Synthesizing Scientific Progress: Outcomes from U.S. EPA's

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Policy Analysis

Synthesizing Scientific Progress: Outcomes from US EPA’s Carbonaceous Aerosols and Source Apportionment STAR Grants Kristina M Wagstrom, Kirk R Baker, Alan E Leinbach, and Sherri W Hunt Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/es500782k • Publication Date (Web): 11 Aug 2014 Downloaded from http://pubs.acs.org on August 13, 2014

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Synthesizing Scientific Progress: Outcomes from US EPA’s Carbonaceous Aerosols and Source

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Apportionment STAR Grants

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Kristina M. Wagstrom1,2, Kirk R. Baker3, Alan E. Leinbach4, Sherri W. Hunt4

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Chemical and Biomolecular Engineering, University of Connecticut, Storrs, CT AAAS Science & Technology Policy Fellow hosted by the U.S. Environmental Protection Agency Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency National Center for Environmental Research, U.S. Environmental Protection Agency

*Sherri W. Hunt, 703.347.8042, [email protected]

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ABSTRACT

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In response to recommendations by the National Research Council in the late 1990s and early 2000s for

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critical research into understanding sources and formation mechanisms of PM2.5, EPA created multiple

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funding opportunities through the Science to Achieve Results (STAR) program: “Measurement,

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Modeling, and Analysis Methods for Airborne Carbonaceous Fine Particulate Matter” (2003) and

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“Source Apportionment of Particulate Matter” (2004). The carbonaceous fine PM solicitation resulted in

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16 different projects focusing on the measurement methods, source identification, and exploration of

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the chemical and physical processes important for PM2.5 carbon in the atmosphere. The source

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apportionment funding opportunity led to 11 projects improving tools and characterization of source-

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receptor relationships of PM2.5. Many funding mechanisms include a final synopsis of funded research

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and published manuscripts. Here, this evaluation is extended to include citations of research published

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as part of these solicitations. These solicitations resulted in 275 publications that included more than

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850 unique authors in 37 different journals with a weighted average 2011 impact factor of 4.21. At the


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time of this assessment, these publications have been cited by 13,612 peer review journal articles with

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31 (11%) of the manuscripts being cited over 100 times.

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INTRODUCTION

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Negative health effects in humans from exposure to ozone and particulate matter (PM) less than 2.5 µm

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in diameter (PM2.5) are well documented.1–4 Beginning in 1987, the PM National Ambient Air Quality

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Standard (NAAQS) was based on PM10 (particles with diameters < 10 µm) mass. In 1997, a second PM

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NAAQS based on fine PM or PM2.5 mass was adopted to specifically address the smaller particle sizes

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which can penetrate deeper into the lungs. In light of the new standard, the National Research Council

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carried out a series of four studies aimed at identifying and recommending research priorities for the

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U.S. Environmental Protection Agency (EPA).5–8 Two of the recommendations from the second report

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were:

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“Research Topic 3. Characterization of Emissions Sources. What are the size

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distribution, chemical composition, and mass-emission rates of particulate matter

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emitted from the collection of primary-particle sources in the United States, and what

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are the emissions of reactive gases that lead to secondary particulate formation through

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atmospheric chemical reactions?” 6

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“Research Topic 4. Air-Quality Model Development and Testing. What are the linkages

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between emission sources and ambient concentrations of the biologically important

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components of particulate matter?” 6

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One part of EPA’s response was the creation of two funding opportunities through the Science to

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Achieve Results (STAR) extramural research funding program: Measurement, Modeling and Analysis



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Methods for Airborne Carbonaceous Fine Particulate Matter (PM2.5) (released in 2003) 9 and Source

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Apportionment of Particulate Matter (released in 2004).10

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A total of 27 projects were funded under these two solicitations.9,10 The 2003 solicitation on

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carbonaceous PM included 16 projects funded for a total of $6.6 M aimed to improve the understanding

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of the sources, reactions, and physical processes impacting fine carbonaceous particulate matter

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concentrations (including both elemental and organic carbon species). It focused on supporting projects

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to evaluate and improve measurement methods, improve methods to identify and distinguish sources,

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and improve the ability to model carbonaceous species.9 The goal of the 2004 solicitation on source

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apportionment of PM was to advance the understanding of source-receptor relationships associated

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with both current and future sources of PM and included 11 projects funded with $4.6M.10

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A unique aspect of the EPA STAR program is the inclusion of several principle investigator meetings

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designed to allow the exchange of ideas and results between investigators on different grants within the

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same program and also researchers and policy makers. These meetings typically include participation

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from each funded project and a large number of participants from EPA’s research and policy offices, as

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well as participants from states and regions and the broad scientific community. The early grant period

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meetings provide opportunities for coordination among scientists. One notable example of a

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collaborative outcome from early grant period meetings was a more coordinated effort among grantees

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participating in a measurement campaign in Riverside, California (Study of Organic Aerosols at Riverside,

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SOAR) and subsequent collaborative research papers. Meetings later in the grant period are used to

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promote the research results to EPA staff and the broader audience participating in person or remotely

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through webinar.

