Grantee Research Project Results
2012 Progress Report: University of Washington Center for Clean Air Research (UW CCAR)
EPA Grant Number: R834796Center: University of Washington Center for Clean Air Research
Center Director: Vedal, Sverre
Title: University of Washington Center for Clean Air Research (UW CCAR)
Investigators: Vedal, Sverre , Sheppard, Lianne (Elizabeth) A. , Szpiro, Adam , Sampson, Paul
Current Investigators: Vedal, Sverre , Sheppard, Lianne (Elizabeth) A. , McDonald, Jacob D. , Kaufman, Joel D. , Campen, Matthew J. , VanReken, Timothy M. , Larson, Timothy V. , Szpiro, Adam , Simpson, Christopher , Rosenfeld, Michael , Yost, Michael , Sampson, Paul , Jobson, Thomas
Institution: University of Washington , Washington University , Lovelace Biomedical & Environmental Research Institute , University of New Mexico
Current Institution: University of Washington , Lovelace Biomedical & Environmental Research Institute , University of New Mexico , Washington University
EPA Project Officer: Callan, Richard
Project Period: December 1, 2010 through November 30, 2015 (Extended to November 30, 2017)
Project Period Covered by this Report: December 1, 2011 through July 31,2012
Project Amount: $8,000,000
RFA: Clean Air Research Centers (2009) RFA Text | Recipients Lists
Research Category: Human Health , Air
Objective:
Administrative Core:Objective of Research
The UW CCAR is focused on the cardiovascular health effects of near-roadway pollution, a complex mixture of particle, vapor and gas phase components that vary by vehicle emission source, road surface, extent of physical aging and the type and degree of atmospheric processing and photochemical reactions. This exposure scenario is not only known to be of considerable health importance, but also serves as a prototypical case for developing research approaches to dealing with multi-pollutant exposure-effect relationships. Our aim is to integrate exposure, epidemiological, toxicological, clinical, and statistical sciences to study cardiovascular hazards of fresh and aged roadway emissions and significantly advance our understanding of the components and reaction products that cause these effects.
The Center consists of five highly integrated research projects and two facility cores that together are pursuing the following six aims:
- To characterize real-world near-roadway pollutant concentrations, particle size distributions and chemical composition.
- To simulate realistic contrasting near-roadway multi-pollutant exposure atmospheres for laboratory animal and human studies.
- To identify cardiovascular and immunologic effects and the pathogenic mechanisms of near-roadway exposures using animal models.
- To identify cardiovascular and immunologic effects of near-roadway exposures in human clinical studies.
- To identify effects of long-term exposure to traffic-derived particles and gases on sub-clinical measures of cardiovascular disease and DNA methylation in a multi-ethnic population.
- To develop a statistical and methodological framework for studying health effects of multi-pollutant mixtures.
Biostatistics Core
Objective of Research
The overall objective is to support the statistical needs of all Center projects. This will be achieved through five specific objectives:
- Advise Center projects on data management and compilation. This Core will provide advice on database design, forms design, data entry support, data quality review, data storage, back-up and documentation.
- Ensure quality statistical design and analysis of Center research. The Core members meet regularly (weekly); these meetings ensure regular attention to the vast array of (bio)statistical needs of the Center, including: study design, power calculations, data collection, statistical analysis plan development, statistical analysis, and interpretation of results.
- Implement novel statistical methods that are required for Center projects. Novel statistical methods are incorporated into Projects 5 and 1 to jointly model and then estimate health effects for mixtures of pollutants.
- Identify additional statistical methodological research that will advance Center projects and seek resources to perform such research. The active participation of statisticians in the scientific research of the Center enables identification of innovative statistical methods and approaches to statistical analyses to deal with the most pressing scientific needs of the Center. The Center will catalyze (but not fund) solicitation of resources for new methodological research.
- Communicate and disseminate Center findings. This Core will aid in the interpretation of Center findings and use examples from Center research in statistical papers on methodological development and implementation. The Core will also collaborate on manuscripts, foster understanding of statistical methods, and engage statisticians in air pollution research.
Progress Summary:
Administrative Core:
Committees and Meetings
- Investigators Committee – The Investigators Committee is comprised of key members from all five research projects, as well as representatives from the Biostatistics and Administrative Cores.
As the research activity has accelerated in Year 2, this group now meets approximately every 4 weeks for status reports and to discuss the day to day scientific activities of the Center and its individual projects. We also have initiated a results or discussion period in these meetings where, on a rotating basis, investigators from each project present findings and progress.
- Internal Steering Committee – The Internal Steering Committee (ISC) is comprised of the Center Director, Deputy Directors, project and core PIs, the Center Quality Assurance Manager (QAM), and the Center Manager. This group meets quarterly to discuss finances, budgets, resource allocation, and collaborations. The ISC also serves as the Cross Collaboration Committee and convened recently to discuss the inter-Center collaboration projects proposed during the June 2012 CLARC Annual Meeting. The projects and scientific components of interest, collaborating parties, and budgeting requirements were discussed and the recommendations from this meeting are included in the Annual Report to help define the Center’s collaborative focus and participation.
- Scientific Advisory Committee – The Scientific Advisory Committee (SAC) is composed of 10 scientists representing varying specialties and institutions, including the U.S. EPA and members from the other CLARC Centers. A list of the committee members with their associated institutions appears in Table 1. The committee convened in Seattle for the first annual “UW CCAR” SAC meeting on September 26-27, 2011. We thank the committee for evaluating our Center’s initial project plan and for sharing their ideas. The insight and suggestions provided during that meeting, and in the follow up SAC comments, were greatly appreciated and have been strongly considered by our investigators. Our second SAC committee meeting is scheduled for September 27-28, 2012, with a similar format to the previous year. All 10 members, as well our EPA program and project officers, have confirmed their attendance and are expected to participate and offer constructive advice on the Center’s progress, direction, focus, and future.
