Final Report: Exposure Mapping – Characterization of Gases and Particles for ExposureAssessment in Health Effects and Laboratory Studies

EPA Grant Number: R834796C001
Subproject: this is subproject number 001 , established and managed by the Center Director under grant R834796
(EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).

Center: University of Washington Center for Clean Air Research
Center Director: Vedal, Sverre
Title: Exposure Mapping – Characterization of Gases and Particles for ExposureAssessment in Health Effects and Laboratory Studies
Investigators: Yost, Michael , Jobson, B. Thomas , Larson, Timothy V. , Simpson, Chris , VanReken, Timothy M.
Institution: University of Washington , Washington State University
EPA Project Officer: Callan, Richard
Project Period: December 1, 2010 through November 30, 2015 (Extended to November 30, 2017)
RFA: Clean Air Research Centers (2009) RFA Text |  Recipients Lists
Research Category: Air Quality and Air Toxics , Air

Objective:

Roadway-source air pollutants encompass a diverse range of constituents and chemicals, including both particulate and gas phase components, which are transformed by chemical and physical reactions as they age in the environment. Consequently, human exposures to air pollutants can range from relatively unaged aerosols to highly aged components that vary with respect to particle size and the chemical composition of particle and gas phase components. To obtain a more comprehensive understanding of the seasonal and spatial variability in the concentration and composition of air pollutant exposures within Multi-Ethnic Study of Atherosclerosis Air (MESA-Air) Study cities, we employ mobile and fixed site monitoring to assess both gas and particle components of these pollutants as they age from roadway sources to population areas.

The main project aims and objectives were—

  1. Characterize spatial and temporal gradients of selected air pollutants along roadways and within neighborhoods in MESA cities using a mobile platform.
  2. Measure spatial variation in concentrations of selected air pollutants at 2-week average stationary sites in coordination with the mobile measurements.
  3. Characterize aging of air pollutant components as they are transported from roadway sources to neighborhood receptor locations.
  4. Provide detailed characterization of laboratory exposure conditions available for toxicology testing, and identify likely conditions that mimic those found in urban settings.

 

Summary/Accomplishments (Outputs/Outcomes):

Field studies

A series of field sampling campaigns were conducted to address aims 1 through 3 of this study. Field sampling in four cities in the MESA-Air cohort was completed: Minneapolis/St. Paul, MN; Baltimore, MD; Los Angeles, CA; and Winston-Salem, NC. Due to financial constraints, only passive sampling was deployed in Winston-Salem. Both mobile monitoring and passive sampling measurements were conducted for both heating and nonheating seasons in all other cities.  In addition, a collaborative measurement campaign was conducted in Atlanta, GA, with the Southeastern Center for Air Pollution & Epidemiology (SCAPE Center) that provided data described in the Collaborative Projects section.

The instrument platform for mobile monitoring was assembled and tested in Seattle, WA, beginning in October 2011. During each 2-week sampling period the mobile monitoring platform measures concentrations of particles and gases while continuously on the move along a fixed sampling route with position information simultaneously logged by a real time GPS. Data collection includes the following components: optical particle size in 31 size bins from 10 to 0.2 µm, particle mean diameter and particle counts from 0.03 to 0.2 µm, total particle count >0.1 µm, particle light scattering coefficient, particle light absorption (black carbon), NO/NO2, O3, CO, CO2 and total VOCs.

Pre-planned driving routes were created for each city, arranged into three sectors with 14 measurement intersection waypoints in each sector for measurement, plus a common central reference site. These 43 waypoints were selected in advance, based on a set of route criteria developed in consultation with the Biostatistics Core of the center. The routes were evaluated by the Biostatistics Core for use in the spatial mapping of exposures performed later in the study.  Based on advice from our advisory committee, we also developed a more intensive “roadway gradient” sampling scheme, which modified one of the waypoints near a roadway to capture local gradients in pollutants. This gradient sampling scheme was pilot tested during our field visit to Albuquerque, NM. Similar gradient samples were collected in all cities where mobile monitoring was conducted. A paper describing this gradient sampling work, titled “Multi-pollutant mobile platform measurements of air pollutants adjacent to the I-40 corridor in Albuquerque, NM,” was published in Atmospheric Environment (Riley 2014).  