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The work resulting from these projects addressed most of the objectives (scientific questions) set forth

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in the original solicitations developed by EPA (Table 1). The development of new and advanced

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instrumental methods with increased chemical speciation of organic PM (question C1) and the collection

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and identification of unique source tracers (question C2) and profiles for many different sources

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(question C4 and C5) enabled enhanced source apportionment for organics (question C7).

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Investigations into the reliability of different measurement techniques and common parameters

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provided insight into the strengths and weakness of currently available and employed measurement

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techniques (question C3). Projects advanced understanding and model representation of organic PM

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and its formation as secondary organic aerosol (SOA) through photooxidation with work on semi-volatile

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primary PM, the volatility basis set, aqueous phase oxidation of organics, heterogeneous phase

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reactions, and modeling applications with externally mixed aerosol approaches (question C8).

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Several new modeling source apportionment approaches were developed (questions C9, SA2 and SA3).

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Research also increased the knowledge of biogenic organic emissions and their reaction kinetics

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(question C7). While a productive body of work resulted from these solicitations, several of the original

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goals were only slightly addressed and provide opportunities for subsequent research. These include

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questions relating to using source apportionment to evaluate emissions control programs (SA1),

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improved understanding of local compared with regional emissions impacts on urban air quality (C6),

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and source contribution to ambient PM coarse mass (SA4).

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Broad reviews of specific grant solicitations have frequently been requested by various Agency review

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groups including EPA’s Science Advisory Board and the Board of Scientific Counselors. Determining the

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impact of scientific funding is a complex problem. Some studies use publication counts and citations11,12,

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economic impacts (for instance, immediate job creation) 13 or attempt to assess the broader impact on



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scientific knowledge and the creation of new technology. Other STAR grant reviews include a synopsis

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of research highlights and list of published papers for each grantee. A review of these grant summaries

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and those developed by other funding agencies shows that they generally do not include a quantitative

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impact of the work on the scientific community.

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Here, the impact of these solicitations is estimated quantitatively in terms of publications and citations

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and also qualitatively by presenting a synthesis of the work in the most cited publications and additional

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research that has clearly impacted the field. This assessment is unique in that total publications are

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provided along with quantitative estimates of how work done for each funding opportunity impacted

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the scientific community: with estimates of citations of manuscripts published through funding of these

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RFAs and also reporting the impact factor of published work. In this assessment, the scientific impacts of

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these two solicitations are considered jointly due to the significant overlap in content of the questions

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(shown in Table 1). The quantitative and qualitative approach to assessing the research related to these

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funding opportunities presented here may provide a template for similar assessments of other programs

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within EPA or for other funding organizations.

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METHOD

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A list of published, peer-reviewed manuscripts resulting from work partially or fully funded through

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these two solicitations was compiled. This list is based on final reports and follow-ups submitted by the

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principal investigators and additional database searches, primarily Google Scholar. For most STAR grant

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programs, these additional database searches typically account for 25 – 45% of the total publication

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count. This is often due to publications being released after the end of the project and reporting period


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that attribute support to the closed grant. In addition to the solicitations assessed here, publication

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totals are estimated for 5 other EPA STAR grants.

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While an insufficient lag time for tracking new publication may lead to some underestimate of the

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impact in peer review literature, some overestimate of impact is possible as some publications attribute

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unrelated work to these STAR grant funded projects. It is also possible some publications partially

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funded by these grants did not properly acknowledge these other funding sources leading to an

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underestimate of impact. While such inconsistencies were investigated, this inaccurate attribution

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could potentially result in some publications being improperly included or excluded from this analysis.

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Annual citation data was extracted from Thomson Reuters’ Web of Science® database on July 8 and 9,

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2013. Journal impact factors were taken from Thomson Reuters’ 2011 Journal Citation Report®.