Table 1 – CCAR Scientific Advisory Committee Members Expertise |
Member |
Institution |
Exposure Science |
Michael Brauer |
University of British Columbia |
Exposure Science |
Thomas Peters |
University of Iowa |
Exposure Science |
Barbara Turpin |
Rutgers University |
Epidemiology |
Arden Pope |
Brigham Young University |
Toxicology |
Ian Gilmour |
US EPA |
Toxicology |
Jake Lusis |
University of California, Los Angeles |
Toxicology |
Sanjay Rajagopalan |
Ohio State University (Michigan State University CLARC Member) |
Statistics |
Brent Coull |
Harvard University (Harvard University CLARC Member) |
Clinical Studies |
John Balmes |
University of California, San Francisco (Chair) |
Clinical Studies |
Nicholas Mills |
University of Edinburgh, UK |
Information Technology
- The Center continues to utilize the University of Washington’s Department of Environmental and Occupational Health Sciences (DEOHS) temporary server space. This resource is appropriately maintained, secured, and archived by DEOHS IT personnel, with password access for approved Center/project personnel. Its capacity is adequate for the current usage and can be expanded if needed.
- Each of the lead investigators, as well as the Internal Steering Committee, has been consulted for their data storage preferences and requirements, through the end of the Center’s award period. It was determined that the most appropriate course would be to have each project collect, process, analyze, and store their respective raw and “intermediate” data on their own institution or research group IT resources. Final products, or output from each project, and from the Biostatistics Core, will be stored for inter-project use, as well as external use and distribution, on a common Center drive. This drive would be password accessible to only the project PI’s and those approved by them. A Structured Query Language (SQL) server, as previously considered, will not be necessary. The proposed drive will integrate into an existing University of Washington DEOHS system, providing a very cost effective, flexible, reliable, protected, and secure computing environment that can be expanded and reconfigured easily. Figure 1 provides a general overview of the proposed project and data structure.
- The Center’s website has been live for almost 1 year and continues to provide information to the investigators, as well as to the general public. Content relating to the Center’s calendar, members, projects, and collaborators remains current. This Year 2 Annual Report provides a comprehensive list of all publications, presentations, posters, etc., relating to Center activities and these items will populate the site as soon as possible. As the Center and its individual projects continue to progress, we expect to have significant content to add to the website.
Subawards
- The three original Center sub-awards for Washington State University, Lovelace Respiratory Research Institute (LRRI), and the University of New Mexico were renewed for Year 2. We appreciate their participation and contributions to the Center as the research progresses. Financial information relating to the sub-awards was reported in the separate Center Annual Financial Report.
Biostatistics Core
The primary activities to date of the Biostatistics Core have fallen in three areas: participation in overall UW CCAR and CLARC activities, supporting the design and data management of the mobile monitoring research being conducted by Project 1, and advancing statistical methodological research.
Overall UW CCAR and CLARC Activities
Drs. Sheppard, Sampson, and Szpiro attended the June CLARC meeting along with student Josh Keller and soon-to-be-hired postdoctoral fellow Roman Jandarov. All Core representatives participated in the CLARC Biostatistics Workshop with presentations by Drs. Sheppard, Szpiro, and Sampson. This Core has collaborated with other Centers to develop two collaborative proposals: one on multipollutant measurement error, the other on modeling pollutant fields using satellite data.
Support of Project 1
The monitoring campaigns being conducted by Project 1 involve two different activities in each of four cities: 1) a mobile monitoring campaign that includes both continuous monitoring at a single fixed site along with repeated sampling of multiple intersections along three pre-determined routes over 9 days within a 2-week period during afternoon rush hours, and 2) a concurrent passive sampling campaign at a fixed number of stationary sites for a 2-week period. Biostatistics Core faculty and staff continue to support enhancements to the design of the monitoring campaigns. This year the Core also has supported a wide range of data-related activities including data cleaning, management, analysis, and presentation. We recently have begun to fund additional staff to develop the Project’s database management system.
Advancing Methodological Research
Our methodological work is advancing on two fronts: developing approaches to predict multipollutant surfaces across space and estimation of multipollutant health effects. Our objective is to use full multipollutant monitoring data to obtain estimated multivariate eigenpollutant health effects. (As described in our proposal we call eigenpollutants mixtures of multiple pollutants determined by a principal component analysis.)
- Multipollutant Prediction: In our current work we are considering whether the data reduction necessary to estimate eigenpollutants should be done prior to or after predicting pollutants. This project will move more quickly once our postdoctoral fellow starts in September.
- Multipollutant Health Effects: It now is well understood that spatial misalignment of exposure and health data means that a statistical model needed to predict exposures at subject locations (e.g., Sheppard, et al., 2011). Less attention has been paid to the implications of the predicted exposures in the inference about health effects. We have shown that counter to intuition, the best exposure model for prediction accuracy is not always the best for health effect inference (Szpiro, et al., 2011b). We also have developed theory to decompose the measurement error into Berkson-like error (from smoothing) and classical-like error (from estimating smoothing parameters) and have clarified the tradeoffs between these Berkson-like and classical-like components (Szpiro, et al., 2011a). Recent work suggests that for single pollutants 1) a lower rank exposure model increases Berkson-like error but decreases classical-like error; this may improve health effect inference even at the cost of worse prediction accuracy, and 2) it may be reasonable to guide the exposure model selection (e.g., lasso parameter selection) by the asymptotic results for health effect parameter estimates rather than prediction. Our preliminary assessment of multipollutant effects has shown that incompatibility between exposure models for different pollutants can introduce bias in the health effect estimates from the Berkson-like error component. Further work is needed to understand how to correct for this bias; we believe that the tradeoff with variability from classical-like error may depend on whether compatible models will work “almost as well” for individual pollutants.
Future Activities:
Administrative Core
- Committee Meetings – The Investigators and Internal Steering Committees will continue to meet regularly to discuss and refine the direction of the Center. Coordination for the September 27-28 SAC meeting is under way.
- Quality Management – The Center will continue to follow up with each individual project, and associated QAO, to review, revise, and archive all relevant SOPs, and their respective QAPPs. Additionally, Projects 4 and 5 will be responsible for submitting for approval their individual QAPPs before any data is collected.
- Information Technology – With the computing space for the Center, and each of its individual projects and cores now defined, the Center Manager will work with UW DEOHS IT staff to design and purchase the appropriate hardware needed to house the Center’s drive for final working products. This process should be completed and the system functional before the new year of 2013.