Next, AERMOD was used to evaluate the dispersion condition near the roadway during the specific days and times that mobile sampling was done.  Two major dispersion conditions were identified: a dominant north-side dispersion pattern with winds coming from the south and a symmetric dispersion condition during more stagnant conditions. Three sampling days corresponded to the dominant north-side pattern, and 4 days corresponded to the symmetric pattern. The data for black carbon (absorbance) and Ozone quite clearly show that the instruments capture the near roadway gradient and illustrate the effect of dispersion conditions on the shape of the gradient.  The mobile sampling also clearly captures the near road deficit in Ozone which is likely due to NO/NOx scavenging. 

Similar patterns in Ozone and NO/NOx have been observed in larger scale sampling with both our passive samplers and mobile platform in the other cities. Note that the mobile sampling data are collected only during the evening commute, while the passive badges collect continuously over the 2-week period. Since the mobile platform is often collected during peak traffic and Ozone periods, it may more clearly capture these near-roadway effects showing an interaction of the multipollutants. Additional comparisons of the data after final QC were made with reference monitors in Baltimore. The mobile data has excellent agreement with AQS site and captures the day-to-day variation in these pollutants.

Multivariate analysis of the mobile platform data was done using pilot measurements in Seattle. Traditional principal component analysis (PCA) with varimax rotation was examined, and the resultant factor scores were compared with a photographic record using an onboard camera. 

The results indicate that there are strong latent variables that are logically related to specific roadway sources. These features also are observed in our MESA cities data.

We have used a larger data set spanning more days in this same Seattle area to deduce the fuel-based emission factors for both light- and heavy-duty vehicles. The traditional fuel-based analysis relies on departures of concurrent CO2 values above local background that others have used in both vehicle chase studies and tunnel studies. Our method uses an unsupervised approach that does not require prior identification of the vehicle or vehicles of interest. It is therefore not constrained spatially (Larson, et al., 2017).  A table of the derived average emission factors and a map of the their spatial distributions was prepared.

We also have employed a factor analysis of mobile monitoring data taken in Baltimore and Los Angeles in order to help elucidate the TRAP emission impacts and their spatial distribution.  

Characterization of laboratory exposure conditions

In pursuance of Objective 4, detailed chemical characterization measurements were made of the controlled exposure atmospheres at the Lovelace Respiratory Research Institute (LRRI) (see project #3) in May 2012. Over the course of 3 weeks, nearly 50 distinct exposure atmospheres were sampled. The majority of these test atmospheres were composed of unaged gasoline and diesel exhaust at various loadings and degrees of mixing; a few atmospheres also were sampled where the emissions were photochemically aged prior to sampling. All test atmospheres were sampled by the same instrument platform used for the mobile sampling.

Our Washington State University (WSU) collaborators sampled the test atmospheres with a high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) and a proton transfer reaction mass spectrometer (PTR-MS). The PTR-MS was coupled with a thermal desorption system for analyzing organic compounds with intermediate volatility (IVOCs). The HR-AMS and PTR-MS provided a much more detailed characterization of the particle- and gas-phase organic composition of the test atmospheres, which will yield improved understanding of the chemical characteristics and phase partitioning behavior of exhaust mixtures. Preliminary results from the experiments at LRRI were presented at the Clean Air Research Centers (CLARC) annual meeting, and a manuscript (Gueneron 2015 #4) was published describing the analysis of thermal desorption PTR-MS sampling of engine exhausts and fuels.

Detailed analysis of the aerosol mass spectrometer data utilized two types of data from the HR-ToF-AMS. Unit Mass Resolution (UMR) data and the more highly resolved High-Resolution (HR) data. The UMR data collapses mass spectral signals into their respective unit masses and uses a fragmentation algorithm to allocate signals at a given UMR between Organic, Nitrate, Sulfate, Ammonium, and Chloride species contributions. The fragmentation algorithm is standard practice within the AMS community and has been corrected using filter data to account for non-ambient conditions observed in the engine exhaust experiments. HR analysis provides a more robust identification of individual ions and thus a direct quantification of contributions between the five main classifications (Organic, Nitrate, Sulfate, Ammonium, and Chloride).

