SS118.1-2 Correlation of diesel engine horsepower with carbon monoxide emissions and diesel exhaust particle emissions

Monday, March 19, 2012: 14:35
Costa Maya 4 (Cancun Center)
Nigel N. Clark
Particulate matter (PM) from diesel engines are quantified less than other emissions because of complexities related to exhaust dilution required for particle formation prior to particle collection. The lack of PM emissions data has driven interest in correlations to estimate PM mass in terms of more readily measured or available parameters. Since PM from diesel engines consists primarily of elemental and organic carbon, there are qualitative combustion arguments that PM emissions may correlate with the production of carbon monoxide (CO) and hydrocarbon emissions. Prior studies have explored the use of continuously measured CO as a surrogate to distribute cycle-averaged PM over a transient cycle. Data sets for a wide variety of on-road and nonroad diesel engines have been explored to determine whether CO-PM relationships hold true across a range of technologies, vocations and fuel types. Reasonable correlation of PM and CO was observed for selected specific engines but analysis showed that quantitative prediction of PM emissions based on CO across engine technologies, duty cycles, and fuel types results in significant error. Correlation of CO and PM data from 54 trucks tested over the same driving schedule at the same test weight yielded a coefficient of determination (R2) of 0.29 overall, 0.17 for tractors up to and including the 1993 model year (higher PM standard), and 0.14 for trucks from 1994 to 2004 (pre-diesel particulate filter). Similarly, analysis of nonroad engine data did not yield strong correlation. Specific cases for diesel oxidation catalyst equipped engines and malfunctioning engines were also considered. PM was also compared with carbon dioxide emissions as they are a surrogate for engine power and showed duty cycle dependency. The conclusion is that it is difficult to support quantitative correlations to predict PM emissions over an ensemble of engines and engine technologies.