CO<inf>2</inf> vehicular emission statistical analysis with instantaneous speed and acceleration as predictor variables

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Conference Proceeding
2013 International Conference on Control, Automation and Information Sciences, ICCAIS 2013, 2013, pp. 158 - 163
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Models for predicting vehicular emissions of carbon dioxide (CO 2) are usually insensitive to vehicle modes of operation (such as cruise, acceleration, deceleration, and idling) as they are based on the average speed of motor vehicles. In the present study, real world on-road second-by-second data are used to improve the accuracy of air quality models by considering modal emissions of CO2 in terms of vehicles' instantaneous speed and acceleration. A regression analysis approach is used with speed and acceleration as the predictor variables while CO2 emission factor as the outcome variable for vehicles manufactured in 2002 and 2008. The results show that there is significantly a linear relationship between CO2, speed and acceleration/deceleration in which speed, as compared to acceleration, has a stronger correlation with respect to the CO2 emission factor. Also, for 2002 and 2008 vehicles, every 1m/s increase in speed will emit respectively 0.041g/s and 0.034g/s CO2, whereas an increase in acceleration by 1m/s2 will produce 0.025g/s and 0.008g/s of CO2 emission in the case of constant predictors. While speed and acceleration are all significant predictors of CO2 emission, it is concluded from the magnitude of the t-statistics that speed has a greater impact than acceleration in predicting CO2 emission. © 2013 IEEE.
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