WSU analysis has focused on the composition of the controlled mixtures of diesel and gasoline exhaust generated at the LRRI exposure facility. The test atmospheres were found to contain strong signals from polycyclic aromatic hydrocarbons (PAHs), and we developed a new analytical procedure to examine the contributions of individual PAH compounds to the aerosol under varying test conditions. This procedure, called PAHs by Molecular Ion Proxy (P-MIP), relies on the fact that PAHs are relatively resistant to fragmentation from electron impact ionization, and thus that significant signal remains at the molecular ion.  After quantifying the molecular ion signal and taking into account potential interferences, the contributions of the parent PAH to the aerosol may be inferred. Using the dataset from LRRI, we identified and quantified the molecular ions associated with 53 PAH species, including both un-substituted and functionalized species. For this data set, the observed interferences typically were less than 1.2 percent of the observed signal. This analysis technique should have broad applicability, particularly once follow-up work establishing standard HR-AMS spectra for PAH compounds is complete. In the LRRI chamber data, we found that the fractional PAH molecular ion signal remained stable despite dramatic temporal variability of the total particulate organic signal, and that the fractional contributions of grouped PAH species and even individual PAH ions were remarkably consistent across experiments. The distribution of PAHs showed no apparent dependence on engine load or exhaust type. Comparison of particle-phase PAH concentrations against gas-phase PAH concentrations for four species suggests a strong enhancement of the particle-phase over what is predicted by absorptive partitioning theory. This work appeared in a publication in Aerosol Science & Technology (Herring, et al., 2015).

Laboratory work on characterizing the PTR-MS sampling of IVOCs was done to determine the potential for positive interferences from n-aldehydes present in diesel exhaust on the measurement of naphthalene and alkyl substituted naphthalenes. This interference has bearing on the interpretation of the gas-particle partitioning analysis using the combined PTR-MS and AMS data sets. Laboratory tests were conducted to establish product ions produced from H3O+ reaction with aldehydes as a function of drift field strength. Laboratory test were conducted to evaluate NO+ as a reagent ion to more effectively distinguish between aldehydes, alkanes, and substituted naphthalene compounds.

Diesel exhaust was sampled using NO+ to contrast information content of the mass spectrum against that obtained with H3O+.  It was determined that using NO+ in IVOC mode would produce a more interpretable mass spectrum.  These results are currently being written up as a manuscript to be submitted for publication.

Conclusions:

CCAR Project 1 collected a unique set of real-time multipollutant monitoring data, which has resulted in a better understanding of spatial gradients along roadways. Laboratory analyses of controlled mixtures demonstrated the importance of PAHs in mixtures containing gasoline or diesel. These data and results helped enhance and inform the other CCAR projects.

 

References:

  1. Gueneron M, Erickson MH, VanderSchelden GS, Jobson BT. PTR-MS fragmentation patterns of gasoline hydrocarbons. International Journal of Mass Spectrometry 2015;379:97-109. 
  2. 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.
  3. Larson T, Gould TR, Riley EA, Austin E, Fintzi J, Sheppard L, Yost MG, Simpson CD. 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.
  4. May AA, Nguyen NT, Presto AA, Gordon TD, Lipsky EM, Karve M, Gutierrez A, Robertson WH, Zhang M, Brandow C, Chang O. Gas-and particle-phase primary emissions from in-use, on-road gasoline and diesel vehicles. Atmospheric Environment 2014;88:247-60.
  5. 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 2016a;132:229-239.
  6. 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 2016b;139:20-29. 
  7. 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 the I-40 corridor in Albuquerque, NM. Atmospheric Environment 2014;98:492-499. 
  8. Tessum M, Larson TV, Gould TR, Simpson C, Yost M, 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.


