Final Report: Research Consortium on Ozone and Fine Particle Formation in California and in the Northeastern United States: Cal Tech, UC-Riverside, UC-San Diego, UC-Davis Report

EPA Grant Number: R826371C001
Subproject: this is subproject number 001 , established and managed by the Center Director under grant R826371
(EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).

Center: Research Consortium on Ozone and Fine Particle Formation in California and in the Northeastern United States
Center Director: Seinfeld, John
Title: Research Consortium on Ozone and Fine Particle Formation in California and in the Northeastern United States: Cal Tech, UC-Riverside, UC-San Diego, UC-Davis Report
Investigators: Bhave, Prakash , Cass, Glen , Kleeman, Michael J. , Prather, Kimberly A.
Institution: California Institute of Technology , University of California - Irvine , University of California - Riverside , University of California - San Diego
EPA Project Officer: Shapiro, Paul
Project Period: April 15, 1998 through April 14, 2003
RFA: Special Opportunity in Tropospheric Ozone (1997) RFA Text |  Recipients Lists
Research Category: Air Quality and Air Toxics , Air

Objective:

This is one of the projects conducted by the Research Consortium on Ozone and Fine Particle Formation in California and in the Northeast United States. In this particular project, source-oriented air quality model predictions of the size and chemical composition of individual atmospheric particle classes were evaluated against single-particle measurements taken by aerosol time-of-flight mass spectrometry (ATOFMS) and applied to assess the source apportionment accuracy of a single-particle receptor-oriented method. The distinguishing feature of the air quality model used in these studies is that the ambient aerosol is represented as an ensemble of compositionally distinct particle classes, rather than as an internally mixed distribution in which the chemical composition of all like-sized particles are assumed to be identical. The air quality model tracks the physical diameter, chemical composition, and atmospheric concentration of thousands of particle classes as they are transported from sources to receptors while undergoing atmospheric chemical reactions. Each particle class interacts with a common gas phase, but otherwise evolves separately from all other particle classes, yielding an aerosol population in which particles of a given size may exhibit different chemical compositions (Kleeman, et al., 1997).

Summary/Accomplishments (Outputs/Outcomes):

Air quality model predictions were evaluated by comparison with semiquantitative ATOFMS measurements of single-particle size and composition at Long Beach and Riverside, CA, during September 1996. Model predictions were modified to simulate the chemical sensitivities and compositional detection limits of the ATOFMS instruments, thus permitting a direct, semiquantitative comparison between the air quality model predictions and the single-particle ATOFMS measurements to be made (see Figure 1). The air quality model predictions of the fraction of atmospheric particles containing sodium, ammonium, nitrate, carbon, and mineral dust matched the single-particle observations across all particle sizes measured by ATOFMS at the Long Beach site (Da = 0.56 - 3.5 µm), and in the coarse particle size range at the Riverside site (Da = 1.8 - 3.5 µm, where Da = aerodynamic particle diameter). The results of this study provide some confidence that the source-oriented air quality model can be used to accurately predict the relative abundances of various classes of atmospheric particles (Bhave, et al., 2002).

Figure 1. Comparison of Model Predictions and ATOFMS Measurements Taken at Long Beach, CA, on September 24, 1996. Each dot represents 1 percent of the particle population in the 1.0-1.8 µm range.

Second, a method was developed for quantifying ATOFMS measurements of ammonium and nitrate in size-segregated atmospheric aerosols. Chemical composition measurements taken by single-particle mass spectrometers are difficult to quantify, largely because the instrument sensitivities to different chemical species in mixed ambient aerosols are unknown. Our approach for determining these sensitivities relies on tandem ATOFMS-impactor sampling, where impactor measurements of the size-segregated aerosol composition are used to quantitatively reconstruct ATOFMS data. ATOFMS measurements were compared with collocated impactor measurements taken at Riverside, CA, in September 1996, August 1997, and October 1997. The comparisons revealed that the ATOFMS instrument sensitivities to both NH4+ and NO3- decline with increasing aerodynamic diameter over the 0.32–1.8 µm particle size range. The stability of this particle size dependence was tested over the broad range of fine-particle concentrations (PM1.8 = 17.6 ± 2.0–127.8 ± 1.8 µg/m3), ambient temperatures (23-35°C), and relative humidity conditions (21–69 percent), encountered during the field experiments. This study provided a potentially generalizable methodology for increasing the temporal and particle-size resolution of atmospheric aerosol chemical composition measurements. These continuous, high-resolution aerosol measurements can ultimately be used for extensive evaluations of air quality models (Bhave, et al., 2002).

Third, the source-oriented air quality model predictions were evaluated against quantitative ambient aerosol measurements taken at Riverside, CA, on September 25, 1996. The aerosol data set included continuous, quantitative, size-resolved measurements of particulate mass, nitrate, and ammonium concentrations, as well as quantitative measurements of atmospheric aerosol mixing characteristics. These measurements, reconstructed from collocated ATOFMS and impactor data, provided an opportunity to perform more detailed and stringent evaluations of aerosol air quality models than were previously possible. The hourly time series of size-segregated aerosol mass, nitrate, and ammonium concentrations, calculated using the model, exhibited diurnal trends comparable to the measurements. Measurements during a 4-hour intensive sampling period were aggregated into narrow particle size intervals to test model calculations of the detailed structure of the aerosol mass, nitrate, and ammonium distributions. Model predictions of the absolute contributions of sea salt, mineral dust, and carbonaceous particles to the size-resolved aerosol mass distribution were found to be consistent with the corresponding measurements. These model evaluations were performed at finer temporal and particle-size resolution than in any previous study, and represent the first quantitative comparison of aerosol mixing characteristics measurements with air quality model predictions (Bhave, et al., in preparation)..

