this study in the current project (e.g., with respect to anticipated data availability, timeline, and data sharing matters). Finally, Birmingham, AL, was proposed as a city of interest due to its contrasting pollution mix from Atlanta, availability of detailed daily speciated AQ measurements conducted as part of the SEARCH network, and feasibility of ED visit and HA data collection from hospitals. Progress has been made on acquiring the relevant AQ monitoring data and initiation of hospital recruitment activities. These five cities may be characterized as distinct, non-coastal major urban population centers with varying degrees of contribution from traffic, industrial sources, coal-fired power plants, and secondary pollutant formation. We are considering the feasibility of including a limited number of additional cities in this study, which may provide increased power and generalizability of study findings.

Future Activities:

Air Quality Core

1. Continue to collect relevant air quality-related data (e.g., air quality and emissions data), apply the various source apportionment approaches, and finalize the hybrid CTM-CMB approach.
2. Continue to build the air quality database to support Projects 3 and 4 with data obtained from EPA’s AQS and STN and from the SEARCH and ARIES networks supported by EPRI.
3. Conduct descriptive analyses of the data and error analyses to support Projects 3 and 4.
4. Implement organic speciation methodology in support of Projects 1 and 2.

Plans for 2011-2012 include continued collection of relevant air quality-related data (e.g., air quality and emissions data), application of the various source apportionment approaches, and finalization of the hybrid CTM-CMB approach. Building of the air quality data base to support Projects 3 and 4 will continue with data obtained from EPA’s AQS and STN and from the SEARCH and ARIES networks supported by EPRI. Descriptive analyses of the data will be performed and error analyses conducted to support Projects 3 and 4. Organic speciation methodology in support of Projects 1 and 2 will be implemented.

Biostatistics Core

1. Continue work on conceptualizing mixtures, measurement errors, and support of separate research projects in regard to design and analytic issues.
2. Work to adapt methods for analyses of time series based on LASSO and CART.

Over the next period, we plan to continue our work on conceptualizing mixtures, measurement errors, and support of separate research projects in regard to design and analytic issues. We will also work to adapt methods for analyses of time series based on LASSO and CART.

Project 1: Development and Deployment of an Instrumentation Suite for Comprehensive Air Quality Characterization including Aerosol ROS

1. Finish development of the ROS instrument, perform preliminary testing and validation, prepare manuscripts describing ROS instrumentation, and present results at meetings.
2. Continue acquiring/testing instrumentation necessary for field deployment.
3. Begin first year of roughly two continuous years of field measurements at sites within Atlanta.
4. Collect and quality check data from field studies and submit to data archive.

Project 2: Examining In-Vehicle Pollution and Oxidative Stress in a Cohort of Daily Commuters

1. Continue to finalize the sampling protocol and evaluate proof-of-concept based on the ACE study results throughout 2011 with a goal of beginning subject recruitment in November 2011.
2. Continue staffing throughout 2011 in anticipation of commencing actual field sampling in spring 2012. Hire a Project Manager at the postdoctoral level to begin working around October 2011.
3. Conduct the sub-analysis examining in-vehicle noise as a potential confounder of observed pollutant-related health effects during the July – September 2012 time period.

We expect to continue finalizing the Project 2 sampling protocol and evaluating proof-of-concept based on the ACE results throughout 2011 with a goal of beginning subject recruitment in November 2011. Project 2 staffing will also continue throughout 2011 in anticipation of commencing actual field sampling in spring 2012. We expect to hire a Project Manager (at the post doc level) to begin working on the project in October 2011. A qualified candidate has been identified and we expect to receive a signed offer letter soon.

Project 3: Novel Estimates of Pollutant Mixtures and Pediatric Health in Two Birth Cohorts

1. Create final, clean, ready-to-use health datasets.
2. Work on analytic issues inherent in Project 3, particularly those related to mixtures and to the use of modeled exposure estimates in epidemiologic models.
3. Conduct empirical work characterizing mixtures that can be applied across Projects.

Howard Chang will begin a faculty position in biostatistics in August 2011 and will work on many of the analytic issues inherent in Project 3, particularly those related to mixtures and to the use of modeled exposure estimates in the epidemiological models. We recruited a student (Chao Yu) to work closely with Center investigator Yang Liu to collect and analyze satellite data for the Air Quality Core and Project 3. We plan to do some empirical work characterizing mixtures that can be applied across the different Projects (including Project 3). We will create final, clean, ready-to-use datasets so that we will be ready to analyze the various air quality estimates when they become available.