Biostatistics Core
We have successfully recruited a postdoctoral fellow, Roman Jandarov, to support our methodological research program. With this enhanced staffing, we expect to make good progress in the next year on methods to quantify the health effects of multipollutant mixtures in a cohort study. We will focus on exposure prediction models, relying to the degree possible on the foundation provided by our currently developed spatio-temporal model. We will assess whether the multipollutant data we will be using will be rich enough to support this model or whether alternative approaches will be necessary.
We will continue Core activities to support all projects on an as needed basis. In the next year we expect the bulk of our effort will continue to support Project 1 investigators and staff with their data management and analysis.
Journal Articles: 94 Displayed | Download in RIS Format
Other center views: | All 196 publications | 93 publications in selected types | All 92 journal articles |
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Adar SD, D'Souza J, Mendelsohn-Victor K, Jacobs DR, Cushman M, Sheppard L, Thorne PS, Burke GL, Daviglus ML, Szpiro AA, Diez Roux AV, Kaufman JD, Larson TV. Markers of inflammation and coagulation after long-term exposure to coarse particulate matter: a cross-sectional analysis from the Multi-Ethnic Study of Atherosclerosis. Environmental Health Perspectives 2015;123(6):541-548. |
R834796 (2014) R831697 (Final) R833741 (Final) |
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Aragon MJ, Chrobak I, Brower J, Roldan L, Fredenburgh LE, McDonald JD, Campen MJ. Inflammatory and vasoactive effects of serum following inhalation of varied complex mixtures. Cardiovascular Toxicology 2016;16(2):163-171. |
R834796 (2015) R834796 (Final) R834796C003 (2015) R834796C003 (Final) |
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Bergen S, Sheppard L, Sampson PD, Kim SY, Richards M, Vedal S, Kaufman JD, Szpiro AA. A national prediction model for PM2.5 component exposures and measurement error-corrected health effect inference. Environmental Health Perspectives 2013;121(9):1017-1025. |
R834796 (2013) R834796 (2014) R834796 (Final) R834796C005 (2013) R831697 (2013) R831697 (Final) R833864 (2011) |
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Bergen S, Szpiro AA. Mitigating the impact of measurement error when using penalized regression to model exposure in two-stage air pollution epidemiology studies. Environmental and Ecological Statistics 2015;22(3):601-631. |
R834796 (2014) R834796 (Final) R831697 (Final) |
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Bergen S, Sheppard L, Kaufman JD, Szpiro AA. Multipollutant measurement error in air pollution epidemiology studies arising from predicting exposures with penalized regression splines. Journal of the Royal Statistical Society Series C-Applied Statistics 2016;65(5):731-753. |
R834796 (Final) R831697 (Final) |
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Brower JB, Doyle-Eisele M, Moeller B, Stirdivant S, McDonald JD, Campen MJ. Metabolomic changes in murine serum following inhalation exposure to gasoline and diesel engine emissions. Inhalation Toxicology 2016;28(5):241-250. |
R834796 (2016) R834796 (Final) R834796C003 (2016) R834796C003 (Final) |
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Campen MJ, Lund A, Rosenfeld M. Mechanisms linking traffic-related air pollution and atherosclerosis. Current Opinion in Pulmonary Medicine 2012;18(2):155-160. |
R834796 (2012) R834796 (2013) R834796 (2015) R834796 (Final) R834796C003 (2012) R834796C003 (2013) R834796C003 (Final) R833990 (2010) R833990 (2011) |
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Campen M, Robertson S, Lund A, Lucero J, McDonald J. Engine exhaust particulate and gas phase contributions to vascular toxicity. Inhalation Toxicology 2014;26(6):353-360. |
R834796 (2014) R834796 (2015) R834796 (Final) R834796C003 (Final) |
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Chan SH, Van Hee VC, Bergen S, Szpiro AA, DeRoo LA, London SJ, Marshall JD, Kaufman JD, Sandler DP. Long-term air pollution exposure and blood pressure in the Sister Study. Environmental Health Perspectives 2015;123(10):951-958. |
R834796 (2015) R834796 (Final) R834796C005 (2015) R834796C005 (2016) R834796C005 (Final) R831697 (Final) |
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Chi GC, Liu Y, MacDonald JW, Barr RG, Donohue KM, Hensley MD, Hou L, McCall CE, Reynolds LM, Siscovick DS, Kaufman JD. Long-term outdoor air pollution and DNA methylation in circulating monocytes: results from the Multi-Ethnic Study of Atherosclerosis (MESA). Environmental Health 2016;15(1):119 (12 pp.). |
R834796 (2016) R834796 (Final) R834796C005 (2016) R834796C005 (Final) R831697 (Final) |
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Chi GC, Hajat A, Bird CE, Cullen MR, Griffin BA, Miller KA, Shih RA, Stefanick ML, Vedal S, Whitsel EA, Kaufman JD. Individual and neighborhood socioeconomic status and the association between air pollution and cardiovascular disease. Environmental Health Perspectives 2016;124(12):1840-1847. |
R834796 (Final) R834796C005 (Final) R831697 (Final) |
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Chi GC, Hajat A, Bird CE, Cullen MR, Griffin BA, Miller KA, Shih RA, Stefanick ML, Vedal S, Whitsel EA, Kaufman JD. Individual and neighborhood socioeconomic status and the association between air pollution and cardiovascular disease. Environmental Health Perspectives 2016; doi:10.1289/EHP199 (Epub ahead of print]. |
R834796C005 (2015) R834796C005 (2016) |
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Cosselman KE, Krishnan RM, Oron AP, Jansen K, Peretz A, Sullivan JH, Larson TV, Kaufman JD. Blood pressure response to controlled diesel exhaust exposure in human subjects. Hypertension 2012;59(5):943-948. |
R834796C004 (Final) R827355 (Final) R830954 (Final) |
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Cosselman KE, Navas-Acien A, Kaufman JD. Environmental factors in cardiovascular disease. Nature Reviews Cardiology 2015;12(11):627-642. |