Fourth, the source apportionment accuracy of a neural network algorithm (ART-2a) was tested by applying the algorithm to synthetic single-particle data sets, which were generated using the source-oriented air quality model. The synthetic data sets contain the sizes and chemical compositions of thousands of particle classes as well as the emission source from which each particle class originated. The operator of the ART-2a algorithm was provided with the chemical compositions of each particle with varying degrees of detail, but the particle sources were not disclosed. The ART-2a algorithm successfully grouped particles from the majority of sources actually present when given complete data on ambient particle composition at monitoring sites located near the emission sources. As particles aged in the atmosphere, the algorithm could not accurately separate particles from different sources due to the accumulation of gas-to-particle conversion products. When the algorithm was applied to synthetic single-particle data that were modified to simulate the biases in ATOFMS measurements, best results were obtained using the ATOFMS dual ion operating mode that simultaneously yields both positive and negative ion mass spectra. The results of this study suggest that the use of continuous single-particle measurements, coupled with neural network algorithms, can significantly improve the time resolution of particulate matter source apportionment (Bhave et al., 2001).

References:

Kleeman MJ, Cass GR, Eldering A. Modeling the airborne particle complex as a source-oriented external mixture. Journal of Geophysical Research 1997;102:21355-21372.


Journal Articles on this Report : 4 Displayed | Download in RIS Format

Other subproject views: All 4 publications 4 publications in selected types All 4 journal articles
Other center views: All 49 publications 46 publications in selected types All 46 journal articles
Type Citation Sub Project Document Sources
Journal Article Bhave PV, Fergenson DP, Prather KA, Cass GR. Source apportionment of fine particulate matter by clustering single-particle data:tests of receptor model accuracy. Environmental Science & Technology 2001;35(10):2060-2072. R826371 (Final)
R826371C001 (Final)
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  • Journal Article Bhave PV, Kleeman MJ, Allen JO, Hughes LS, Prather KA, Cass GR. Evaluation of an air quality model for the size and composition of source-oriented particle classes. Environmental Science & Technology 2002;36(10):2154-2163. R826371 (Final)
    R826371C001 (Final)
    R826371C004 (Final)
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  • Journal Article Bhave PV, Allen JO, Morrical BD, Fergenson DP, Cass GR, Prather KA. A field-based approach for determining ATOFMS instrument sensitivities to ammonium and nitrate. Environmental Science & Technology 2002;36(22):4868-4879. R826371 (Final)
    R826371C001 (Final)
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  • Journal Article Song X-H, Hopke PK, Fergenson DP, Prather KA. Classification of single particles analyzed by ATOFMS using an artificial neural network, ART-2A. Analytical Chemistry 1999;71(4):860-865. R826371 (Final)
    R826371C001 (Final)
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  • Supplemental Keywords:

    air quality monitoring, ambient air, particulate, ozone, environmental chemistry, California, Northeastern United States., RFA, Air, particulate matter, tropospheric ozone, ambient air quality, particulates, ozone occurrence, aerosol time-of-flight mass spectrometry (ATOFMS), ambient measurement methods, ozone, ambient air, National Ambient Air Quality Standard, Los Angeles, control measure modeling, modeling studies

    Progress and Final Reports:

    Original Abstract
  • 1998
  • 1999
  • 2000
  • 2001

  • Main Center Abstract and Reports:

    R826371    Research Consortium on Ozone and Fine Particle Formation in California and in the Northeastern United States

    Subprojects under this Center: (EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).
    R826371C001 Research Consortium on Ozone and Fine Particle Formation in California and in the Northeastern United States: Cal Tech, UC-Riverside, UC-San Diego, UC-Davis Report
    R826371C002 Research Consortium on Ozone and Fine Particle Formation in California and in the Northeastern United States: Cal Tech, Carnegie Mellon, Georgia Institute, NJIT, Oregon Institute, UC-Irvine, UC-Riverside Report
    R826371C003 Research Consortium on Ozone and Fine Particle Formation in California and in the Northeastern United States: Cal Tech Report
    R826371C004 Research Consortium on Ozone and Fine Particle Formation in California and in the Northeastern United States: California - Irvine Report
    R826371C005 Research Consortium on Ozone and Fine Particle Formation in California and in the Northeastern United States: Carnegie Mellon Report
    R826371C006 Research Consortium on Ozone and Fine Particle Formation in California and in the Northeastern United States: Carnegie Mellon Report
    R826371C007 Research Consortium on Ozone and Fine Particle Formation in California and in the Northeastern United States: UC-Riverside
    R826371C008 Research Consortium on Ozone and Fine Particle Formation in California and in the Northeastern United States: Oregon Health and Science Report
    R826371C009 Research Consortium on Ozone and Fine Particle Formation in California and in the Northeastern United States: NJIT Report