A Study to Measure the Chemical Characteristics of Particle Emissions from Biomass Burning Stoves
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1 A Study to Measure the Chemical Characteristics of Particle Emissions from Biomass Burning Stoves End of Summer Workshop, 2006 Dabrina Dutcher School of Public Health and Department of Mechanical Engineering University of Minnesota
2 Direct Emissions of Particulate Matter
3 Goals of the Study Goal 1: Measure chemical composition and associated parameters (size distribution and mass) of the particles emitted from wood and corn combustion. Goal 2: Compare chemical composition, size distribution and mass emissions from various types of fuel combusted : Hard wood: Oak, Birch Soft wood: Pine Corn Goal 3: Compare emissions characteristics.
4 It is of interest to characterize sources of particles in the atmosphere Aerosol particles are of critical importance in the atmosphere because of their effect on: Human Health Visibility Climate Change We need to understand contributions from various emission sources, eg: Anthropogenic, eg: combustion (gasoline, diesel, biomass, etc.) Natural, eg: sea-spray.
5 Schematic of Our Measurements Sample directly from chimney Lopi Wood Stove St. Croix Corn Stove Gas emissions (CO 2, CO, O 2, NO x ) Particle Mass Concentration (TEOM) Particle Size Distribution (SMPS) Particle Chemical Composition (ATOFMS)
6 Sampling from the Wood Stove
7 The Corn Stove
8 Gas Measurements Monitor #1 Monitor #2 Characterize combustion conditions Concentrations of: CO 2, CO, O 2, NO, NO 2 Two gas monitors to determine the dilution ratio Monitor #1 (TSI CA-Calc) measured raw emissions Monitor #2 (ECOM-AC) measured diluted emissions
9 Particle Mass Concentration TEOM: Thermal Electric Oscillating Microbalance PM2.5 mass emissions (mg/m 3 of exhaust sampled) Mass emission is a useful measure when comparing emissions from different sources
10 Particle Mass Concentration Oak Door Closed 14:58:02 14:53:02 14:48:02 14:43:02 14:38:02 14:33:02 14:19:02 14:14:02 14:09:02 14:04:02 13:59:02 13:54:02 13:49:02 13:44:02 13:39:02 13:34:02 13:29:02 13:24:02 13:19:02 13:14:02 13:09:02 13:04:02 12:59:02 12:39: Reloaded Wood Fire Lit time mass concentration (ug/m3)
11 17:25:02 Particle Mass Concentration Birch Choked Fire (vent) Door Closed 17:20:02 17:15:02 17:10:02 17:05:02 17:00:02 16:55:02 16:50:02 16:45:02 16:40:02 16:35:02 16:30:02 16:25:02 16:20: Fire Lit time mass concentration (ug/m3)
12 Particle Size Distribution SMPS: Scanning Mobility Particle Sizer Number of particles as a function of particle size nanometers (1 nanometer = 10-9 meters) Size distribution measured every 2.5 minutes Particle size determines many atmospheric and health effects
13 Particle Size Distribution 4.5E E+06 Pine (avg 11:40-12:45) Corn (avg 11:45-12:20) 3.5E+06 dn/dlogdp (#/cm3) 3.0E E E E E E E Dp (nm)
14 Particle Size Distribution 1.6E E+07 Oak (14:00) Oak (14:45 after adding wood) 1.2E+07 dn/dlogdp (#/cm3) 1.0E E E E E E Dp (nm)
15 Particle Chemical Composition ATOFMS: Aerosol Time-of-Flight Mass Spectrometer Size and chemical composition of individual particles, in real time Ash Soot Organic compounds
16 TSI 3800: Aerosol Time of Flight Mass Spectrometer - AKA Wallace Reflectron Aerodynamic Lens Sizing Lasers (532 nm) Ellipsoidal Mirrors PMT + ions - ions Microchannel Plate Ion Detectors Ionization/Desorption Laser (266 nm)
17 400 ATOFMS - Oak m/z :30 PM 4/25/2006 2:00 PM 2:30 PM 3:00 PM dat
18 400 ATOFMS - Pine m/z :30 AM 4/26/ :00 AM 11:30 AM 12:00 PM 12:30 PM 1:00 PM dat
19 ATOFMS Pine (sorted by particle size) 1.0 Relative Peak Area POS below 7.5 nm POS 7.5 to 10 nm POS 1 0 to 13.3 nm POS 17.8 to 23.7 nm POS 23.7 to 31.6 nm POS 31.6 to 42.2 nm POS 42.2 to 56.2 nm POS 56.2 to 75 nm POS 75 to 100 nm POS 100 to nm POS to nm POS to nm POS to nm POS to nm POS to nm POS to nm POS749.9 to 1000 nm POS 1000 to nm POS to nm m /z
20 ATOFMS - Corn m/z 200 K 3 SO 4 + K 2 HSO K 2 Cl 3 + K :00 AM 4/28/ :30 AM 11:00 AM 11:30 AM 12:00 PM 12:30 PM 1:00 PM 1:30 PM dat
21 400 ATOFMS - Corn m/z KCl 2 - SO :00 AM 4/28/ :30 AM 11:00 AM 11:30 AM 12:00 PM 12:30 PM 1:00 PM 1:30 PM dat CN -
22 Results? A great deal of good data was acquired Data analysis is underway and will require integration of the results from all of the instruments used
23 Acknowledgements Jeff and Milt, GREF for funding Deborah Gross, Joakim Pagels, Mark Stolzenburg, Peter McMurry Woodland Stoves and Fireplaces Peter Solac, Ted Palmer and coworkers TSI, Inc. (for loan of CA-Calc) University of Minnesota Center for Diesel Research (for loan of ECOM-AC) Fuels Emissions Engines
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