R834796 (2015) R834796 (Final) R834796C004 (2015) R834796C004 (2016) R834796C004 (Final) |
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Erickson MH, Gueneron M, Jobson BT. Measuring long chain alkanes in diesel engine exhaust by thermal desorption PTR-MS. Atmospheric Measurement Techniques. 2014;7(1):225-239. |
R834796 (2013) R834796 (Final) R834796C001 (2013) |
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Erickson MH, Gueneron M, Jobson BT. Measuring long chain alkanes in diesel engine exhaust by thermal desorption PTR-MS. Atmospheric Measurement Techniques 2014;7(1):225-239. |
R834796 (2014) R834796 (2015) R834796C001 (2015) R834796C001 (Final) |
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Erickson MH, Gueneron M, Jobson BT. Measuring long chain alkanes in diesel engine exhaust by thermal desorption PTR-MS. Atmospheric Measurement Techniques. 2014;7(1):225-239. |
R834796 (2013) R834796 (Final) R834796C001 (2013) |
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Fann N, Kim S-Y, Olives C, Sheppard L. Estimated changes in life expectancy and adult mortality resulting from declining PM2.5 exposures in the contiguous United States:1980-2010. Environmental Health Perspectives 2017;125(9):097003 (8 pp.). |
R834796 (2016) R834796 (Final) R831697 (Final) |
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Fox JR, Cox DP, Drury BE, Gould TR, Kavanagh TJ, Paulsen MH, Sheppard L, Simpson CD, Stewart JA, Larson TV, Kaufman JD. Chemical characterization and in vitro toxicity of diesel exhaust particulate matter generated under varying conditions. Air Quality, Atmosphere & Health 2015;8(5):507-519. |
R834796 (2014) |
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Galaviz VE, Yost MG, Simpson CD, Camp JE, Paulsen MH, Elder JP, Hoffman L, Flores D, Quintana PJE. Traffic pollutant exposures experienced by pedestrians waiting to enter the U.S. at a major U.S.-Mexico border crossing. Atmospheric Environment 2014;88:362-369. |
R834796 (2014) R834796 (2015) R834796 (2016) R834796 (Final) R834796C001 (2015) R834796C001 (Final) |
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Galaviz VE, Quintana PJE, Yost MG, Sheppard L, Paulsen MH, Camp JE, Simpson CD. Urinary metabolites of 1-nitropyrene in US-Mexico border residents who frequently cross the San Ysidro Port of Entry. Journal of Exposure Science and Environmental Epidemiology 2017;27(1):84-89. |
R834796 (2016) R834796 (Final) R834796C001 (2016) R834796C001 (Final) |
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Gueneron M, Erickson MH, VanderSchelden GS, Jobson BT. PTR-MS fragmentation patterns of gasoline hydrocarbons. International Journal of Mass Spectrometry 2015;379:97-109. |
R834796 (2014) R834796 (2015) R834796 (Final) R834796C001 (2015) R834796C001 (Final) |
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Hazelhurst M, Dearborn L, Sherris A, Loftus C, Adgent M, Szpiro A, Ni Y, Day D, Kaufman J, Thakur N, Wright R, Sathyanarayana S, Carroll K, Moore P, Karr C. Long-term ozone exposure and lung function in middle childhood. ENVIRONMENTAL RESEARCH 2024;421(117632) |
R834796 (Final) R831697 (Final) R833741 (Final) |
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Hazlehurst MF, Spalt EW, Curl CL, Davey ME, Vedal S, Burke GL, Kaufman JD. Integrating data from multiple time-location measurement methods for use in exposure assessment: the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air). Journal of Exposure Science and Environmental Epidemiology 2017;27(6):569-574. |
R834796 (2016) R834796 (Final) R834796C005 (2016) R834796C005 (Final) R831697 (Final) |
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Hazlehurst MF, Spalt EW, Nicholas TP, Curl CL, Davey ME, Burke GL, Watson KE, Vedal S, Kaufman JD. Contribution of the in-vehicle microenvironment to individual ambient-source nitrogen dioxide exposure: the Multi-Ethnic Study of Atherosclerosis and Air Pollution. Journal of Exposure Science & Environmental Epidemiology 2018;28(4):371-380. |
R834796 (Final) R834796C005 (Final) R831697 (Final) |
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Herring CL, Faiola CL, Massoli P, Sueper D, Erickson MH, McDonald JD, Simpson CD, Yost MG, Jobson BT, VanReken TM. New methodology for quantifying polycyclic aromatic hydrocarbons (PAHs) using high-resolution aerosol mass spectrometry. Aerosol Science and Technology 2015;49(11):1131-1148. |
R834796 (2015) R834796 (Final) R834796C001 (2015) R834796C001 (Final) |
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Hooper LG, Young MT, Keller JP, Szpiro A, O’Brien K M, Sandler DP, Vedal S, Kaufman J, London S. Ambient air pollution exposure and chronic bronchitis in a cohort of U.S. women. Environmental Health Perspectives 2018;126(2):027005 (9 pp.). |
R834796 (Final) |
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Hudda N, Gould T, Hartin K, Larson TV, Fruin SA. Emissions from an international airport increase particle number concentrations 4-fold at 10 km downwind. Environmental Science & Technology 2014;48(12):6628-6635. |
R834796 (2014) R834796 (2015) R834796 (Final) R834796C001 (2015) R834796C001 (Final) |
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Jandarov RA, Sheppard LA, Sampson PD, Szpiro AA. A novel principal component analysis for spatially misaligned air pollution data. Journal of the Royal Statistical Society: Series C, Applied Statistics 2017,66(1):3-28. |
R834796 (Final) |
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Keller JP, Olives C, Kim S-Y, Sheppard L, Sampson PD, Szpiro AA, Oron AP, Lindstrom J, Vedal S, Kaufman JD. A unified spatiotemporal modeling approach for predicting concentrations of multiple air pollutants in the Multi-Ethnic Study of Atherosclerosis and Air Pollution. Environmental Health Perspectives 2015;123(4):301-309. |
R834796 (2014) R834796 (2015) R834796 (Final) R831697 (Final) |
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Keller JP, Drton M, Larson T, Kaufman JD, Sandler DP, Szpiro AA. Covariate-adaptive clustering of exposures for air pollution epidemiology cohorts. Annals of Applied Statistics 2017;11(1):93-113. |
R834796 (Final) R831697 (Final) |
