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Implementation of Emissions Source Apportionment in a Regional Air Quality Model

This study discusses the implementation, verification, and application of a tagged species method in AURAMS to track primary organic and elemental carbons from different sources in the North American domain. The research includes emissions inventory analysis, modeling results verification, and future work considerations.

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Implementation of Emissions Source Apportionment in a Regional Air Quality Model

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  1. Application of an emissions source apportionment method for primary PM components in a regional air quality model M. Samaali, M. Sassi, V. Bouchet Environment Canada, Meteorological Service of Canada, Air Quality Modelling Application Section, 2121 Trans-Canada highway, Dorval, Québec, H9P 1J3. M. Moran Air Quality Research Division, Science and Technology Branch, Environment Canada, 4905 Dufferin Street, Toronto, ON, M3H 5T4, Canada.Environment 6-8th Oct. 2008, Chapel Hill, NC

  2. Contents • Introduction • Implementation of a source apportionment (tagged species) method in AURAMS • Emissions inventory analysis • Modeling results (method’s verification and application) • Conclusion and future work

  3. Introduction - How much does a given source contribute to total PM pollution? • Two main categories of source apportionment methods used in Eulerian 3D AQ model (Yarwood et al., 2004): • (1) sensitivity analysis methods • (2) tagged species methods. - American AQ models (e.g. CMAQ, CAMx) use already both techniques. - Canadian AQ models (e.g. AURAMS, CHRONOS) used only for scenarios analysis so far. Objective:implement, verify and apply a tagged species method in AURAMS to tag and track primary organic (POC) & elemental carbons (EC) emissions from 4 sources in the North American domain.

  4. AQ model description (A Unified Regional Air quality Modeling System: AURAMS)

  5. Implementation of a tagged species method in AURAMS • 4 source types (area and point): • on-road (vehicles, trucks, motorcycles), • off-road & others (marine, air, rail, residential, construction, agriculture, etc.), • minorpoints (stack height < 35m) • majorpoints (stack height >= 35m) • 2 tracers (i.e. POC and EC) for each source with 12 bins each: species increase from 108 to 204 PM species. • Apply the same physical and chemical processes treatment to the tagged species as the original POC and EC species: • Transport (3D advection) and vertical diffusion • Removal processes (dry deposition, wet deposition and rain, fog, and cloud processing) • Emissions (chemical speciation)

  6. Emissions inventory analysis (1): POC and EC emissions totals (Jun-Jul-Aug 2002) Monthly total POC (PM2.5 ) emissions by source type Monthly total EC (PM2.5 ) emissions by source type On-road sources are major emitter of EC Off-road & other sources are major emitter of POC

  7. Emissions inventory analysis (2) : POC from on-road and off-road & other sources (June 2002) Total POC (PM2.5 )from on-road Total POC (PM2.5 ) from off-road & other. - Most of the emissions are located in the Eastern domain - Canadian cities are surrounded by high emission levels

  8. Emissions inventory analysis (3): POC from minor and major points (June 2002) Total POC (PM2.5 )emissionsfrom minor points Total POC (PM2.5 )emissionsfrom major points - Highest spatial density for minor points - Highest emission levels for major points

  9. Runs settings and CPU time analysis Run period (J-J-A 2002) : started in May. 25th 2002, at 6:00 Lateral boundary (LB) & initial conditions: zero initial conditions & zero-gradient method for LB conditions Required computational resources on Environment Canada IBM cluster: ~ 62% CPU time increase Optimization of the code to keep CPU time increase at minimum

  10. Modeling results (tagging method verification) (1) Average difference: 2.2 10-4 ug/m3 (0.37%) Average difference: 2.4 10-4 ug/m3 (1.48%) Good agreement between total POC and EC and their respective tracers sums

  11. Modeling results (tagging method verification) (2) POC emissions contributions POC concentrations contributions There is a correspondence between concentration and emission contributions for each POC tagged species

  12. Modeling results (tagging method verification) (3) EC concentrations contributions EC emissions contributions There is a correspondence between concentration and emission contributions for each EC tagged species

  13. Modeling results (tagging method application) (4) Off-road & other. On-road 3% 5% 6% 2% 6% 3% 4% On-road POC concentration decrease: dispersion by wind & no significant surrounding emission sources. Off-road & other. POC concentration increase: balance with on-road & POC transport from surrounding sources.

  14. Conclusion and future work • The tagged species method implemented in AURAMS verifies well the mass conservation and hypotheses (linearity) of primary chemistry processes. • The method’s application is promising for: • (1) Detailed analysis of pollution in Canadian cities • (2) Assessment studies of specific sources (e.g. transportation) - Code optimization is underway for possible future long-term (annual) runs.

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