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2006 Progress Report: Advancing ATOFMS to a Quantitative Tool for Source Apportionment
EPA Grant Number: R831083Title: Advancing ATOFMS to a Quantitative Tool for Source Apportionment
Investigators: Prather, Kimberly A. , Hopke, Philip K.
Institution: University of California - San Diego , Clarkson University
EPA Project Officer: Hunt, Sherri
Project Period: October 1, 2003 through September 30, 2006 (Extended to September 30, 2007)
Project Period Covered by this Report: October 1, 2005 through September 30, 2006
Project Amount: $450,000
RFA: Measurement, Modeling, and Analysis Methods for Airborne Carbonaceous Fine Particulate Matter (PM2.5) (2003)
Research Category: Air Quality and Air Toxics , Particulate Matter
Description:
Objective:The objective of this research project is to explore fully the aerosol time-of-flight mass spectrometry (ATOFMS) data collected during the Supersite Program to ascertain if single particle mass spectrometry can: (1) measure quantitatively the carbonaceous component of the ambient aerosol, including organic carbon (OC) and elemental carbon (EC) and specific compounds like polyaromatic hydrocarbons, and to ascertain if it is possible to develop a quantitative and universal calibration that provides results comparable to time-resolved OC/EC measurements; (2) provide key markers that distinguish among sources of carbonaceous aerosol, including diesel and spark-ignition vehicles, mobile and stationary sources, fossil fuel sources versus biomass burning, and primary biological and/or secondary organics; (3) distinguish the difference between primary and secondary OC by examining if primary OC is more related to coemitted EC particles or gases whereas secondary OC is found associated with more abundant sulfate or nitrate particles; and (4) provide critical insights into atmospheric processes that then can be represented better in air quality models such as the relationship of secondary OC with primary particle type. Particle type(s) like sulfate or nitrate may be particularly important for providing an effective surface on which the carbonaceous material can condense.
Progress Summary:Work has been completed on a number of objectives. There has been progress on the development of additional approaches to analyzing ATOFMS data, including developing better classification approaches for single-particle compositions measured using the ATOFMS, calibrations based on particle class populations and ambient particulate matter composition measurements, and direct approaches to determining quantitatively the amount of OC associated with EC in particles.
Particle Classification
To test classification methods, we have analyzed datasets prepared from single particle data collected in source tests so the true origins of each particle are known. Through random selection of particle data from each source type, a simulated ambient sample of particles can be prepared, and the data analysis tools can then be tested. The following source types were used: gasoline-powered light duty vehicles (LDV), diesel-powered heavy duty vehicles (HDV), biomass burning, dust, coal combustion, and sea salt. Adaptive resonance theory (ART)-2a (Song, et al., 1999) and a density-based cluster method, Density-Based Spatial Clustering of Application with Noise (DBSCAN) (Daszykowski, et al., 2001; Daszykowski, et al., 2002), have been used for classification of the single particle mass spectra along with a regrouping program that was developed in Dr. Prather’s group (Regroup). It has been found that ART does not merge clusters during the training process, so once the training process generates two close centers, they will remain and grow up separately. This result could produce an overly fine clustering. One feasible way to resolve this problem is to use a “second grouping” method. We have compared two second grouping methods, DBSCAN and “Regroup.” Although these two methods did not show a significant difference in this benchmark set, they both generated a clean clustering result for the biomass, dust, coal combustion, and sea salt samples. Using DBSCAN alone also yielded a relatively good (but a little poorer) result for the biomass, dust, coal combustion, and sea salt samples, so some suggestions for using DBSCAN can be inferred from the results. A manuscript is being prepared for publication.