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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. |
R834796 (2016) R834796 (Final) R834799 (2016) R834799 (Final) R834799C003 (Final) |
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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. |
R834796 (Final) R834799 (Final) |
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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. |
R834796 (2016) R834796 (Final) R834799 (2016) R834799 (Final) R834799C003 (Final) |
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Keller JP, Larson TV, Austin E, Barr RG, Sheppard L, Vedal S, Kaufman JD, Szpiro AA. Pollutant composition modification of the effect of air pollution on progression of coronary artery calcium:the Multi-Ethnic Study of Atherosclerosis. Environmental Epidemiology 2018;2:e024. |
R834796 (Final) R834796C005 (Final) R838300 (2018) R838300 (2020) |
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Kelp M, Gould T, Austin E, Marshall JD, Yost M, Simpson C, Larson T. Sensitivity analysis of area-wide, mobile source emission factors to high-emitter vehicles in Los Angeles. Atmospheric Environment 2020;223:117212 |
R834796 (Final) R835873 (2019) R835873 (Final) |
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Kim SY, Dutton SJ, Sheppard L, Hannigan MP, Miller SL, Milford JB, Peel JL, Vedal S. Erratum to: The short-term association of selected components of fine particulate matter and mortality in the Denver Aerosol Sources and Health (DASH) study. Environmental Health 2016;15(1):85. |
R834796 (Final) |
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Kim S-Y, Dutton SJ, Sheppard L, Hannigan MP, Miller SL, Milford JB, Peel JL, Vedal S. The short-term association of selected components of fine particulate matter and mortality in the Denver Aerosol Sources and Health (DASH) study. Environmental Health 2015;14:49 (11 pp.). |
R834796 (2014) R834796 (2015) R834796 (Final) |
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Kim S-Y, Sheppard L, Bergen S, Szpiro AA, Sampson PD, Kaufman JD, Vedal S. Prediction of fine particulate matter chemical components with a spatio-temporal model for the Multi-Ethnic Study of Atherosclerosis cohort. Journal of Exposure Science & Environmental Epidemiology 2016;26(5):520-528. |
R834796 (2016) R834796 (Final) R831697 (Final) |
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Kim S-Y, Olives C, Sheppard L, Sampson PD, Larson TV, Kaufman JD. Historical prediction modeling approach for estimating long-term concentrations of PM2.5 in cohort studies before 1999 implementation of widespread monitoring. Environmental Health Perspectives 2017;125(1):38-46. |
R834796 (2016) R834796 (Final) R831697 (Final) |
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Kim S-Y, Sheppard L, Kaufman JD, Bergen S, Szpiro AA, Larson TV, Adar SD, Diez Roux AV, Polak JF, Vedal S. Individual-level concentrations of fine particulate matter chemical components and subclinical atherosclerosis: a cross-sectional analysis based on 2 advanced exposure prediction models in the Multi-Ethnic Study of Atherosclerosis. American Journal of Epidemiology 2014;180(7):718-728. |
R834796 (2014) R834796 (2015) R834796 (Final) R831697 (Final) |
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Kim S-Y, Sheppard L, Larson TV, Kaufman JD, Vedal S. Combining PM2.5 component data from multiple sources: data consistency and characteristics relevant to epidemiological analyses of predicted long-term exposures. Environmental Health Perspectives 2015;123(7):651-658. |
R834796 (2014) R834796 (2015) R834796 (Final) R831697 (Final) |
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Kioumourtzoglou MA, Spiegelman D, Szpiro AA, Sheppard L, Kaufman JD, Yanosky JD, Williams R, Laden F, Hong B, Suh H. Exposure measurement error in PM2.5 health effects studies: a pooled analysis of eight personal exposure validation studies. Environmental Health 2014;13(1):2. |
R834796 (2014) |
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Larson T, Gould T, Riley EA, Austin E, Fintzi J, Sheppard L, Yost M, Simpson C. Ambient air quality measurements from a continuously moving mobile platform: estimation of area-wide, fuel-based, mobile source emission factors using absolute principal component scores. Atmospheric Environment 2017;152:201-211. |
R834796 (2016) R834796 (Final) R834796C001 (2016) R834796C001 (Final) |
Exit Exit Exit |
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Lee A, Szpiro A, Kim SY, Sheppard L. Impact of preferential sampling on exposure prediction and health effect inference in the context of air pollution epidemiology. Environmetrics 2015;26(4):255-267. |
R834796 (2015) R834796 (Final) |
Exit Exit |
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Lindstrom J, Szpiro AA, Sampson PD, Oron AP, Richards M, Larson TV, Sheppard L. A flexible spatio-temporal model for air pollution with spatial and spatio-temporal covariates. Environmental and Ecological Statistics 2014;21(3):411-433. |
R834796 (2013) R834796 (2014) R834796 (2015) R831697 (2013) R831697 (Final) |
Exit |
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Lucero J, Suwannasual U, Herbert L, McDonald J, Lund A. The role of the lectin-like oxLDL receptor (LOX-1) in traffic-generated air pollution exposure-mediated alteration of the brain microvasculature in Apolipoprotein (Apo) E knockout mice. INHALATION TOXICOLOGY 2017;29(6):266-281. |
R834796 (Final) |
Exit Exit |
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Lund AK, Doyle-Eisele M, Lin Y-H, Arashiro M, Surratt JD, Holmes T, Schilling KA, Seinfeld JH, Rohr AC, Knipping EM, McDonald, JD. The effects of α-pinene versus toluene-derived secondary organic aerosol exposure on the expression of markers associated with vascular disease. Inhalation Toxicology 2013;25(6):309-324. |
R834796 (2013) R834796 (2014) R834796 (2015) R834796 (Final) R834796C002 (2015) R834796C002 (Final) R834796C003 (2013) R833990 (2011) |
Exit Exit |