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RESULTS and DISCUSSION

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Quantitative Analysis of the Contribution to Scientific Literature

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The 27 projects funded under these two solicitations supported 50 individual principal investigators and

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produced 275 publications including over 850 unique authors. The full list of publications is included in

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Supplemental Materials. The amount of publications generated from these solicitations falls within the

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range seen from other EPA STAR grants from the 2000s, especially when considering the amount of

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publications per awarded grant (Table 2). Publications appeared in 37 different journals with an average

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2011 impact factor of 4.21 (weighted by the number of papers in each journal). The impact factor for a

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journal is related to the number of citations of recent articles in that specific journal where higher

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impact factors indicate journals where papers are, on average, more highly cited. Table S1 shows the

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complete list of journals and individual journal impact factors. Notably, three journals accounted for



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55% of the publications: Environmental Science and Technology (25%), Atmospheric Environment (20%),

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and Atmospheric Chemistry and Physics (10%).

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Many of the publications resulting from these projects were highly cited within the scientific

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community. As of the collection of the data, there were 13,612 citations to publications supported by

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these solicitations with 31 publications (11%) cited over 100 times and over half (142 papers) cited over

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25 times. Yearly citation counts for each publication are shown in Table S2. Figure 1 shows the number

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of publications and citations for years 2004 to 2012. Publication levels peaked in 2007 and continued

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well past the end of project funding, which was approximately 2006-2007 (with several no cost

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extensions into 2009). Citations to these manuscripts steadily increased between 2004 and 2011 with a

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slight decrease in citations in 2012. Additional years of citation counts are needed to determine whether

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citations to this body of work have peaked in published literature.

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A lag time is necessary after funding completion to fully capture the total number of published

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manuscripts for grant evaluation assessments. Here, publications continue for five years beyond the end

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of the grant funding and those published after the end of the project period account for nearly half of

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the total number of papers related to these solicitations. While enough time has likely passed to

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determine which publications will have considerable impacts on the scientific community, it may still be

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too early to fully evaluate the impact of this body of research since citations to these manuscripts

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continue. A lag time well beyond five years after the end of grant funding is needed to fully capture

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citations to grant funded research for bibliometric evaluation assessments. In addition, it may take even

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longer before definitive conclusions about policy impacts may be drawn. These significant time lags


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should be considered when identifying research priorities and assessing the effectiveness of research

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programs.

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Bibliometric assessments provide some context about the impact research has on the scientific

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community and allows for comparison with other research funding programs. Ultimately, the success of

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a research funding program is based on the advancements in science as a result of the awarded research

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projects. Figure 2 highlights advances in our knowledge and understanding of PM in the atmosphere

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resulting from this group of projects. The following discussions provides more detail about these

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highlights while focusing on the more impactful and highly cited papers in the 10 years following these

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solicitations.

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Emission Precursors to SOA

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In the early 2000s, at the time these solicitations were drafted, regulatory photochemical models such

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as EPA’s Community Multiscale Air Quality (CMAQ) model treated SOA formation and organic oxidation

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in fairly simple implementations. Yields of SOA within models from known biogenic and anthropogenic

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precursors were not well characterized and few SOA pathways were modeled.14 Biogenic emissions

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inventories of monoterpenes were poor and sesquiterpene emissions were not included in biogenic

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emissions models due to the minimal impact these compounds have on ozone chemistry.15,16 Several

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STAR-funded projects investigated the emission rates of sesquiterpenes and monoterpenes from a

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variety of tree species17–20 and additional projects prepared air quality model ready emissions datasets

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of biogenic organic gases.16,21

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Characterization of biomass burning emissions for use in modeling has improved, in part, by work

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funded through these solicitations.22 Several groups investigated the emissions rates from biomass

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burning as well as the radiative forcing properties of wildland fires23, the emissions factors associated

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with both the flaming and smoldering stages of prescribed burning in Georgia22, and a downwind

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analysis of prescribed burning plumes.24

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While model performance for organic carbon mass has improved, it is still typically underestimated at

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many monitor locations in the United States.25 Researchers working on projects funded from these

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solicitations point out that traditional emissions measurement techniques collect high volatility gas

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phase species and particulate phase carbon but do not capture volatile organic compound (VOC) species

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with intermediate volatility.26 Speculation that these missing VOC emissions likely form SOA has led to

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additional research focused on characterizing the missing VOC mass from various sectors (e.g. mobile