Source Apportionment Using Positive Matrix Factorization (PMF)
Real ATOFMS aerosol time series from the ACE-Asia campaign were submitted to PMF and factored successively with different numbers of assumed sources. Two methods are introduced for testing the resulting factors: (1) comparing the residuals of the factorization to residuals obtained from control data made by shuffling the original data; and (2) examining the relative difference between actual and shuffled data factors. In addition, the factors are compared to the original time series of the overall particle types. All of these methods show that several factors can be retained: factorization residuals are substantially lower than residuals from the same series randomized, factors differ much less from their low bandpass filtered version than random variables would, and the smoothest factors coincide with the time series of the most easily explained chemical classes. Besides their immediate application to PMF of ATOFMS aerosol counts, these results suggest that these validation methods can be used in other blind source separation problems, and in particular, that frequency content of the data can be used to select good from bad factors in blind source separation. A manuscript is being prepared for publication.
Direct Approach
Spencer, et al. (2006) used a new approach to measure the fraction of OC associated with EC in aerosol particles using single particle laser desorption ionization. A tandem differential mobility analyzer (DMA) was used to generate OC/EC particles by size, selecting EC particles of a given mobility diameter and then coating them with known thicknesses of OC measured using a second DMA. The mass spectra of the OC/EC particles exiting the second DMA were measured using an ultrafine-ATOFMS. A calibration curve was produced with a linear correlation (R2 = 0.98) over the range of OC/EC ion intensity ratios observed in source and ambient studies. Importantly, the OC/EC values measured in ambient field tests with the ultrafine-ATOFMS show a linear correlation (R2 = 0.69) with OC/EC mass ratios obtained using semicontinuous, filter-based, thermo-optical measurements. The calibration procedure established herein represents a significant step toward quantification of OC and EC in submicron ambient particles using laser desorption ionization mass spectrometry.
Future Activities:In this closing period of the grant, we are completing final manuscripts that we expect to submit by the end of the extended project period.
References:
Daszykowski M, Walczak B, Massart DL. Looking for natural patterns in data: part 1. density-based approach. Chemometrics and Intelligent Laboratory Systems 2001;56:83-92.
Daszykowski M, Walczak B, Massart DL. Representative subset selection. Analytica Chimica Acta 2002;468:91-103.
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;71:860-865.
Spencer MT, Prather KA. Using ATOFMS to determine OC/EC mass fractions in particles. Aerosol Science and Technology 2006;40(8):585-594.
Journal Articles:No journal articles submitted with this report: View all 8 publications for this project
Supplemental Keywords:OC/EC, secondary organic aerosol, supersite, air, environmental chemistry, air toxics, particulate matter, PM, aerosol time-of-flight mass spectrometry, air quality models, atmospheric measurements, human health risks, Ecosystem Protection/Environmental Exposure & Risk, Air, Scientific Discipline, RFA, air toxics, Environmental Engineering, particulate matter, Environmental Chemistry, Monitoring/Modeling, Environmental Monitoring, aerosol analyzers, carbon particles, particulate matter mass, secondary organic aerosols, particle phase molecular markers, aerosol time of flight mass spectrometry, measurement methods, aerosol particles, air sampling, atmospheric dispersion models, emissions, air quality models, human health effects, monitoring stations, source apportionment, modeling studies, atmospheric particulate matter, atmospheric measurements, modeling, secondary organic aerosol, human exposure, transport modeling,
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Ecosystem Protection/Environmental Exposure & Risk, Air, Scientific Discipline, RFA, air toxics, Environmental Engineering, particulate matter, Environmental Chemistry, Monitoring/Modeling, Environmental Monitoring, aerosol analyzers, carbon particles, particulate matter mass, secondary organic aerosols, particle phase molecular markers, aerosol time of flight mass spectrometry, measurement methods, aerosol particles, air sampling, atmospheric dispersion models, emissions, air quality models, human health effects, monitoring stations, source apportionment, modeling studies, atmospheric particulate matter, atmospheric measurements, modeling, secondary organic aerosol, human exposure, transport modeling
Progress and Final Reports:
2004 Progress Report
2005 Progress Report
Original Abstract
Final Report