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Assessing carbon emissions from road transport through traffic flow estimators

机译:通过交通流量估算器评估道路运输中的碳排放

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Carbon emissions from road transport are one of the main issues related to modern transport planning. To address them adequately, the acquisition of reliable data about traffic flow is an essential prerequisite. However, the large quantity and the heterogeneity of available information often cause problems; missing or incomplete data are one of the most critical aspects. This paper discusses how technology handles imperfect information in order to obtain more accurate quantification of CO2 emissions. First, an analysis of single estimators and combination models is provided, highlighting their main characteristics. Then, the TANINO model (Tool for the Analysis of Non-conservative Carbon Emissions In TraNspOrt) is presented, jointly developed at the University of Seville and at the IUAV University of Venice. It consists of two different modules: the first is a combination model that optimizes the results of three traffic flow single estimators, while the second is a macro-model of carbon evaluation, which takes into account road infrastructure, vehicle type and traffic conditions. TANINO is then tested to calculate CO2 emissions along the ring road of the Spanish city of Seville, showing its more efficient performance, compared to the single estimators normally adopted for such aims. Transport planning can benefit from the adequate knowledge of traffic flows and related CO2 emissions, since it allows a more reliable monitoring of the progresses granted by specific carbon policies.
机译:公路运输产生的碳排放是与现代交通规划有关的主要问题之一。为了充分解决这些问题,获取有关流量的可靠数据是必不可少的前提。但是,可用信息的数量庞大且种类繁多,经常会引起问题。数据丢失或不完整是最关键的方面之一。本文讨论了技术如何处理不完善的信息,以便更准确地量化CO2排放。首先,提供了对单个估计量和组合模型的分析,突出了它们的主要特征。然后,提出了由塞维利亚大学和威尼斯IUAV大学联合开发的TANINO模型(用于分析TraNspOrt中非保守碳排放的工具)。它由两个不同的模块组成:第一个是组合模型,用于优化三个交通流量单个估算器的结果,而第二个是碳评估的宏观模型,其中考虑了道路基础设施,车辆类型和交通状况。然后,对TANINO进行了测试,以计算西班牙塞维利亚市环路上的CO2排放量,与通常用于此目的的单个估算器相比,它的效率更高。交通规划可以从对交通流量和相关的CO2排放的充分了解中受益,因为它可以更可靠地监视特定碳政策所授予的进度。

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