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Quantifying the temporal variation of the boreal wildfire smoke contribution to PM 2.5 in Halifax during the BORTAS-B m

Quantifying the temporal variation of the boreal wildfire smoke contribution to PM 2.5 in Halifax during the BORTAS-B mission using four receptor models. .

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Quantifying the temporal variation of the boreal wildfire smoke contribution to PM 2.5 in Halifax during the BORTAS-B m

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  1. Quantifying the temporal variation of the boreal wildfire smoke contribution to PM2.5 in Halifax during the BORTAS-B mission using four receptor models. Mark D. Gibson1, James Kuchta1, Lucy Chisholm2, Tom Duck3, Jason Hopper1, Stephen Beauchamp2, David Waugh2, Gavin King1, Jeffrey Pierce3/8, Zhengyan Li4, Richard Leaitch5, Tony J. Ward6Jan Haelssig1, Paul Palmer7 1Dalhousie University, Department of Process Engineering and Applied Science, Halifax, Nova Scotia, Canada2Environment Canada, Dartmouth, Nova Scotia, Canada. 3Dalhousie University, Department of Physics and Atmospheric Science, Halifax, Nova Scotia, Canada4Ocean University of China, College of Environmental Science and Engineering. 5Environment Canada, Toronto, Ontario, Canada, 6Centre for Environmental Health Sciences, University of Montana7School of GeoSciences, The University of Edinburgh, Edinburgh, UK.8Department of Atmospheric Physics, Colorado State, Colorado, US.Corresponding author: mark.gibson@dal.ca, http://afrg.peas.dal.ca

  2. Objective Quantifying the temporal variation of the boreal wildfire smoke contribution to PM2.5 in Halifax during the BORTAS-B mission

  3. 2x Thermo ChemCombsfor PM2.5 Speciation @ 10L/min(1x 47 mm pre-fired quartz and 1x 47 mm nylon filter) Continuous PM2.5 (TSI DustTrak) nephelometer Magee AethalometerContinuous black carbon Thermo Partisol 2025-dichot, 24-hr47 mm Teflon Filter PM2.5

  4. Environment Canada’s, Aerodyne, Aerosol Chemical Speciation Monitor ContinuousOrganic Matter

  5. Four Receptor Models Used 1. Absolute Principal Component Scores2. Pragmatic Mass Closure3. USEPA Chemical Mass Balance 4. USEPA Positive Matrix Factorization Details of models found > http://afrg.peas.dal.ca/publishing/

  6. Absolute Principal Component Scores Model Results

  7. Pragmatic Mass Closure Receptor Model Results

  8. USEPA Chemical Mass Balance Receptor Model Results

  9. USEPA Positive Matrix Factorization Receptor Model Results R2= 0.84n = 45

  10. Ensemble of daily NOAA HYSPLIT air mass back trajectories during BORTAS Marine air flow resulted very low PM2.5-woodsmoke contributions

  11. Ensemble of daily NOAA HYSPLIT air mass back trajectories during BORTAS These woodsmoke spikes were associated with NE airflow that crossed New Foundland and Cape Breton, en route to Halifax

  12. Ontario boreal forest fire woodsmoke event 22 July Ontario Forest Fire

  13. FLEXPART 5-DAY Air Parcel Forward Trajectory Model 17 July to 22 July 2011 Air parcel crosses large forest fire in Northern Ontario, eventually impacting Halifax, Nova Scotia

  14. FLEXPART Model of the Ontario forest fire smoke concentration directly above Halifax – 20 July to 22 July 2011

  15. USEPA PMF PM2.5 source apportionment during BORTAS-B

  16. Summary • APCS, PMC and CMB models can not predict total PM2.5 mass concentrations below 2.0 mg/m3 • USEPA PMF model able topredict total PM2.5 below 2.0 mg/m3 • The use of a woodsmoke chemical marker such as levoglucosan is critical when carrying out PM2.5 source apportionment studies of boreal forest wild fire smoke • USEPA PMF model was the best model for predicting the wildfire smoke (and other sources) contribution to PM2.5 in Halifax during BORTAS-B

  17. Next Steps • Paper in prep • Dalhousie Ground Station Paper(all observations)

  18. Acknowledgements • Professor Paul Palmer (BORTAS lead) University of Edinburgh, School of GeoSciences for funding project consumables via Philip LeverhulmePrize • Health Canada for the loan of the black carbon analyzer, DustTraks, ChemComb samplers and chemical analysis • Atmospheric Forensics Research Grouphttp://afrg.peas.dal.ca Photo courtesy of James Kuchta

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