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sources and biomass burning) and better understanding their SOA formation potential. Since studies

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have now shown that species with intermediate volatility have a strong potential to form SOA in the

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atmosphere, understanding and including their emissions as model input is essential.26

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Production Pathways of SOA

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STAR-funded researchers identified biogenic monoterpene and sesquiterpene pathways of SOA

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production27–29, leading to a more accurate representation of organic PM in models. Several studies

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estimated yields for isoprene oxidation under a large variety of conditions using smog chamber data.30–34

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Building on this, the contribution of isoprene to SOA formation was determined30,31,33 and included in

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model formulations.35 With the high global emissions rates of isoprene (emitted from trees such as oak

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and poplar), it became evident that even though the reaction rates have relatively low yields, the


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contributions to SOA would still be quite high in many regions.35 Using modeling approaches, it was

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found PM mass contributions from isoprene oxidation products to be non-negligible 36 and as high as 1

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µg/m3 in the Southeastern United States (for reference, the current annual average PM2.5 NAAQS is 12

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µg/m3) 37.

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Additionally, STAR-funded researchers investigated the kinetics of α-pinene and β-pinene (emitted from

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coniferous trees) oxidation under a variety of conditions and the measured characteristics of the

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resulting SOA.28,29,38–46 Several other terpene compounds were also analyzed to quantify their potential

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contributions to SOA formation.46–49 As a result, the mechanisms and yields associated with SOA

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formation from a variety of other organic natural sources are now better understood.50–55 The addition

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and improvement of these biogenic production pathways in photochemical models combined with

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better representation of biogenic precursor emissions16,17 increased model predictions of summertime

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organic aerosol, where underestimates were most pronounced.56

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Additional analyses of the impacts of clouds on the concentrations and reactions of biogenic species

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showed significant aqueous-phase oxidation of isoprene using a chemical box model and a proposed

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pathway for in-cloud isoprene oxidation57. Follow-up studies provided additional evidence of the

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importance of this reaction pathway58,59 and studies also demonstrated aqueous-phase oxidation of

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glyoxal60, pyruvic acid61, and methylglyoxal62 to SOA. Researchers gained a better understanding of what

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fraction of organic aerosols are water soluble63,64 and the potential of SOA to act as cloud condensation

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nuclei.79–81 STAR-funded projects found that heterogeneous chemistry could occur on atmospherically

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relevant time scales.65–67 Accounting for the aqueous phase oxidation of glyoxal and

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methyglyoxal58,60,61 have also improved model performance underscoring the importance of continued

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investigations into the kinetics associated with other chemical systems.



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SOA formation mechanisms and yields for anthropogenic compounds such as toluene68,69, xylene,

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benzene54, and other alkanes70 also provided opportunities for improving model formulations71 as did

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results showing that both anthropogenic and biogenic SOA form oligomers under certain atmospheric

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conditions, thus potentially increasing atmospheric residence time.53,72 Improved anthropogenic SOA

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representation and the inclusion of multi-step oxidation (or aging) resulted in model estimates aligning

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more closely with measurements. In recent years, the treatment of organic aerosol in CMAQ has been

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extensively updated to reflect the scientific community’s improved understanding of SOA partitioning,

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pathways, and yields.56

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Some of the research done under these projects showed the inaccuracy of combining individual species

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kinetics to reproduce kinetics of mixtures of organic species49. Work with measurements of the kinetics

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of SOA formation for several mixtures73,74 highlighted the difficulty in extrapolating kinetics of even

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simple mixtures from individual species75 and the need for more studies of realistic mixtures or new

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methods for accounting for these interactions. Related projects showed the importance of accounting

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for the semivolatile nature of many primary organic PM emissions26.

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Under certain conditions, some organic PM species emitted as particles will revolatilize once they reach

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more dilute solutions in ambient air. These gas phase species could then be oxidized to form additional

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SOA. An approach for treating SOA based on the volatility of the species, termed the volatility basis set

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approach, was developed to account for continued oxidation of organic species.76 Including these phase

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changes and subsequent reactions leads to better agreement between the fraction of oxygenated

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organic PM predicted in models with laboratory chambers and ambient measurements.77–79

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Additionally, researchers considered additional reaction steps leading to “second-“, “third-“, and even


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“fourth-generation” oxidation products, which can also contribute to SOA mass.80–82 These further

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oxidation products also potentially have lower volatilities and are more likely to exist in the condensed

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phase.

