slide1 n.
Skip this Video
Download Presentation

Loading in 2 Seconds...

play fullscreen
1 / 8

Background - PowerPoint PPT Presentation

  • Uploaded on

I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
Download Presentation

PowerPoint Slideshow about 'Background' - ardith

Download Now An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript

MARAMA/NESCAUM/LADCO Project:Source Apportionment of Air Quality Monitoring Data:Paired Aerosol / Trajectory Database AnalysisTool DevelopmentR. Husar, K. Hoijarvi, J. Colson, S. Falke, CAPITAProject Officer, Serpil Kayin, MARAMAProject Period: September 2002 – July 2003Progress Report: Dec 2002

  • Atmospheric aerosol system has three extra dimensions (red), compared to gases (blue):
    • Spatial dimensions (X, Y, Z)
    • Temporal Dimensions (T)
    • Particle size (D)
    • Particle Composition ( C )
    • Particle Shape (S)
  • Bad news: The mere characterization of the 7D aerosol system is a challenge
    • Spatially dense network -X, Y, Z(??)
    • Continuous monitoring (T)
    • Size segregated sampling (D)
    • Speciated analysis ( C )
    • Shape (??)
  • Good news: The aerosol system is self-describing.
    • Once the aerosol is characterized (Speciated monitoring) and multidimensional aerosol data are organized, (see RPO VIEWS effort), unique opportunities exists for extracting information about the aerosol system (sources, transformations) from the data directly.
  • Analysts challenge: Deciphering the handwriting contained in the data
    • Chemical fingerprinting/source apportionment
    • Meteorological back-trajectory analysis
    • Dynamic modeling
data input pmf and unmix model results
Data Input: PMF and UNMIX Model Results

Source attribution results (PMF and UNMIX) for 16 receptor sites between Illinois and New England using IMPROVE and CastNet data have been completed by a previous project.

The results of the Battelle/Sonoma modeling project are source profiles and time series for each source contribution at each location

Prepared by

Battelle and Sonoma Tech. Inc.

pmf cluster sources c1 c9
PMF Cluster ‘sources’: c1-c9
  • PMF Cluster Trends

Analysis Tool is implemented in Voyager – Distributed Web-based data explorer.

seasonal residence time e g sum restime for loc lybr date between june sept
Seasonal Residence Time e.g. Sum ResTime for Loc=LYBR, Date between June-Sept

Lye Brook, DJF

Gr Smoky Mtn, JJA

Lye Brook, JJA

Gr Smoky Mtn, JJA


Combining Chemical Fingerprints and Transport, Lye Brook, NH Aerosol Source Type and Transport Origin AnalysisWishinski and Poirot (2002)Based on Positive Matrix Factorization, PMF results from B. Coutant and ATAD trajectories from K. Gebhart

Secondary Coal

Avg. Mass: 3.2 ug/m3 (42%)

Species: S, OC, EC, Na

Summer Maximum

Biomass Smoke

Avg. Mass: 2.4 ug/m3 (32%)

Species: OC, EC, S, K

Summer Maximum

East Coast Residual Oil

Avg. Mass: 0.38 ug/m3 (5%)

Species: OC, EC, S, Si, Ni, V

Winter Maximum

transport pattern filtered by chemical source lye brook pmf source c6 sulfate titanium
Transport PatternFiltered by Chemical ‘Source’ LYE BROOK, PMF Source C6 Sulfate, Titanium

Transport During High C6 Chemical Conditions

Transport During Low C6 Chemical Conditions

chemical trajectory tools project options
Chemical Trajectory Tools Project Options

VIEWS Database Compatibility

  • Make the chemical-trajectory exploration tool compatible with the evolving VIEWS database at CIRA, Colorado State U.:
    • insuring consistency of the data base schema
    • query tools compatibility
    • data presentation compatibility

Dynamic Trajectory Aggregation

  • Online filtering and aggregation of trajectory data
    • ad hoc gridding, contouring at arbitrary grid resolution
    • alternative rendering, e.g. trajectory bundles, instead of residence time contours

Future: Routine analysis tool?

  • Procedure part of standard toolbox?
  • All locations?
  • All times?