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首页> 外文期刊>The Science of the Total Environment >A new method to compare vehicle emissions measured by remote sensing and laboratory testing: High-emitters and potential implications for emission inventories
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A new method to compare vehicle emissions measured by remote sensing and laboratory testing: High-emitters and potential implications for emission inventories

机译：一种比较通过遥感和实验室测试测得的车辆排放量的新方法：高排放量及其对排放清单的潜在影响

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A new method is presented which is designed to investigate whether laboratory test data used in the development of vehicle emission models adequately reflects emission distributions, and in particular the influence of high-emitting vehicles. The method includes the computation of a 'high-emitter' or 'emission distribution' correction factor for use in emission inventories. In order to make a valid comparison we control for a number of factors such as vehicle technology, measurement technique and driving conditions and use a variable called 'Pollution Index' (g/kg). Our investigation into one vehicle class has shown that laboratory and remote sensing data are substantially different for CO, HC and NO_X emissions, both in terms of their distributions as well as in their mean and 99-percentile values. Given that the remote sensing data has larger mean values for these pollutants, the analysis suggests that high-emitting vehicles may not be adequately captured in the laboratory test data. The paper presents two different methods for the computation of weighted correction factors for use in emission inventories based on laboratory test data: one using mean values for six 'power bins' and one using multivariate regression functions. The computed correction factors are substantial leading to an increase for laboratory-based emission factors with a factor of 1.7-1.9 for CO, 1.3-1.6 for HC and 1.4-1.7 for NO_X (actual value depending on the method). However, it also clear that there are points that require further examination before these correction factors should be applied. One important step will be to include a comparison with other types of validation studies such as tunnel studies and near-road air quality assessments to examine if these correction factors are confirmed. If so, we would recommend using the correction factors in emission inventories for motor vehicles.
机译：提出了一种新方法，旨在调查在开发车辆排放模型时使用的实验室测试数据是否充分反映了排放分布，尤其是高排放车辆的影响。该方法包括计算用于排放清单的“高排放”或“排放分布”校正因子。为了进行有效的比较，我们控制许多因素，例如车辆技术，测量技术和驾驶条件，并使用一个称为“污染指数”（g / kg）的变量。我们对一种车辆类别的调查表明，就CO，HC和NO_X排放而言，实验室和遥感数据的分布，均值和99％均存在很大差异。鉴于遥感数据对这些污染物的平均值较高，分析表明，实验室测试数据可能无法充分捕获高排放车辆。本文介绍了两种基于实验室测试数据的排放清单加权校正因子的计算方法：一种是使用六个“电源箱”的平均值，另一种是使用多元回归函数。计算得出的校正因子非常重要，导致基于实验室的排放因子增加，CO因子为1.7-1.9，HC因子为1.3-1.6，NO_X因子为1.4-1.7（实际值取决于方法）。但是，也很清楚，在应用这些校正因子之前，有些点需要进一步检查。一个重要步骤将是与其他类型的验证研究（例如隧道研究和近路空气质量评估）进行比较，以检查这些校正因子是否得到确认。如果是这样，我们建议在机动车的排放清单中使用校正因子。

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