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Mauderly JL, Kracko D, Brower J, Doyle-Eisele M, McDonald JD, Lund AK, Seilkop SK. The National Environmental Respiratory Center (NERC) experiment in multi-pollutant air quality health research: IV. Vascular effects of repeated inhalation exposure to a mixture of five inorganic gases. Inhalation Toxicology 2014;26(11):691-696. |
R834796 (2014) R834796 (2015) R834796 (Final) R834796C002 (2015) R834796C002 (2016) R834796C002 (Final) |
Exit |
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McDonald JD, Chow JC, Peccia J, Liu Y, Chand R, Hidy GM, Mauderly JL. Influence of collection region and site type on the composition of paved road dust. Air Quality, Atmosphere and Health 2013;6(3):615-628. |
R834796 (2013) R834796 (2014) R834796 (2015) R834796 (Final) R834796C002 (2013) R834796C002 (2016) R834796C002 (Final) |
Exit Exit |
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Miller KA, Spalt EW, Gassett AJ, Curl CL, Larson TV, Avol E, Allen RW, Vedal S, Szpiro AA, Kaufman JD. Estimating ambient-origin PM2.5 exposure for epidemiology: observations, prediction, and validation using personal sampling in the Multi-Ethnic Study of Atherosclerosis. Journal of Exposure Science and Environmental Epidemiology 2019;29(2):227-237. |
R834796 (Final) R831697 (Final) R838300 (2018) R838300 (2020) |
Exit |
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Olives C, Sheppard L, Lindstrom J, Sampson PD, Kaufman JD, Szpiro AA. Reduced-rank spatio-temporal modeling of air pollution concentrations in the Multi-Ethnic Study of Atherosclerosis and Air Pollution. Annals of Applied Statistics 2014;8(4):2509-2537. |
R834796 (2014) R834796 (2015) R834796 (Final) R831697 (Final) |
Exit Exit |
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Oppenheim HA, Lucero J, Guyot A-C, Herbert LM, McDonald JD, Mabondzo A, Lund AK. Exposure to vehicle emissions results in altered blood brain barrier permeability and expression of matrix metalloproteinases and tight junction proteins in mice. Particle and Fibre Toxicology 2013;10:62. |
R834796 (2014) R834796 (2015) R834796 (Final) R834796C002 (2015) R834796C002 (2016) R834796C002 (Final) |
Exit Exit Exit |
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Paffett ML, Zychowski KE, Sheppard L, Robertson S, Weaver JM, Lucas SN, Campen MJ. Ozone inhalation impairs coronary artery dilation via intracellular oxidative stress: evidence for serum-borne factors as drivers of systemic toxicity. Toxicological Sciences 2015;146(2):244-253. |
R834796 (2014) R834796 (2015) R834796 (Final) R834796C003 (Final) |
Exit Exit Exit |
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Riley EA, Banks L, Fintzi J, Gould TR, Hartin K, Schaal L, Davey M, Sheppard L, Larson T, Yost MG, Simpson CD. Multi-pollutant mobile platform measurements of air pollutants adjacent to a major roadway. Atmospheric Environment 2014;98:492-499. |
R834796 (2014) R834796 (2015) R834796 (Final) R834796C001 (2015) R834796C001 (2016) R834796C001 (Final) |
Exit Exit Exit |
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Riley EA, Gould T, Hartin K, Fruin SA, Simpson CD, Yost MG, Larson T. Ultrafine particle size as a tracer for aircraft turbine emissions. Atmospheric Environment 2016;139:20-29. |
R834796 (2016) R834796 (Final) R834796C001 (2016) R834796C001 (Final) |
Exit Exit Exit |
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Riley EA, Schaal L, Sasakura M, Crampton R, Gould TR, Hartin K, Sheppard L, Larson T, Simpson CD, Yost MG. Correlations between short-term mobile monitoring and long-term passive sampler measurements of traffic-related air pollution. Atmospheric Environment 2016;132:229-239. |
R834796 (2016) R834796 (Final) R834796C001 (2016) R834796C001 (Final) |
Exit Exit Exit |
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Robertson S, Colombo ES, Lucas SN, Hall PR, Febbraio M, Paffett ML, Campen MJ. CD36 mediates endothelial dysfunction downstream of circulating factors induced by O3 exposure. Toxicological Sciences 2013;134(2):304-311. |
R834796 (2013) R834796 (2014) R834796 (2015) R834796 (Final) R834796C003 (2013) R834796C003 (2016) R834796C003 (Final) R833990 (2011) R833990 (Final) |
Exit Exit Exit |
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Sampson PD, Richards M, Szpiro AA, Bergen S, Sheppard L, Larson TV, Kaufman JD. A regionalized national universal kriging model using Partial Least Squares regression for estimating annual PM2.5 concentrations in epidemiology. Atmospheric Environment 2013;75:383-392. |
R834796 (2013) R834796 (2014) R834796 (2015) R831697 (2013) R831697 (Final) R833864 (2012) R833864 (2013) R833864 (Final) |
Exit Exit Exit |
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Schisler JC, Ronnebaum SM, Madden M, Channell M, Campen M, Willis MS. Endothelial inflammatory transcriptional responses to an altered plasma exposome following inhalation of diesel emissions. Inhalation Toxicology 2015;27(5):272-280. |
R834796 (2015) R834796 (Final) R834796C003 (Final) |
Exit Exit |
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Schisler J, Campen MJ, Madden M, and Willis MS. Transcriptional Endothelial Biosensor Response to Diesel-Induced Plasma Compositional Changes. Inhalation Toxicology. 2015, 27(5):272–280. |
R834796C003 (2016) |
not available |
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Sheppard L, Burnett RT, Szpiro AA, Kim S-Y, Jerrett M, Pope III CA, Brunekreef B. Confounding and exposure measurement error in air pollution epidemiology. Air Quality, Atmosphere & Health 2012;5(2):203-216. |
R834796 (2012) R834796 (2013) R834796 (2015) R834796 (Final) R831697 (2013) R831697 (Final) |
Exit Exit |
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Spalt EW, Curl CL, Allen RW, Cohen M, Williams K, Hirsh JA, Adar SD, Kaufman JD. Factors influencing time-location patterns and their impact on estimates of exposure: the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air). Journal of Exposure Science & Environmental Epidemiology 2016;26(4):341-348. |
R834796 (2014) R834796 (2015) R834796 (Final) R834796C005 (2015) R834796C005 (2016) R834796C005 (Final) R831697 (Final) |
Exit Exit Exit |
