Distance-based emission factors from vehicle emission remote sensing measurements.
Jack Davison, Yoann Bernard, Jens Borken-Kleefeld, Naomi J Farren, Stefan Hausberger, Åke Sjödin, James E Tate, Adam R Vaughan, David C Carslaw
Author Information
Jack Davison: Wolfson Atmospheric Chemistry Laboratories, University of York, York, United Kingdom. Electronic address: jd1184@york.ac.uk.
Yoann Bernard: International Council on Clean Transportation, Washington, United States.
Jens Borken-Kleefeld: International Institute for Applied Systems Analysis, Laxenburg, Austria.
Naomi J Farren: Wolfson Atmospheric Chemistry Laboratories, University of York, York, United Kingdom.
Stefan Hausberger: Institute for Internal Combustion Engines and Thermodynamic, TUG, University of Technology, Graz, Austria.
Åke Sjödin: IVL Swedish Environmental Research Institute, Stockholm, Sweden.
James E Tate: Institute for Transport Studies, University of Leeds, Leeds, United Kingdom.
Adam R Vaughan: Wolfson Atmospheric Chemistry Laboratories, University of York, York, United Kingdom.
David C Carslaw: Wolfson Atmospheric Chemistry Laboratories, University of York, York, United Kingdom; Ricardo Energy & Environment, Harwell, Oxfordshire, United Kingdom. Electronic address: david.carslaw@york.ac.uk.
Vehicle emission remote sensing has the potential to provide detailed emissions information at a highly disaggregated level owing to the ability to measure thousands of vehicles in a single day. Fundamentally, vehicle emission remote sensing provides a direct measure of the molar volume ratio of a pollutant to carbon dioxide, from which fuel-based emissions factors can readily be calculated. However, vehicle emissions are more commonly expressed in emission per unit distance travelled e.g. grams per km or mile. To express vehicle emission remote sensing data in this way requires an estimate of the fuel consumption at the time of the emission measurement. In this paper, an approach is developed based on vehicle specific power that uses commonly measured or easily obtainable vehicle information such as vehicle speed, acceleration and mass. We test the approach against 55 independent comprehensive PEMS measurements for Euro 5 and 6 gasoline and diesel vehicles over a wide range of driving conditions and find good agreement between the method and PEMS data. The method is applied to individual vehicle model types to quantify distance-based emission factors. The method will be appropriate for application to larger vehicle emission remote sensing databases, thus extending real-world distance-based vehicle emissions information.