Project 4: A Multi-City Time-Series Study of Pollutant Mixtures and Acute Morbidity

1. Finalize selection of cities to be included and continue data collection activities.
2. Compile ED visit and hospitalization data from all cities, which will entail a combination of hospital recruitment activities and negotiations and contracts to be initiated with centralized data sources or collaborators.
3. Compile air quality monitoring data for all cities and relevant study periods and compute population-weighted averages when possible.
4. Commence work on developing the proposed mixture characterization metrics, including source-resolved PM metrics in each city.
5. Develop focused hypotheses and epidemiologic approaches for the planned multi-city analyses.

Over the coming year, we will finalize the selection of cities to be included in this study and will continue with data collection activities. Specifically, ED visit and hospitalization data will be compiled from all cities, which will entail a combination of hospital recruitment activities and negotiations and contracts to be initiated with centralized data sources or collaborators. Air quality monitoring data for all cities and relevant study periods will be compiled and population-weighted averages will be computed when possible. Work will commence on developing the proposed mixture characterization metrics, including source-resolved PM metrics in each city. Throughout the coming year, we also will develop focused hypotheses and epidemiologic approaches for the planned multi-city analyses.


Journal Articles: 132 Displayed | Download in RIS Format

Other center views: All 334 publications 136 publications in selected types All 132 journal articles
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Journal Article 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. R834799 (Final)
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  • Journal Article 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)
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  • Journal Article 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. R834799 (2012)
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  • Journal Article 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. R834799 (2014)
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  • Journal Article 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)
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  • Journal Article 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. R834799 (2015)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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. R834799 (Final)
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  • Journal Article 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.). R834799 (2012)
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  • Journal Article 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)
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  • Journal Article 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. R834799 (2014)
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  • Journal Article 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. R834799 (2014)
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  • Journal Article 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. R834799 (2014)
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  • Journal Article 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. R834799 (2015)
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  • Journal Article 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)
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  • Journal Article 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. R834799 (2012)
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  • Journal Article 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. R834799 (2015)
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  • Journal Article 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. R834799 (2014)
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  • Journal Article 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. R834799 (2014)
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  • Journal Article 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. R834799 (2015)
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  • Journal Article 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. R834799 (2015)
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  • Journal Article 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. R834799 (2015)
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  • Journal Article 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. R834799 (Final)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article Flanders WD, Klein M. A general, multivariate definition of causal effects in epidemiology. Epidemiology 2015;26(4):481-489. R834799 (2016)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article Reich BJ, Chang HH, Foley KM. A spectral method for spatial downscaling. Biometrics 2014;70(4):932-942. R834799 (2014)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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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  • Journal Article 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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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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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  • Journal Article Waller LA. Commentary: regarding assessments of chance in investigations of ‘cluster series.’ International Journal of Epidemiology 2013;42(2):449-452. R834799 (2013)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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)
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  • Journal Article 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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  • Journal Article 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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  • Journal Article 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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  • Journal Article 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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  • Journal Article 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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  • Journal Article 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)
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  • Supplemental Keywords:

    reactive oxygen species, ROS, oxidative stress, oxidative potential, air quality, chemical transport modeling, receptor modeling, exposure measurement error, measurement error, time series, spatial statistics, exposure misclassification, nonparametric methods, LASSO, CART, mixture models, health effects, inflammation, human health, susceptibility, vulnerability, PAHs, PM2.5, organics, elemental carbon, metals, ozone, oxidants, PAH, sulfates, source characterization, mobile sources, Georgia, GA, ambient air, atmosphere, health effects, sensitive populations, infants, children, risk, dose-response, cumulative effects, epidemiology, exposure, public policy, air quality modeling, monitoring, measurement methods, aerosol, particulates, Southeast, 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 risk

    Relevant Websites:

    www.scape.gatech.edu Exit

    Progress and Final Reports:

    Original Abstract
  • 2012 Progress Report
  • 2013 Progress Report
  • 2014 Progress Report
  • 2015 Progress Report
  • 2016 Progress Report
  • Final Report
  • 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