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Spalt EW, Curl CL, Allen RW, Cohen M, Adar SD, Stukovsky KH, Avol E, Castro-Diehl C, Nunn C, Mancera-Cuevas K, Kaufman JD. Time-location patterns of a diverse population of older adults:the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air). Journal of Exposure Science & Environmental Epidemiology 2016;26(4):349-355. |
R834796 (2014) R834796 (2015) R834796 (Final) R834796C005 (2015) R834796C005 (2016) R834796C005 (Final) R831697 (Final) |
Exit Exit |
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Sun M, Kaufman JD, Kim S-Y, Larson TV, Gould TR, Polak JF, Budoff MJ, Diez Roux AV, Vedal S. Particulate matter components and subclinical atherosclerosis:common approaches to estimating exposure in a Multi-Ethnic Study of Atherosclerosis cross-sectional study. Environmental Health 2013;12:39. |
R834796 (2013) R834796 (2014) R834796 (2015) R834796 (Final) R834796C005 (2013) R834796C005 (2015) R834796C005 (2016) R834796C005 (Final) R831697 (2013) R831697 (Final) |
Exit Exit |
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Suwannasual U, Lucero J, McDonald JD, Lund AK. Exposure to traffic-generated air pollutants mediates alterations in brain microvascular integrity in wildtype mice on a high-fat diet. Environmental Research 2018;160:449-461. |
R834796 (Final) |
Exit Exit Exit |
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Szpiro AA, Sheppard L, Lumley T. Efficient measurement error correction with spatially misaligned data. Biostatistics 2011;12(4):610-623. |
R834796 (2012) R834796 (2013) R834796 (2014) R834796 (2015) R834796 (Final) R831697 (2013) R831697 (Final) |
Exit Exit Exit |
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Szpiro AA, Paciorek CJ, Sheppard L. Does more accurate exposure prediction necessarily improve health effect estimates? Epidemiology 2011;22(5):680-685. |
R834796 (2012) R834796 (2013) R834796 (2014) R834796 (2015) R834796 (Final) R831697 (2013) R831697 (Final) |
Exit Exit Exit |
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Szpiro AA, Paciorek CJ. Measurement error in two-stage analyses, with application to air pollution epidemiology. Environmetrics 2013;24(8):501-517. |
R834796 (2013) R834796 (2014) R834796 (2015) R834796 (Final) R831697 (2013) R831697 (Final) |
Exit |
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Szpiro AA, Sheppard L, Adar SD, Kaufman JD. Estimating acute air pollution health effects from cohort study data. Biometrics 2014;70(1):164-174. |
R834796 (2013) R834796 (2014) R834796 (2015) R834796 (Final) R834796C005 (2013) R834796C005 (2015) R834796C005 (2016) R834796C005 (Final) R831697 (2013) R831697 (Final) |
Exit |
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Tessum MW, Larson T, Gould TR, Simpson CD, Yost MG, Vedal S. Mobile and fixed-site measurements to identify spatial distributions of traffic-related pollution sources in Los Angeles. Environmental Science & Technology 2018;52(5):2844-2853. |
R834796 (Final) R834796C001 (Final) |
Exit Exit Exit |
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Tyler CR, Zychowski KE, Sanchez BN, Rivero V, Lucas S, Herbert G, Liu J, Irshad H, McDonald JD, Bleske BE, Campen MJ. Surface area-dependence of gas-particle interactions influences pulmonary and neuroinflammatory outcomes. Particle and Fibre Toxicology 2016;13(1):64 (18 pp.). |
R834796 (2016) R834796 (Final) R834796C003 (Final) |
Exit Exit |
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Vedal S, Kaufman JD. What does multi-pollutant air pollution research mean? American Journal of Respiratory and Critical Care Medicine 2011;183(1):4-6. |
R834796 (2012) R834796 (2013) R834796 (2014) R834796 (Final) R834796C005 (2013) R834796C005 (2016) R834796C005 (Final) |
Exit Exit Exit |
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Wang M, Keller JP, Adar SD, Kim S-Y, Larson TV, Olives C, Sampson PD, Sheppard L, Szpiro AA, Vedal S, Kaufman JD. Development of long-term spatiotemporal models for ambient ozone in six metropolitan regions of the United States: the MESA Air Study. Atmospheric Environment 2015;123(A):79-87. |
R834796 (2016) R834796 (Final) R831697 (Final) R833741 (Final) |
Exit Exit Exit |
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Wang M, Brunekreef B, Gehring U, Szpiro A, Hoek G, Beelen R. A new technique for evaluating land-use regression models and their impact on health effect estimates. Epidemiology 2016;27(1):51-56. |
R834796 (2015) R834796 (Final) |
Exit |
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Wang M, Sampson PD, Hu J, Kleeman M, Keller JP, Olives C, Szpiro AA, Vedal S, Kaufman JD. Combining land-use regression and chemical transport modeling in a spatiotemporal geostatistical model for ozone and PM2.5. Environmental Science & Technology 2016;50(10):5111-5118. |
R834796 (2016) R834796 (Final) R831697 (Final) R833741 (Final) R833864 (Final) |
Exit Exit Exit |
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Weuve J, Kaufman JD, Szpiro AA, Curl C, Puett RC, Beck T, Evans DA, Mendes de Leon CF. Exposure to traffic-related air pollution in relation to progression in physical disability among older adults. Environmental Health Perspectives 2016;124(7):1000-1008. |
R834796 (Final) R834796C005 (2016) R834796C005 (Final) R831697 (Final) |
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Xu W, Riley EA, Austin E, Sasakura M, Schaal L, Gould TR, Hartin K, Simpson CD, Sampson PD, Yost MG, Larson TV, Xiu G, Vedal S. Use of mobile and passive badge air monitoring data for NOx and ozone air pollution spatial exposure prediction models. Journal of Exposure Science and Environmental Epidemiology 2017;27(2):184-192. |
R834796 (Final) R834796C001 (2015) R834796C001 (2016) R834796C001 (Final) |
Exit Exit |
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Yin F, Lawal A, Ricks J, Fox JR, Larson T, Navab M, Fogelman AM, Rosenfeld ME, Araujo JA. Diesel exhaust induces systemic lipid peroxidation and development of dysfunctional pro-oxidant and pro-inflammatory high-density lipoprotein. Arteriosclerosis, Thrombosis, and Vascular Biology 2013;33(6):1153-1161. |
R834796 (2013) R834796 (2014) R834796 (2015) R834796 (Final) R834796C003 (2013) R834796C003 (2016) R834796C003 (Final) |
Exit Exit Exit |
