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Spatial disaggregation of traffic emission inventories in large cities using simplified top-down methods

机译:使用简化的自上而下方法对大城市交通排放清单进行空间分类

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摘要

Simple, inexpensive and accurate methods for assessing the spatial distribution of traffic emissions are badly needed for the environmental management in South American cities. In this study, various spatial disaggregation methods of traffic emissions of carbon monoxide are presented and evaluated for a large city (Santiago de Chile). Previous methods have used a simplified road network as a proxy for deriving spatial patterns of emissions. However, these approaches resulted in underestimation of emissions in urban centers, industrial zones and highly loaded roads, as well as overestimation in residential zones. Here we modify these methods by adding data correlated with the emissions (e.g. traffic counts, vehicles mean speed, road capacity) solving partially or completely the indicated problems. After an accuracy-simplicity analysis two methodologies stand out over the others: using traffic count classification and using a land use map, both combined with a simplified road network. Both are top-down approaches that correlate well (~0.9) with the reference emissions and capture emission peaks (within 30% relative error). Hence the proposed changes allow an improved balance between accuracy and costs (monetary, availability of data and time to obtain data).
机译:南美城市的环境管理迫切需要简单,廉价和准确的方法来评估交通排放的空间分布。在这项研究中,提出并评估了一个大城市(智利圣地亚哥)的一氧化碳交通排放量的各种空间分解方法。先前的方法已使用简化的道路网络作为推导排放空间模式的代理。然而,这些方法导致低估了城市中心,工业区和高负荷道路的排放,以及高估了居民区的排放。在这里,我们通过添加与排放相关的数据(例如交通流量,车辆平均速度,道路通行能力)来修改这些方法,以部分或完全解决所指出的问题。经过准确性-简单性分析后,两种方法在其他方法中脱颖而出:使用交通流量分类和使用土地利用图,两者均与简化的道路网络相结合。两者都是自上而下的方法,与参考排放量相关性很好(〜0.9),并捕获了排放峰值(相对误差在30%以内)。因此,建议的更改可以在准确性和成本(货币,数据可用性和获取数据的时间)之间实现更好的平衡。

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