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Measurements and Methods

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While methods for measuring components such as elemental (or black) carbon have been in place since

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the early 1980s, thorough evaluation of these methods was needed to improve the understanding of

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atmospheric PM concentrations and its contributing species. One project carried out a comprehensive

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comparison and assessment of the light-absorbing properties of elemental carbon important in

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measurement approaches and climate modeling83. Findings from that work suggest the commonly used

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values for many of these properties are invalid and they provide recommendations for better values and

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ranges for several light absorbing properties. In comparing optical approaches based on transmittance

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and reflectance for separating elemental and organic carbon in ambient samples under a variety of

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temperature protocols, much stronger dependencies were found on the optical approach than the

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temperature protocols that were employed84. Work by several groups compared measurements from

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different instruments and protocols and led to a greater confidence and broader understanding of

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carbonaceous species measurements.85–87 Additionally, STAR-funded researchers investigated the

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potential errors and biases existing in current air pollution monitoring networks and made

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recommendations for the use of new parameters in analysis and new calibration approaches for long-

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term data.88–92 93

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The development of advanced measurement techniques to effectively characterize the organic fraction

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of PM provided high-time resolution data with detailed chemical composition information.94–97 The



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enhanced chemical separation provided by these new instrumental techniques allowed for the

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application of source apportionment techniques to organic concentrations from high-resolution aerosol

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mass spectrometer (AMS) data. These new analysis techniques were applied to global PM

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measurements81 providing evidence that organic species contribute significantly to the PM mass in many

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locations (sometimes exceeding sulfate). This work, alongside work carried out by others, led to the

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development of a systematic approach for considering the extent of oxidation of organic PM based on

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these techniques.82 With the knowledge of other projects funded through the program, several STAR

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grantees organized two fields campaigns (Study of Organic Aerosols in Riverside, Phase 1 and 2 – SOAR-1

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and SOAR-2) in Riverside, CA to leverage among projects and take advantage of the opportunity to

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compare these new techniques while developing a rich dataset for further use.

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Following extensive analysis of the Pittsburgh Air Quality Study dataset, multiple guidelines were

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outlined for the use of AMS data in source apportionment including potential pitfalls98. Similar

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techniques have since been applied to a large variety of data sets including the MILAGRO Campaign in

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Mexico City99–101; SOAR-1 and SOAR-2 campaigns in Riverside, CA; and globally.81

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Furthermore, STAR-funded studies characterized traditional organic molecular markers in emissions for

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diesel in Bangkok102, wildland fuels103, in-use diesel vehicles104, meat cooking, trash burning, and motor

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vehicles.105,106 Two campaigns in Montana (FLAME-1 and FLAME-2) investigated the characteristics of

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biomass burning aerosol from multiple feedstocks using improved instruments.79,95,107 Additional

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methods were developed to better measure volatility profiles107 and polycyclic aromatic hydrocarbons

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(PAHs)108 from ambient samples, respectively. All of these measurements and data analysis techniques

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have improved understanding of the composition of organic PM in the atmosphere.

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Source Apportionment

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Many challenges exist to understanding and attributing the contributions of various sources to organic

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PM at a given location. At the time of these solicitations, primary PM emissions from key sectors were

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not well characterized. Several STAR-funded projects provided better estimates of the mass fraction of

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organic and elemental carbon in primary PM from important source categories such as biomass

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burning.109–112 The improved speciation of primary PM2.5 provided better source profiles for source and

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receptor based models. Advances in measurement techniques enable the detection of specific organic

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compounds, which are known as tracers because they are linked to a particular source. When organic

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carbon "tracers" are included in the identification of sources with receptor modeling tools such as the

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Chemical Mass Balance (CMB) and Positive Matrix Factorization (PMF) greater specificity is

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possible.109,113–115 The level of source information gained through organic carbon tracers and receptor

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modeling techniques provides more information to develop area specific conceptual descriptions of

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PM2.5 origin.116–120 The recognition that organic carbon may be dominated by a single source (e.g.

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residential wood combustion) or group of sources will allow regulating agencies to focus emissions

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reduction strategies in appropriate and effective places.

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Multiple studies used organic tracers to estimate source contributions to organic aerosol in a variety of

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places. Source contributions were estimated from biomass and meat cooking in Pittsburgh, PA and

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found much lower contributions from biomass than in other regions and also large variation in the

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contribution from meat cooking depending on the source profiles used114,115. Source contributions were

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investigated at the Fresno Supersite121 and seasonally in Philadelphia.122 The Philadelphia results

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indicated the importance of considering the SOA component of PM10. Several advanced techniques



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were developed allowing the use of higher time resolution ambient data123 and time variable source

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profiles124 in source apportionment applications.

