Wolfson Atmospheric Chemistry Laboratories, University of York, York, United Kingdom.
International Council on Clean Transportation, Washington, United States.
Sci Total Environ. 2020 Oct 15;739:139688. doi: 10.1016/j.scitotenv.2020.139688. Epub 2020 Jun 6.
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.
车辆排放遥测技术由于能够在一天内测量数千辆汽车，因此具有在高度细分的水平上提供详细排放信息的潜力。从根本上讲，车辆排放遥测技术直接测量污染物与二氧化碳的摩尔体积比，从中可以很容易地计算出基于燃料的排放因子。然而，车辆排放通常以单位行驶距离的排放量来表示，例如每公里或英里的克数。要以这种方式表示车辆排放遥测数据，需要估算排放测量时的燃料消耗。本文提出了一种基于车辆比功率的方法，该方法使用通常测量或易于获得的车辆信息，例如车辆速度、加速度和质量。我们针对 55 个独立的全面 PEMS 测量值进行了测试，这些测量值涵盖了广泛的驾驶条件下的欧 5 和 6 汽油和柴油车辆，结果表明该方法与 PEMS 数据之间具有良好的一致性。该方法应用于单个车辆模型类型，以量化基于距离的排放因子。该方法将适用于更大的车辆排放遥测数据库的应用，从而扩展了实际基于距离的车辆排放信息。
