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首页> 外文期刊>Energy Policy >Implications of uncertainty on regional CO_2 mitigation policies for the U.S. onroad sector based on a high-resolution emissions estimate
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Implications of uncertainty on regional CO_2 mitigation policies for the U.S. onroad sector based on a high-resolution emissions estimate

机译：基于高分辨率排放估算的不确定性对美国公路部门的区域CO_2减排政策的影响

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摘要

In this study we present onroad fossil fuel CO_2 emissions estimated by the Vulcan Project, an effort quantifying fossil fuel CO_2 emissions for the U.S. in high spatial and temporal resolution. This high-resolution data, aggregated at the state-level and classified in broad road and vehicle type categories, is compared to a commonly used national-average approach. We find that the use of national averages incurs state-level biases for road groupings that are almost twice as large as for vehicle groupings. The uncertainty for all groups exceeds the bias, and both quantities are positively correlated with total state emissions. States with the largest emissions totals are typically similar to one another in terms of emissions fraction distribution across road and vehicle groups, while smaller-emitting states have a wider range of variation in all groups. Uncertainties in reduction estimates as large as ± 60% corresponding to + 0.2 MtC are found for a national-average emissions mitigation strategy focused on a 10% emissions reduction from a single vehicle class, such as passenger gas vehicles or heavy diesel trucks. Recommendations are made for reducing CO_2 emissions uncertainty by addressing its main drivers: VMT and fuel efficiency uncertainty.
机译：在这项研究中，我们介绍了由Vulcan项目估算的道路上化石燃料的CO_2排放量，该工作旨在量化美国在高时空分辨率下的化石燃料的CO_2排放量。将该高分辨率数据在州一级汇总并分类为广泛的道路和车辆类型类别，然后将其与常用的全国平均方法进行比较。我们发现，使用全国平均水平会导致州级偏向的道路分组几乎是车辆分组的两倍。所有组的不确定性都超过了偏差，并且两个数量都与国家总排放量呈正相关。就道路和车辆类别的排放分数分布而言，排放总量最大的州通常彼此相似，而排放量较小的州在所有类别中的变化范围更大。对于全国平均减排策略而言，减少排放估算值的不确定性高达±60％，相当于+ 0.2 MtC，该策略的重点是将单一车辆类别（如乘用汽油车或重型柴油卡车）的排放减少10％。为解决CO_2排放的不确定性，提出了一些建议，以解决其主要驱动因素：VMT和燃油效率的不确定性。

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