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Several STAR-funded groups also developed approaches to quantify source contributions using air

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quality models. Among these were approaches that track model-predicted pollutant sensitivity to

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sources emissions either forward (decoupled direct method in three dimensions) or backward (adjoint)

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through a photochemical model.125 The adjoint of GEOS-Chem for particulate matter species126 was

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developed as a tool for optimizing emissions inventories and investigating current source sector

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contributions and impacts from long-range transport.127 Source contribution to SOA concentrations in

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California were estimated by directly tracking source specific tracers within a regional air pollution

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model and found a strong diurnal variation in SOA concentrations119. Estimates of source contributions

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to primary species in the San Joaquin Valley128 were compared with observation-based source

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apportionment approaches in California and found reasonable agreement.129 Source contributions to

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primary organic aerosols in the Eastern United States were estimated using a zero-out approach and

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recommendations followed based on that assessment for emissions inventory improvements130. The

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contribution of Asian dust to North American air pollutant levels were estimated using the GEOS-Chem

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global chemical transport model and found contribution of Asian dust to North American PM

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concentrations131 132.

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Source oriented apportionment approaches that track the contribution of primarily emitted and

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secondarily formed PM2.5 in photochemical models are increasingly relied on to support regulatory

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modeling projects. Most notably EPA has used these models for the 2012 Cross State Air Pollution Rule

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to track state specific emissions to downwind concentrations of PM2.5133 and to attribute health impacts

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to specific emissions sectors.134 Source sensitivity approaches125,135 are also being increasingly applied to


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support regulatory modeling. Higher order decoupled direct method (HDDM) ozone source sensitivity is

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being used to estimate needed changes in NOX and VOC emissions to meet various levels of the ozone

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NAAQS25 to support the risk and exposure assessment for ozone. Source sensitivity and contribution

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information could be used to support evaluation of emissions control options simultaneously for the

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purposes to achieving air quality goals for multiple pollutants.136 Reliance on air quality modeling tools

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and assessments that efficiently assess source sensitivity and contribution information to inform air

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quality management will likely increase in the future. Further work is aimed at supporting research in

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this direction.

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Policy Implications & Continued Related Research

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The research results from these projects led to improvements in policy decision support tools used by

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regulating agencies. One important such tool, the photochemical transport model, is used to estimate

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the impacts of emissions control programs on primary (directly emitted) and secondary (formed in the

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atmosphere) pollutants such as ozone and PM on urban to continental scales. Work done under these

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STAR grant projects led to improved model inputs and model processes, ultimately strengthening the

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technical credibility and confidence in model projections of emission control options.

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In the last decade, advances in understanding of primarily emitted particles and precursors to organic

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carbon mass have brought regulatory photochemical model estimates for PM2.5 closer to agreement

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with observed values. These advances include better estimates of SOA yields from precursors, improved

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biogenic emissions, and identification of new SOA formation pathways.137 However, the work does not

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completely ameliorate the underprediction tendency of regulatory photochemical modeling systems138,

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underscoring the importance of continued research in improving the computational representation of

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emissions and atmospheric fate of organics.



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The motivation for the body of work described in this paper was to understand the concentrations and

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sources of biologically important components of PM to develop science in support of the broader goal to

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improve air quality management. The timing of the 2003 and 2004 solicitations and funding supported

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large scale research toward critical priorities laid out in the NRC studies5–8 in the late 1990s and early

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2000s. As noted previously, much of the research supported by these solicitations were to some degree

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co-funded by other organizations such as the National Science Foundation and the Electric Power

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Research Institute. In addition to working towards answering critical research questions, some of the

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results identified new questions and highlighted the need for continued research in this area. The STAR

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grants program has continued to fund work within this general topic area with two more recent

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solicitations: Sources and Atmospheric Formation of Organic Particulate Matter in 2007139 and

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Anthropogenic Influences on Organic Aerosol Formation and Regional Climate Implications in 2012.140

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Acknowledgements

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We would like to thank Melinda Beaver, Prakash Bhave, Sergey Napelenok, Rob Pinder, Heather Simon,

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and Ted Russell for their helpful feedback and comments on early versions of this work.

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Disclaimer

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The views expressed in this paper are those of the authors and do not necessarily represent the views or

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policies of the U.S. Environmental Protection Agency.

