Final Report: Characterization of Fine Particulate MatterEPA Grant Number: R827355C004
Subproject: this is subproject number 004 , established and managed by the Center Director under grant R827355
(EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).
Center: Airborne PM - Northwest Research Center for Particulate Air Pollution and Health
Center Director: Koenig, Jane Q.
Title: Characterization of Fine Particulate Matter
Investigators: Covert, David S. , Haneuse, Sebastien , Koenig, Jane Q. , Larson, Timothy V. , Lumley, Thomas , Schreuder, Astrid
Institution: University of Washington
EPA Project Officer: Chung, Serena
Project Period: June 1, 1999 through May 31, 2004 (Extended to May 31, 2006)
Project Amount: Refer to main center abstract for funding details.
RFA: Airborne Particulate Matter (PM) Centers (1999) RFA Text | Recipients Lists
Research Category: Air Quality and Air Toxics , Particulate Matter , Air
There are two goals to this project: define the number and mass size distribution for the Seattle area over the size range from 20 nm to 10 μm diameter at a central site and secondary sites, and determine the hygroscopic properties of the ultrafine and fine aerosol in Seattle.
Size distribution data processing and fitting
Ultrafine, very fine and fine PM were collected nearly continuously from December 2000 through March 2003 at a Washington State Department of Ecology site on Beacon Hill in Seattle. Particle size distributions from 20nm to 800nm were measured using a differential mobility particle sizer (DMPS) and an aerodynamic particle sizer (APS). The DMPS consisted of an electrostatic classifier and condensation particle counter (models 3081 and 3010, TSI, St. Paul MN). The DMPS stepped through the mobility size range over a period of ten minutes. At the end of a stepped scan sequence, the mobility data were inverted with the charge probability matrix to get the Stokes diameter size distribution, (dN(DpStk)/dlogDp). The size distribution from 700 to 5000 nm was measured with an aerosol particle sampler APS (model 3310, TSI, St. Paul, MN) on the same ten minute basis to yield the aerodynamic diameter size distribution (dN(DpAero)/dlogDp). The DMPS measurements were converted to an aerodynamic diameter base by assuming a particle density that varied from 1.0 g/cm3 at 100 nm to 1.8 g/cm3 at 600nm based on measurements at other locations, chemical analysis and several direct measurements of the output of the DMA by the APS over their overlapping measurement range. These inverted DMPS data were merged with the APS aerodynamic size distributions. The ten-minute distributions were edited to eliminate periods of instrument malfunction and high variability in particle concentration due to on-site activity.
The ten-minute distributions were grouped into overlapping, two hour windows. The two- hour window was selected to minimize the stochastic variability in the measurement and to maximize the measure of atmospheric variability. The number-size distributions were then fit by a multi-modal, multi-moment lognormal fitting algorithm The algorithm software was implemented in the R statistical programming system (Ihaka Gentleman, 1996), which minimizes the residual between the measured concentration as a function of size and the fit values simultaneously for three moments (number, surface, and volume) of the distribution rather than for each moment individually. Four lognormal modes were allowed reducing the sixty-seven measured differential concentrations to twelve parameters: concentration, geometric mean , diameter, and standard deviation for each the four modes. The algorithm found a combination of the four lognormal functions that simultaneously minimized the residual of the number, surface area, and volume moments of the distribution. Constraints to the ranges mean diameters and standard deviation for the modes were imposed to prevent unphysical solutions. Volume mean diameters and concentrations were derived from the number-size, multimodal model.
The nanometer mode was included in the algorithm for completeness even though measurement did not include the range; it was not subsequently used due to insignificant frequency of occurrence and volume concentrations even when the algorithm indicated the presence of a nano-mode.
Size distribution and chemical species measurements were combined into a multivariate receptor model of PM2.5 (Larson et al, 2006). The combined model extends the traditional chemical mass balance approach by including a simultaneous set of conservation equations for both particle mass and volume, linked by a unique value of apparent particle density for each source. The model distinguished three mobile source feature, two consistent with previous identifications of “gasoline” and “diesel” sources , and an additional minor feature enriched in EC, Fe, MN and ultrafine particle mass that would have been difficult to interpret in absence of particle size information. This study has also demonstrated the feasibility of defining missing mass as an additional variable, and thereby providing additional useful model constraints and eliminating the posthoc regression step that is traditionally used to rescale the results. Secondly, the very fine particle data were used in a health outcome study evaluating associations between emergency department visits for asthma (Mar et al, 2007, submitted -- see project R827355C002).
Journal Articles on this Report : 1 Displayed | Download in RIS Format
|Other subproject views:||All 5 publications||3 publications in selected types||All 3 journal articles|
|Other center views:||All 209 publications||113 publications in selected types||All 109 journal articles|
||Larson TV, Covert DS, Kim E, Elleman R, Schreuder AB, Lumley T. Combining size distribution and chemical species measurements into a multivariate receptor model of PM2.5. Journal of Geophysical Research-Atmospheres 2006;111(D10):D10S09 (10 pp.).||
Supplemental Keywords:RFA, Scientific Discipline, Air, Geographic Area, Ecosystem Protection/Environmental Exposure & Risk, particulate matter, Environmental Chemistry, Health Risk Assessment, State, Monitoring/Modeling, Biochemistry, indoor air, Atmospheric Sciences, ambient aerosol, environmental monitoring, fate and transport, particle size, particulates, atmospheric dispersion models, atmospheric measurements, hygroscopic properties, environmental measurement, ambient air, air pollution, Washington (WA), particulate matter mass, size distribution monitoring, indoor air quality, ecological models, transport modeling, aerosol analyzers, aerosols, air quality, dosimetry
Progress and Final Reports:Original Abstract
Main Center Abstract and Reports:R827355 Airborne PM - Northwest Research Center for Particulate Air Pollution and Health
Subprojects under this Center: (EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).
R827355C001 Epidemiologic Study of Particulate Matter and Cardiopulmonary Mortality
R827355C002 Health Effects
R827355C003 Personal PM Exposure Assessment
R827355C004 Characterization of Fine Particulate Matter
R827355C005 Mechanisms of Toxicity of Particulate Matter Using Transgenic Mouse Strains
R827355C006 Toxicology Project -- Controlled Exposure Facility
R827355C007 Health Effects Research Core
R827355C008 Exposure Core
R827355C009 Statistics and Data Core
R827355C010 Biomarker Core
R827355C011 Oxidation Stress Makers