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Comparison of the Particulate Matter Index and Particulate Evaluation Index Numbers Calculated by Detailed Hydrocarbon Analysis by Gas Chromatography (Enhanced ASTM D6730) and Vacuum Ultraviolet Paraffin, Isoparaffin, Olefin, Naphthene, and Aromatic Analysis (ASTM D8071)
Technical Paper
2021-01-5070
ISSN: 0148-7191, e-ISSN: 2688-3627
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Automotive Technical Papers
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English
Abstract
The Particulate Matter Index (PMI) is a tool that provides an indication of a fuel’s tendency to produce Particulate Matter (PM) emissions. Currently, the index is being used by various fuel laboratories and the Automotive OEMs as a tool to understand the gasoline fuel’s impact on both PM from engine hardware and vehicle-out emissions. In addition, a newer index that could be used to give an indication of the PM tendency of the gasoline range fuels, called the Particulate Evaluation Index (PEI), is shown to have a good correlation to PMI. The data used in those indices are collected from chemical analytical methods. This paper will compare gas chromatography (GC) methods used by three laboratories and discuss how the different techniques may affect the PMI and PEI calculation. Data from two fuel laboratories running an Enhanced ASTM D6730 method will be compared to the paraffin, isoparaffin, olefin, naphthene, or aromatic (PIONA) data from a modified ASTM D8071 method using a newly developed vacuum ultraviolet (VUV) detector from VUV Analytics. While values do trend together, they are not equivalent. The possible reasons for this are explored, and some recommendations are made for future work.
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Chapman, E., Salyers, J., Wispinski, D., Scussel, M. et al., "Comparison of the Particulate Matter Index and Particulate Evaluation Index Numbers Calculated by Detailed Hydrocarbon Analysis by Gas Chromatography (Enhanced ASTM D6730) and Vacuum Ultraviolet Paraffin, Isoparaffin, Olefin, Naphthene, and Aromatic Analysis (ASTM D8071)," SAE Technical Paper 2021-01-5070, 2021, https://doi.org/10.4271/2021-01-5070.Data Sets - Support Documents
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References
- 2018 www.ccacoalition.org/en/news/china-vi-emissions-standard-milestone-global-transition-soot-free-vehicles
- Karavalakis , G. , Durbin , T.D. , Yang , J. , Ventura , L. et al. Fuel Effects on PM Emissions from Different Vehicle/Engine Configurations: A Literature Review SAE Technical Paper 2018-01-0349 2018 https://doi.org/10.4271/2018-01-0349
- Aikawa , K. , Sakurai , T. , and Jetter , J. Development of a Predictive Model for Gasoline Vehicle Particulate Matter Emissions SAE Int. J. Fuels Lubr. 3 2 2010 610 622 https://doi.org/10.4271/2010-01-2115
- Fatouraie , M. , Frommherz , M. , Mosburger , M. , Chapman , E. et al. Investigation of the Impact of Fuel Properties on Particulate Number Emission of a Modern Gasoline Direct Injection Engine SAE Technical Paper 2018-01-0358 2018 https://doi.org/10.4271/2018-01-0358
- Chapman , E. , Winston-Galant , M. , Geng , P. , Latigo , R. et al. Alternative Fuel Property Correlations to the Honda Particulate Matter Index (PMI) SAE Technical Paper 2016-01-2250 2016 https://doi.org/10.4271/2016-01-2250
- Wittmann , J. and Menger , L. Novel Index for Evaluation of Particle Formation Tendencies of Fuels with Different Chemical Compositions SAE Int. J. Fuels Lubr. 10 3 2017 690 697 https://doi.org/10.4271/2017-01-9380
- Vuk , C. and Vander Griend , S.J. Fuel Property Effects on Particulates in Spark Ignition Engines SAE Technical Paper 2013-01-1124 2013 https://doi.org/10.4271/2013-01-1124
- Chapman , E. , Winston-Galant , M. , Geng , P. , and Pryor , S. Development of an Alternative Predictive Model for Gasoline Vehicle Particulate Matter and Particulate Number SAE Technical Paper 2019-01-1184 2019 https://doi.org/10.4271/2019-01-1184
- Chapman , E. , Winston-Galant , M. , Geng , P. , and Konzack , A. Global Market Fuel Review Using Fuel Particulate Emission Correlation Indices SAE Technical Paper 2016-01-2251 2016 https://doi.org/10.4271/2016-01-2251
- Chapman , E. , Geng , P. , Zhao , Y. , Gong , J. et al. China Market Gasoline Range Fuel Review using Fuel Particulate Emission Correlation Indices SAE Technical Paper 2017-01-2401 2017 https://doi.org/10.4271/2017-01-2401
- ASTM D6729-20 2020 www.astm.org
- Coordinating Research Council, Advanced Vehicle Fuels & Lubricants Committee 2018
- ASTM D6730-21 2021 www.astm.org
- ASTM D5580-21 2021 www.astm.org
- ASTM D5769-20 2020 www.astm.org
- ASTM D8071-20 2020 www.astm.org
- Coordinating Research Council, Emissions Committee/Real World Committee 2019
- ASTM D1319-20a 2020 www.astm.org
- ASTM D6839-21a 2021 www.astm.org
- Cochran , J. , Jameson , S. , Wispinski , D. , and Diekmann , J. Estimating Particulate Matter Index for Gasoline with Fast Gas Chromatography—Vacuum Ultraviolet Spectroscopy 2018 Gulf Coast Conference 2018 https://vuvanalytics.com/knowledge-base/estimating-pmi-w-gc-vuv-gcc3/