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Subramanian, R.; Winijkul, E.; Bond, T. C.; Thiansathit, W.; Oanh, N. T. K.; Paw-Armart, I.; Duleep, K. G. Climate-Relevant Properties of Diesel Particulate Emissions: Results from a Piggyback Study in Bangkok, Thailand. Environ. Sci. Technol. 2009, 43. Chen, L.-W. A.; Moosmuller, H.; Arnott, W. P.; Chow, J. C.; Watson, J. G.; Susott, R. A.; Babbitt, R. E.; Wold, C. E.; Lincoln, E. N.; Hao, W. M. Emissions from laboratory combustion of wildland fuels: Emission factors and source profiles. Environ. Sci. Technol. 2007, 41. Oanh, N. T. K.; Thiansathit, W.; Bond, T. C.; Subramanian, R.; Winijkul, E.; Paw-armart, I. Compositional characterization of PM2.5 emitted from in-use diesel vehicles. Atmos. Environ. 2010, 44. Mohr, C.; Huffman, J. A.; Cubison, M. J.; Aiken, A. C.; Docherty, K. S.; Kimmel, J. R.; Ulbrich, I. M.; Hannigan, M.; Jimenez, J. L. Characterization of Primary Organic Aerosol Emissions from Meat Cooking, Trash Burning, and Motor Vehicles with High-Resolution Aerosol Mass Spectrometry and Comparison with Ambient and Chamber Observations. Environ. Sci. Technol. 2009, 43, 2443–2449. Huffman, J. A.; Docherty, K. S.; Mohr, C.; Cubison, M. J.; Ulbrich, I. M.; Ziemann, P. J.; Onasch, T. B.; Jimenez, J. L. Chemically-Resolved Volatility Measurements of Organic Aerosol from Different Sources. Environ. Sci. Technol. 2009, 43, 5351–5357. Huffman, J. A.; Ziemann, P. J.; Jayne, J. T.; Worsnop, D. R.; Jimenez, J. L. Development and characterization of a fast-stepping/scanning thermodenuder for chemically-resolved aerosol volatility measurements. Aerosol Sci. Technol. 2008, 42, 395–407. Dzepina, K.; Arey, J.; Marr, L. C.; Worsnop, D. R.; Salcedo, D.; Zhang, Q.; Onasch, T. B.; Molina, L. T.; Molina, M. J.; Jimenez, J. L. Detection of particle-phase polycyclic aromatic hydrocarbons in Mexico City using an aerosol mass spectrometer. Int. J. Mass Spectrom. 2007, 263, 152–170. Shrivastava, M. K.; Subramanian, R.; Rogge, W. F.; Robinson, A. L. Sources of organic aerosol: Positive matrix factorization of molecular marker data and comparison of results from different source apportionment models. Atmos. Environ. 2007, 41, 9353–9369. Kasumba, J.; Hopke, P. K.; Chalupa, D. C.; Utell, M. J. Comparison of sources of submicron particle number concentrations measured at two sites in Rochester, NY. Sci. Total Environ. 2009, 407. Kim, E.; Hopke, P. K. Identification of fine particle sources in mid-Atlantic US area. Water. Air. Soil Pollut. 2005, 168. Kim, E.; Hopke, P. K. Improving source apportionment of fine particles in the eastern United States utilizing temperature-resolved carbon fractions. J. Air Waste Manag. Assoc. 2005, 55. Robinson, A. L.; Subramanian, R.; Donahue, N. M.; Bernardo-Bricker, A.; Rogge, W. F. Source apportionment of molecular markers and organic aerosols-1. Polycyclic aromatic hydrocarbons and methodology for data visualization. Environ. Sci. Technol. 2006, 40, 7803–7810. Robinson, A. L.; Subramanian, R.; Donahue, N. M.; Bernardo-Bricker, A.; Rogge, W. F. Source apportionment of molecular markers and organic aerosol. 2. Biomass smoke. Environ. Sci. Technol. 2006, 40, 7811–7819. Robinson, A. L.; Subramanian, R.; Donahue, N. M.; Bernardo-Bricker, A.; Rogge, W. F. Source apportionment of molecular markers and organic aerosol. 3. Food cooking emissions. Environ. Sci. Technol. 2006, 40, 7820–7827. Chen, J.; Ying, Q.; Kleeman, M. J. Source apportionment of wintertime secondary organic aerosol during the California regional PM10/PM2.5 air quality study. Atmos. Environ. 2010, 44. Docherty, K. S.; Stone, E. A.; Ulbrich, I. M.; DeCarlo, P. F.; Snyder, D. C.; Schauer, J. J.; Peltier, R. E.; Weber, R. J.; Murphy, S. M.; Seinfeld, J. H.; et al. Apportionment of Primary and Secondary Organic Aerosols in Southern California during the 2005 Study of Organic Aerosols in Riverside (SOAR-1). Environ. Sci. Technol. 2008, 42, 7655–7662.



