MARAMA/NESCAUM/LADCO Project: MARAMA/NESCAUM/LADCO Project: Source Apportionment of Air Quality Monitoring Data: Paired Aerosol / Trajectory Database Analysis.

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MARAMA/NESCAUM/LADCO Project: MARAMA/NESCAUM/LADCO Project: Source Apportionment of Air Quality Monitoring Data: Paired Aerosol / Trajectory Database Analysis.

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

Background 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 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. 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.previous project

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 Lye Brook, DJF Gr Smoky Mtn, JJA Lye Brook, JJA Gr Smoky Mtn, JJA

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 Secondary Coal Avg. Mass:3.2 ug/m3 (42%) Species: S, OC, EC, Na Summer Maximum Combining Chemical Fingerprints and Transport, Lye Brook, NH Aerosol Source Type and Transport Origin Analysis Wishinski and Poirot (2002) Based on Positive Matrix Factorization, PMF results from B. Coutant and ATAD trajectories from K. Gebhart

Transport Pattern Filtered 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 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?