Highly Time-Resolved Source Apportionment Techniques for Organic Aerosols Using the Aerodyne Aerosol Mass Spectrometer

EPA Grant Number: R832161
Title: Highly Time-Resolved Source Apportionment Techniques for Organic Aerosols Using the Aerodyne Aerosol Mass Spectrometer
Investigators: Jimenez, Jose-Luis , Hannigan, Michael P. , Schauer, James J. , Zhang, Qi
Institution: University of Colorado at Boulder , University of Wisconsin - Madison
EPA Project Officer: Chung, Serena
Project Period: December 1, 2004 through November 30, 2007 (Extended to November 30, 2008)
Project Amount: $450,000
RFA: Source Apportionment of Particulate Matter (2004) RFA Text |  Recipients Lists
Research Category: Particulate Matter , Air Quality and Air Toxics , Air

Objective:

The overall objective of this proposed project is to develop, validate, and apply fine particulate matter (PM) source apportionment techniques for measurements made with the Aerodyne Aerosol Mass Spectrometer (AMS). The AMS is the only current real-time instrument that provides quantitative size-resolved organic aerosol data with a time resolution of a few minutes. AMS organic data have less fragmentation and thus are more specific for source apportionment than data from laser-ablation mass spectrometers. We expect a number of instruments being developed to improve organic detection specificity via chemical ionization and/or photoionization. The proposed efforts will focus on AMS data but will provide the foundation for using other such data for source apportionment.

Approach:

Preliminary results (section E.2.3) indicate that AMS organic aerosol data are sufficiently specific to address the critical need for source apportionment of organic aerosols with very high time resolution. We will investigate various approaches for apportioning AMS organic data, including: (a) custom techniques that take advantage of our understanding of the data; (b) Advanced Data Mining techniques currently being developed by the University of Wisconsin (under NSF funding); and (c) standard multivariate receptor models (e.g., UNMIX and PMF). We will test all models with simulated AMS data with several overlapping sources. We will then apply these methods to the well-characterized AMS datasets from the Pittsburgh, New York City, and Houston EPA Supersites. We will carry out a new field campaign (using three AMSs) with two objectives: (1) compare with the well-established chemical mass balance (CMB) method from collocated organic molecular marker data; and (2) demonstrate the improvements in organic source apportionment from three new techniques designed to improve the sensitivity and selectivity of the AMS for organic aerosols: a time-of-flight mass spectrometer (replacing the quadrupole used in the standard AMS), low temperature vaporization, and thermal denuding.

Expected Results:

The primary result of this project will be to demonstrate and validate source apportionment of organic aerosols with very high time resolution using AMS data. The results of this project can have a rapid and broad impact because the techniques developed here can be used by many researchers around the world, including the more than 25 research groups with an AMS. In addition, these techniques and algorithms will also provide the foundation for source apportionment using data from emerging and future quantitative aerosol mass spectrometers.

Publications and Presentations:

Publications have been submitted on this project: View all 115 publications for this project

Journal Articles:

Journal Articles have been submitted on this project: View all 31 journal articles for this project

Supplemental Keywords:

multivariate methods, single particle mass spectrometry, RFA, Scientific Discipline, Air, Ecosystem Protection/Environmental Exposure & Risk, particulate matter, Air Quality, Environmental Chemistry, Monitoring/Modeling, Environmental Monitoring, Environmental Engineering, atmospheric dispersion models, particulate organic carbon, atmospheric measurements, model-based analysis, time resolved apportionment, chemical characteristics, environmental measurement, source apportionment, emissions monitoring, air quality models, airborne particulate matter, air sampling, air quality model, analytical chemistry, speciation, particulate matter mass, aerodyne aerosol mass spectrometry, modeling studies, chemical transport models, monitoring of organic particulate matter, aerosol analyzers, atmospheric chemistry, chemical speciation sampling, real-time monitoring

Progress and Final Reports:

  • 2005 Progress Report
  • 2006 Progress Report
  • 2007 Progress Report
  • Final Report