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Table 1. The scientific questions posed in the 2003 Measurement, Modeling and Analysis Methods for Airborne Carbonaceous Fine Particulate Matter solicitation (left) and the 2004 Source Apportionment of Particulate Matter solicitation (right).

802 Measurement Methods C1. What methods can be developed and evaluated that will significantly, reliably, and at reasonable cost, improve our ability to collect, identify, and quantify a greater number of organic species in PM2.5, including polar organic compounds, and/or semivolatile organic species? C2. What new, organic, aerosol tracers for important PM2.5 sources can be identified and quantified in ambient samples? C3. What conditions influence the ability of methods employed at monitoring sites across the country to accurately and reliably measure ambient carbonaceous PM2.5? Combustion Source Characterization C4. What are the rates and species of carbonaceous PM2.5 emitted from fossil fuel, agricultural burning, and wildfires as determined by the most cost-effective available and emerging methods, and how do changes in fuel loads and other conditions influence these emissions? C5. What unique source profiles can be identified and characterized for major combustion sources and fuels for use in receptor-oriented modeling? Process Analysis and Modeling C6. What is the relationship of local and regional emissions to locally observed carbonaceous PM2.5? How do urban plumes impact rural air quality? How do the concentrations of ambient PM2.5 and PM2.5 precursor species in background air influence urban air quality? C7. What is the relative importance of emission sources and atmospheric processes in the accumulation of carbonaceous PM2.5 in specific regions of the US? How do the sources and processes affect the interplay between ozone and PM formation? How does the relative importance differ among US regions? What are the implications for effective reductions in ambient carbonaceous PM2.5? C8. What new modules can be developed that improve our ability to accurately simulate ambient carbonaceous PM2.5 concentrations (including secondary organic aerosol) through accounting for: 1) the phase transition between gases and aerosols for semi-volatile compounds, 2) aqueous and heterogeneous chemical processes, and 3) alternative aerosol representations (such as external mixtures of particles)? C9. What techniques can best be used in numerical air quality models to attribute the components of carbonaceous PM2.5 to the specific sources that emitted them or their gaseous precursors?

SA1. How can source apportionment tools be used to evaluate the effectiveness of emission control programs, particularly in cases where not only the source strength changes, but also the source profiles change?

SA2. What will be the sources of PM and their relative impacts in areas that may not attain the PM2.5 NAAQS, with emphasis on sources expected in the future?

SA3. What is the relative importance of emission sources, both locally generated and regionally transported, in the formation and daily variation of PM2.5 in different regions of the US?

Coarse Particulate Matter SA4. What are the relative source contributions to ambient anthropogenic coarse particle concentrations in different regions of the US, with attention to differences in composition?

803


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804

805 806


Table 2. Peer reviewed publication counts for these and other recent EPA STAR grant solicitations.141–145

Carbonaceous PM and Source Apportionment Feasibility of Estimating Pesticide Exposure and Dose in Children Using Biological Measurements Mercury Transport and Fate Through a Watershed Technology for a Sustainable Environment A Decade of Tribal Environmental Health Research

Grants 27 12 11 91 10

Publications in Additional Found in Recent Original Synthesis Total Publications Document Literature Search Publications per Grant 275 10.2 36 40 76 6.3 104 30 134 12.2 372 203 575 6.3 58 3 61 6.1

807



808 809

Figure 1. The number of published journal articles (black line) and citations to those published articles (red line) per year for work funded under these solicitations.

810 811


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812 813


Figure 2. A schematic showing components of the PM2.5 carbon system. Colored sections indicate areas of focused research as part of these grants.

814



80

3000

70

2500

60 2000

50

40

1500

30

1000

20 500

10 0

0 2004 2005 2006 2007 2008 2009 2010 2011 2012

Year ACS Paragon Plus Environment

Number of Citations

Number of Publications

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Synthesizing Scientific Progress: Outcomes from U.S. EPA's

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