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An estimation of heavy-duty vehicle fleet CO_2 emissions based on sampled data

机译：基于采样数据的重型车队CO_2排放的估计

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Certification and monitoring of heavy vehicle CO2 emissions in several countries are based on individual vehicle simulation. Smaller fleet subsets can be used for accurate fleet-level results while preserving the characteristics of the underlying fleet-emissions distributions. The paper focuses on three approaches to capture fleet CO2 emissions: a) sampling directly from the fleet-data, b) sampling from data of individual vehicle components and c) using key statistics regarding the fleet composition that are available. The first and second approach deliver marginal divergences of the mean, between 1.1 and 2.1% and below 2.7 respectively, preserving the characteristics of the distribution. The third deviated by up to 5%, but lacked the detailed characteristics of the underlying statistical distribution. All three are useful when setting up fleet-wide monitoring schemes where detailed data are not available and to investigate the potential CO2 savings of various future fleet compositions, and scenarios regarding the diffusion of different types of technologies.
机译：几个国家的重型车辆二氧化碳排放的认证和监测基于个人车辆模拟。较小的车队子集可用于准确的舰队级结果，同时保持潜在的舰队排放分布的特点。本文专注于捕获舰队二氧化碳排放的三种方法：a）使用关于可用的舰队组合物的关键统计数据，从舰队数据，b）从舰队数据和c）的数据采样。第一和第二种方法分别递送平均值的边缘分歧，分别为1.1至2.1％至2.7以下，保持分布的特性。第三次偏离达5％，但缺乏潜在统计分布的详细特征。所有三个都很有用，当建立不可用的船队范围的监控方案，并调查各种未来舰队组合物的潜在二氧化碳节省的潜在二氧化碳组成，以及关于不同类型技术的扩散的情景。

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