Identifying the effect of vehicle operating history on vehicle running emissions

Abstract This research aims to determine the overall effects that a vehicle's short-term operating history has on its subsequent emissions, and how Vehicle Specific Power (VSP)-based vehicle emission models could be improved to account for these effects. Current VSP-based emission models, such as the U.S. EPA's MOtor Vehicle Emission Simulator (MOVES), only predict emissions based on instantaneous vehicle activity and the corresponding VSP value; the past short-term vehicle operational activity is not taken into account (e.g., the last 10–20 s of operation). For example, instantaneous vehicle emissions could be affected by a hard acceleration vs. a deceleration event at that particular point in time. This paper attempts to determine the accuracy of VSP-based emission models, which may suffer due to the fact that the history effects are being overlooked. A number of experiments were carried out in order to determine the anomalies resulting from instantaneous estimation as opposed to taking short-term vehicle operating history into account. These experiments compare model estimates with actual emission measurements. A quantitative analysis shows that the higher power operating modes (such as modes 33, 35, 37, 38, and 40 in MOVES) had the greatest variability – sometimes in the range of 60–100% – due to the effects that vehicle operating history has on carbon monoxide (CO). Hydrocarbons (HC) in higher power operating modes also vary 40–60% depending on the driving cycle. For lower power operating modes (e.g., MOVES modes 1–30), the uncertainty for all pollutants was significantly less. It was also established that the carbon dioxide (CO 2 ) and nitrogen oxide (NO x ) estimations conducted by MOVES were least affected by the vehicle operational history effects compared with other emissions. As such, MOVES emission results are more accurate for mild to normal driving cycles, but there is greater uncertainty for higher power driving cycles.

[1]  Matthew Barth,et al.  Development and Application of an International Vehicle Emissions Model , 2005 .

[2]  Matthew Barth,et al.  Using Portable Emission Measurement Systems for Transportation Emissions Studies , 2010 .

[3]  Matthew Barth,et al.  Development of Comprehensive Modal Emissions Model: Operating Under Hot-Stabilized Conditions , 1997 .

[4]  Erika Louise Roesler Analysis of tailpipe particulate matter emission from a sampling of Kansas City vehicles , 2006 .

[5]  Kebin He,et al.  Characteristics of diesel truck emission in China based on portable emissions measurement systems. , 2009, Environmental science & technology.

[6]  Hui Guo,et al.  Evaluation of the International Vehicle Emission (IVE) model with on-road remote sensing measurements. , 2007, Journal of environmental sciences.

[7]  Tao Huai,et al.  The effect of fuel sulfur on NH3 and other emissions from 2000-2001 model year vehicles , 2004 .

[8]  José Luis Jiménez-Palacios,et al.  Understanding and quantifying motor vehicle emissions with vehicle specific power and TILDAS remote sensing , 1999 .

[9]  H. Oliver Gao,et al.  Diesel Particulate Matter Number Emissions: Evaluation of Existing Modal Emission Modeling Approaches , 2010 .

[10]  Matthew Barth,et al.  Modal Emissions Model for Heavy-Duty Diesel Vehicles , 2004 .

[11]  Kebin He,et al.  Comparison of vehicle activity and emission inventory between Beijing and Shanghai. , 2007, Journal of the Air & Waste Management Association.

[12]  Matthew Barth,et al.  Development of a Comprehensive Modal Emissions Model , 2000 .

[13]  Prakash Gajendran,et al.  A predictive tool for emissions from heavy-duty diesel vehicles. , 2003, Environmental science & technology.

[14]  Qingyu Zhang,et al.  Vehicle emission inventories projection based on dynamic emission factors: A case study of Hangzhou, China , 2008 .

[15]  Alan W. Gertler,et al.  Comparison of MOBILE4.1 and MOBILE5 predictions with measurements of vehicle emission factors in Fort McHenry and Tuscarora mountain tunnels , 1996 .

[16]  K S Nesamani,et al.  Estimation of automobile emissions and control strategies in India. , 2010, The Science of the total environment.

[17]  Haibo Zhai,et al.  A vehicle-specific power approach to speed- and facility-specific emissions estimates for diesel transit buses. , 2008, Environmental science & technology.

[18]  M. Barth,et al.  Vehicle specific power approach to estimating on-road NH3 emissions from light-duty vehicles. , 2005, Environmental science & technology.