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A New Approach for Very Low Particulate Mass Emissions Measurement

Journal Article
ISSN: 1946-3936, e-ISSN: 1946-3944
Published April 08, 2013 by SAE International in United States
A New Approach for Very Low Particulate Mass Emissions Measurement
Citation: Bushkuhl, J., Silvis, W., Szente, J., and Maricq, M., "A New Approach for Very Low Particulate Mass Emissions Measurement," SAE Int. J. Engines 6(2):1152-1162, 2013,
Language: English


Pending reductions in light duty vehicle PM emissions standards from 10 to 3 mg/mi and below will push the limits of the gravimetric measurement method. At these levels the PM mass collected approaches the mass of non-particle gaseous species that adsorb onto the filter from exhaust and ambient air. This introduces an intrinsic lower limit to filter based measurement that is independent of improvements achieved in weighing metrology. The statistical variability of back-up filter measurements at these levels makes them an ineffective means for correcting the adsorption artifact. The proposed subtraction of a facility based estimate of the artifact will partially alleviate the mass bias from adsorption, but its impact on weighing variability remains a problem that can reach a significant fraction of the upcoming 3 and future 1 mg/mi standards. This paper proposes an improved PM mass method that combines the gravimetric filter approach with real time aerosol measurement. In this work we employ a photoacoustic soot sensor (PASS), which achieves a substantially better detection limit than filter weighing. PM emissions are recorded simultaneously by a Teflon filter and the PASS over the three phase FTP drive cycle. The weighted composite emission rate is determined as follows: Comparison of the net filter weight gain to the time integrated PASS signal serves to calibrate the latter to a gravimetric equivalent PM mass. The adjusted PASS data are then integrated for each test phase and combined with the proper weighting for the FTP average. By utilizing a single filter, this procedure achieves an approximately 3-fold decrease in artifact bias and 2-fold reduction in variability. It provides two additional advantages: a reduction in the time consuming step of filter weighing and time resolved data that can help improve low emissions development.