Journal Articles on this Report : 12 Displayed | Download in RIS Format

Other subproject views: All 43 publications 18 publications in selected types All 18 journal articles
Other center views: All 187 publications 87 publications in selected types All 86 journal articles
Type Citation Sub Project Document Sources
Journal Article 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)
  • Full-text: Atmospheric Measurement Techniques-Full Text PDF
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  • Abstract: Atmospheric Measurement Techniques-Abstract
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  • Other: Harvard University-Abstract
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  • Journal Article 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)
  • Full-text: ScienceDirect-Full Text HTML
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  • Abstract: ScienceDirect-Abstract
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  • Other: ScienceDirect-Full Text PDF
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  • Journal Article 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)
  • Abstract from PubMed
  • Abstract: JESEE-Abstract
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  • Other: ResearchGate-Abstract
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  • Journal Article 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)
  • Abstract: ScienceDirect-Abstract
    Exit
  • Other: ResearchGate-Abstract
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  • Journal Article 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)
  • Full-text: Taylor & Francis-Full Text HTML
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  • Abstract: Taylor & Francis-Abstract
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  • Other: Taylor & Francis-Full Text PDF
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  • Journal Article 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)
  • Full-text from PubMed
  • Abstract from PubMed
  • Associated PubMed link
  • Full-text: ACS-Full Text HTML
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  • Abstract: ACS-Abstract
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  • Other: ACS-Full Text PDF
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  • Journal Article 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)
  • Full-text: Science Direct-Full Text HTML
    Exit
  • Abstract: Science Direct-Abstract
    Exit
  • Other: Science Direct-Full Text PDF
    Exit
  • Journal Article 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)
  • Full-text from PubMed
  • Abstract from PubMed
  • Associated PubMed link
  • Full-text: ScienceDirect-Full Text HTML
    Exit
  • Abstract: ScienceDirect-Abstract
    Exit
  • Other: ScienceDirect-Full Text PDF
    Exit
  • Journal Article 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)
  • Full-text from PubMed
  • Abstract from PubMed
  • Associated PubMed link
  • Full-text: Science Direct-Full Text HTML
    Exit
  • Abstract: Science Direct-Abstract
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  • Other: Science Direct-Full Text PDF
    Exit
  • Journal Article 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)
  • Full-text from PubMed
  • Abstract from PubMed
  • Associated PubMed link
  • Full-text: Science Direct-Full Text HTML
    Exit
  • Abstract: Science Direct-Abstract
    Exit
  • Other: Science Direct-Full Text PDF
    Exit
  • Journal Article 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)
  • Abstract from PubMed
  • Full-text: ACS-Full Text HTML
    Exit
  • Abstract: ACS-Abstract
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  • Other: ACS-Full Text PDF
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  • Journal Article 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)
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  • Abstract: Nature-Abstract
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  • Other: Ovid-Abstract
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  • Supplemental Keywords:

    Exposure science, community exposures, chemical transport, mobile monitoring  , Health, Scientific Discipline, Air, ENVIRONMENTAL MANAGEMENT, Air Quality, air toxics, Health Risk Assessment, Risk Assessments, mobile sources, Biochemistry, Environmental Monitoring, Atmospheric Sciences, Risk Assessment, ambient air quality, atmospheric particulate matter, particulate matter, aerosol particles, air pollutants, motor vehicle emissions, vehicle emissions, air quality models, motor vehicle exhaust, airway disease, bioavailability, air pollution, particle exposure, atmospheric aerosols, ambient particle health effects, vascular dysfunction, cardiotoxicity, atmospheric chemistry, exposure assessment

    Relevant Websites:

    http://depts.washington.edu/uwccar/ Exit

    Progress and Final Reports:

    Original Abstract
  • 2011 Progress Report
  • 2012 Progress Report
  • 2013 Progress Report
  • 2014
  • 2015 Progress Report
  • 2016 Progress Report

  • Main Center Abstract and Reports:

    R834796    University of Washington Center for Clean Air Research

    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