Development of Local Emissions Rate Model for Light-Duty Gasoline Vehicles: Beijing Field Data and Patterns of Emissions Rates in EPA Simulator

A local emissions rate (ER) model is an important tool that is often combined with vehicle activity data in assessing the effect of traffic control strategies on emissions. Such a model is especially critical in developing countries where local emissions data are either unavailable or limited. This study sought to develop a local ER model for light-duty gasoline vehicles (LDGVs) based on limited emissions testing data from Beijing, emissions factors in the China vehicle emission model, and the regular patterns of ERs in the Motor Vehicle Emission Simulator (MOVES) program. To this end, the research team first analyzed the characteristics of vehicle emissions on the basis of field data collected in Beijing. Then the authors summarized the regular pattern of ERs for LDGVs embedded in the MOVES model and examined consistency of normalized ERs derived from Beijing and the MOVES program. The normalized mean square error was used to evaluate the level of consistency. When consistency was sufficiently high, the regular pattern of ERs in the MOVES program was used to fill the missing field emissions data. Development of the model involved four essential elements: (a) data-driven ERs, (b) a supplement for high-power operating modes, (c) modeling ERs of zero-mile-level emissions, and (d) development of a deterioration model of ERs. On the basis of the proposed model, a local database of ERs for LDGVs was established and applied to assess the emissions benefit of electronic toll collection lanes.

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

[2]  H. Frey,et al.  Effects of Errors on Vehicle Emission Rates from Portable Emissions Measurement Systems , 2013 .

[3]  Yu Zhou,et al.  Can Euro V heavy-duty diesel engines, diesel hybrid and alternative fuel technologies mitigate NOX emissions? New evidence from on-road tests of buses in China , 2014 .

[4]  Yu Zhou,et al.  Historic and future trends of vehicle emissions in Beijing, 1998–2020: A policy assessment for the most stringent vehicle emission control program in China , 2014 .

[5]  Kun Chen,et al.  Microscopic Traffic-Emission Simulation and Case Study for Evaluation of Traffic Control Strategies , 2007 .

[6]  Luo Wei-li Characteristics of Motor Vehicle Exhaust Emission in Guangzhou , 2012 .

[7]  Lei Yu,et al.  Sensitive analysis of emission rates in MOVES for developing site-specific emission database , 2014 .

[8]  He Wei Scheme Evaluation of Bus Lane Planning Considering Environmental Impact , 2010 .

[9]  Lei Yu,et al.  Emission Analysis at Toll Station Area in Beijing with Portable Emission Measurement System , 2008 .

[10]  Xiong Ying-ge Investigating Vehicular Energy Consumption and Emissions at Intersections with Micro-Simulation Models , 2010 .

[11]  Wang Meng Application of portable emission measurement system(PEMS) on the emission measurements of urban vehicles on-road , 2010 .

[12]  Song Guo-hua,et al.  Comparative Study of MOBILE and COPERT Emission Models Based on PEMS , 2011 .

[13]  H. Frey,et al.  Speed- and Facility-Specific Emission Estimates for On-Road Light-Duty Vehicles on the Basis of Real-World Speed Profiles , 2006 .

[14]  Lei Yu,et al.  Estimation of Fuel Efficiency of Road Traffic by Characterization of Vehicle-Specific Power and Speed Based on Floating Car Data , 2009 .

[15]  Lei Yu,et al.  Development of Speed Correction Factors Based on Speed-Specific Distributions of Vehicle Specific Power for Urban Restricted-Access Roadways , 2016 .

[16]  Ying Cheng,et al.  Optimized Adjustment of Speed Resolution and Time Alignment Data for Improving Emissions Estimations , 2016 .