Energy consumption and greenhouse gas emissions of diesel/LNG heavy-duty vehicle fleets in China based on a bottom-up model analysis
Energy consumption and greenhouse gas emissions of diesel/LNG heavy-duty vehicle fleets in China based on a bottom-up model analysis
复制标题
基于自下而上模型分析的中国柴油/LNG重型车能源消耗和温室气体排放
DOI：
10.1016/j.energy.2017.09.011
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发表时间：
2017
期刊：
影响因子：
9
通讯作者：
Wang Cheng
中科院分区：
文献类型：
--
作者：
Song Hongqing;Ou Xunmin;Yuan Jiehui;Yu Mingxu;Wang Cheng
结合中国柴油/液化天然气（LNG）重型汽车（HDV）的实时燃料消耗率数据、实际省级柴油/LNG重型汽车保有量数据以及针对中国环境指定的清华-LCA模型（TLCAM）的生命周期库存数据库，进行生命周期分析（LCA）。结果表明，LNG HDV的直接能耗和生命周期能耗（MJ）分别比柴油HDV高出约7.4%和6.2%，而在中国，如果用LNG HDV替代柴油HDV，估计生命周期的温室气体排放量将减少约8.0%。由于中国越来越多地使用LNG作为HDV燃料（即，截至2015年，液化天然气替代柴油的总排放量约为1600万吨（2015年约为46亿立方米天然气），液化天然气替代柴油的总排放量约为1600万吨，于2006年至2015年为HDV车队减少了600万吨二氧化碳当量的温室气体排放。鉴于2015年HDV车队约占中国所有温室气体排放量的6.1%，到2020年，增加LNG HDV数量可使温室气体减排量增加约650万至910万吨二氧化碳当量。
The life-cycle analysis (LCA) is conducted with a combination of real-time fuel consumption rate data for diesel/liquefied natural gas (LNG) heavy-duty vehicles (HDVs) in China, actual provincial diesel/LNG HDV population data, and a life-cycle inventory database for the Tsinghua-LCA Model (TLCAM) specified for the context of China. The results indicate that direct energy consumption and the life-cycle energy use (MJ) of an LNG HDV are approximately 7.4% and 6.2% higher than that of a comparable diesel HDV, whereas an approximate 8.0% reduction in the life cycle of GHG emissions is estimated if diesel HDVs are replaced with LNG HDVs in China. Due to the increasing use of LNG as an HDV fuel in China (i.e., approximately 4.6 billion cubic metres of natural gas in 2015), the accumulated diesel fuel substituted with LNG was approximately 16 million tons, which generated a GHG emission reduction of 6 million tons of CO2equivalent in the HDV fleet from 2006 to 2015. Given that the HDV fleet contributed approximately 6.1% of all GHG emissions in China in 2015, growing the LNG HDV population can increase GHG emission reduction by an approximate range of 6.5–9.1 million tons of CO2equivalent by 2020.