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Young MT, Sandler DP, DeRoo LA, Vedal S, Kaufman JD, London SJ. Ambient air pollution exposure and incident adult asthma in a nationwide cohort of U.S. women. American Journal of Respiratory and Critical Care Medicine 2014;190(8):914-921. |
R834796 (2015) R834796 (Final) R834796C005 (2015) R834796C005 (2016) R834796C005 (Final) R831697 (Final) |
Exit Exit Exit |
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Young M, Jansen K, Cosselman K, Gould T, Stewart J, Larson T, Sack C, Vedal S, Szpiro A, Kaufman J. Blood Pressure Effect of Traffic-Related Air Pollution A Crossover Trial of In-Vehicle Filtration. ANNALS OF INTERNAL MEDICINE 2023;. |
R834796 (Final) |
Exit |
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Zychowski KE, Lucas SN, Sanchez B, Herbert G, Campen MJ. Hypoxia-induced pulmonary arterial hypertension augments lung injury and airway reactivity caused by ozone exposure. Toxicology and Applied Pharmacology 2016;305:40-45. |
R834796 (2016) R834796 (Final) |
Exit Exit Exit |
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Wang M, Sampson PD, Sheppard LE, Stein JH, Vedal S, Kaufman JD. Long-term exposure to ambient ozone and progression of subclinical arterial disease:the multi-ethnic study of atherosclerosis and air pollution. Environmental Health Perspectives 2019;127(5):057001. |
R834796 (Final) R838300 (2019) R838300 (2020) |
Exit |
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Herring CL, Faiola CL, Massoli P, Sueper D, Erickson MH, McDonald JD, Simpson CD, Yost MG, Jobson BT, VanReken TM:New Methodology for Quantifying Polycyclic Aromatic Hydrocarbons (PAHs) Using High-Resolution Aerosol Mass Spectrometry. Aerosol Science and Technology. 2015, 49(11):1131-1148. |
R834796C001 (2016) |
not available |
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Peroxidation and Development of Dysfunctional Pro-Oxidant and Pro-Inflammatory High-Density Lipoprotein. Arterioscler Thromb Vasc Biol. 2013, 33(6):1153-61. |
R834796C003 (2016) |
not available |
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Galaviz V, Yost M, Simpson C, Camp J, Paulsen M, Elder J, Hoffman L, Flores D, Quintana P:Traffic pollutant exposures experienced by pedestrians waiting to enter the US at a major USMexico border crossing. Atmospheric Environment. 2014, 88:362-369. |
R834796C001 (2016) |
not available |
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Erickson M, Gueneron M, Jobson B:Measuring long chain alkanes in diesel engine exhaust by thermal desorption PTR-MS. Atmospheric Measurement Techniques. 2014, 7(1):225-239. |
R834796C001 (2016) |
not available |
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Aragon MJ, Chrobak I, Brower J, Roldan L, Fredenburgh LE, McDonald JD, Campen MJ:Inflammatory and Vasoactive Effects of Serum Following Inhalation of Varied Complex Mixtures. Cardiovascular toxicology. 2016, 16(2):163-171. |
R834796C003 (2016) |
not available |
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Campen MJ, Lund A, Rosenfeld M:Mechanisms linking traffic-related air pollution and atherosclerosis. Current opinion in pulmonary medicine. 2012, 18(2):155. |
R834796C003 (2016) |
not available |
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Hudda N, Gould T, Hartin K, Larson TV, Fruin SA:Emissions from an international airport increase particle number concentrations 4-fold at 10 km downwind. Environmental science & technology. 2014, 48(12):6628-6635. |
R834796C001 (2016) |
not available |
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Campen M, Robertson S, Lund A, Lucero J, McDonald J:Engine exhaust particulate and gas phase contributions to vascular toxicity. Inhalation toxicology. 2014, 26(6):353-360. |
R834796C003 (2016) |
not available |
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Gueneron M, Erickson MH, VanderSchelden GS, Jobson BT:PTR-MS fragmentation patterns of gasoline hydrocarbons. International Journal of Mass Spectrometry. 2015, 379:97-109. |
R834796C001 (2016) |
not available |
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Paffett ML, Sheppard L, Robertson S, Weaver J, Lucas SN, Campen MJ. Ozone inhalation enhances coronary artery constriction and impairs dilation via superoxide-dependent mechanisms. Toxicol Appl Pharmacol. 2015, In press. |
R834796C003 (2016) |
not available |
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Lund AK, Doyle-Eisele M, Lin Y-H, Arashiro M, Surratt JD, Holmes T, Schilling KA, Seinfeld JH, Rohr AC, Knipping EM, McDonald, JD. The Effects of α-Pinene-vs. Toluene-Derived Secondary Organic Aerosol Exposure on the Expression of Markers Associated with Vascular Disease. Inhalation Toxicology. 2013, 25(6):309-324. |
R834796C002 (2016) |
not available |
Supplemental Keywords:
Environmental policy, exposure modeling, epidemiologic inference, health effects, air pollution exposure, atherosclerosis, epidemiology, toxicology, transportation;, Scientific Discipline, Health, Health Risk Assessment, Risk Assessments, Environmental Monitoring, Biochemistry, Atmospheric Sciences, particulate matter, airway disease, bioavailability, air pollution, particle exposure, ambient particle health effects, vascular dysfunction, cardiotoxicityRelevant Websites:
UW Center for Clean Air Research (CCAR) | University of Washington, DEOHS ExitProgress 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).
R834796C001 Exposure Mapping – Characterization of Gases and Particles for ExposureAssessment in Health Effects and Laboratory Studies
R834796C002 Simulated Roadway Exposure Atmospheres for Laboratory Animal and Human Studies
R834796C003 Cardiovascular Consequences of Immune Modification by Traffic-Related Emissions
R834796C004 Vascular Response to Traffic-Derived Inhalation in Humans
R834796C005 Effects of Long-Term Exposure to Traffic-Derived Particles and Gases on Subclinical Measures of Cardiovascular Disease in a Multi-Ethnic Cohort
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
- Final Report
- 2016 Progress Report
- 2015 Progress Report
- 2014 Progress Report
- 2013 Progress Report
- 2011 Progress Report
- Original Abstract
92 journal articles for this center