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Data Analysis Techniques

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Presentation on theme: "Data Analysis Techniques"— Presentation transcript:

1 Probing the Properties of Particulate Pollution Greg Evans, University of Toronto

2 Data Analysis Techniques
LAMS Particles Particle Types ART Seasonal Trends Diurnal Source Identification Apportionment Geographic PMF PSCF

3 Episodes from Long Range Sources
300 Average Hit Rate (Hits/Hour) Jan 2002 Feb 2002 Mar 2002 Apr 2002 May 2002 Jun 2002 Jul 2002 Aug 2002 Sep 2002 Oct 2002 Nov 2002 Dec 2002 Jan 2003 Feb 2003 200 Average Hit Rate (Hits/Hour) Jan 2002 Feb 2002 Mar 2002 Apr 2002 May 2002 Jun 2002 Jul 2002 Aug 2002 Sep 2002 Oct 2002 Nov 2002 Dec 2002 Jan 2003 Feb 2003 Sand storm Forrest fires

4 Temporal Trends Road Salt
Jan 2002 Feb 2002 Mar 2002 Apr 2002 May 2002 Jun 2002 Jul 2002 Aug 2002 Sep 2002 Oct 2002 Nov 2002 Dec 2002 Jan 2003 Feb 2003 100 Average Hit Rate (Hits/Hour) 3 1 0: : : : :00

5 Temporal Trends Organic Nitrate
70 Jan 2002 Feb 2002 Mar 2002 Apr 2002 May 2002 Jun 2002 Jul 2002 Aug 2002 Sep 2002 Oct 2002 Nov 2002 Dec 2002 Jan 2003 Feb 2003 Average Hit Rate (Hits/Hour) 5 4 0: : : : :00

6 Nitrate Episodes Particle types
5 14 Hit Rate (hits/hour) Particle Type Mass Concentration (mg/m3) PM2.5 Nitrate 3/11/02 17:00 3/13/02 4:00

7 Applications Regulations: Health Impact: Environmental Impact:
source identification/apportionment temporal and spatial variations speciation based PM2.5 limits Health Impact: time series for epidemiology identification of physiologically important components Environmental Impact: chemical transformation (lab and/or field based) gas-particle interactions role of PM in climate change transport and deposition of metals PM reduction: Study of emission sources (e.g. combustion chemistry, cars) Model evaluation/validation, Rapid analysis during an emergency


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