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作 者:Zuoming Zhang Hongyang Su Wenbin Yao Fujian Wang Simon Hu Sheng Jin
机构地区:[1]Polytechnic Institute&Institute of Intelligent Transportation Systems,Zhejiang University,Hangzhou 310058,China [2]School of Civil Engineering and Architecture,Zhejiang Sci-Tech University,Hangzhou 310018,China [3]Institute of Intelligent Transportation Systems,College of Civil Engineering and Architecture,Zhejiang University,Hangzhou 310058,China [4]Zhejiang University/University of Illinois at Urbana-Champaign Institute(ZJU-UIUC Institute),Haining 314400,China [5]Alibaba-Zhejiang University Joint Research Institute of Frontier Technologies,Hangzhou 310027,China
出 处:《Fundamental Research》2024年第5期1025-1035,共11页自然科学基础研究(英文版)
基 金:supported by"Pioneer"and"Leading Goose"R&D Program of Zhejiang(2023C03155);the National Natural Science Foundation of China(72361137006,52131202,and 92046011);the Natural Science Foundation of Zhejiang Province(LR23E080002);Alibaba-Zhejiang University Joint Research Institute of Frontier Technologies.
摘 要:Carbon dioxide(CO_(2))from road traffic is a non-negligible part of global greenhouse gas(GHG)emissions,and it is a challenge for the world today to accurately estimate road traffic CO_(2)emissions and formulate effective emission reduction policies.Current emission inventories for vehicles have either low-resolution,or limited coverage,and they have not adequately focused on the CO_(2)emission produced by new energy vehicles(NEV)considering fuel life cycle.To fill the research gap,this paper proposed a framework of a high-resolution well-to-wheel(WTW)CO_(2)emission estimation for a full sample of vehicles and revealed the unique CO_(2)emission characteristics of different categories of vehicles combined with vehicle behavior.Based on this,the spatiotemporal characteristics and influencing factors of CO_(2)emissions were analyzed with the geographical and temporal weighted regression(GTWR)model.Finally,the CO_(2)emissions of vehicles under different scenarios are simulated to support the formulation of emission reduction policies.The results show that the distribution of vehicle CO_(2)emissions shows obvious heterogeneity in time,space,and vehicle category.By simply adjusting the existing NEV promotion policy,the emission reduction effect can be improved by 6.5%-13.5%under the same NEV penetration.If combined with changes in power generation structure,it can further release the emission reduction potential of NEVs,which can reduce the current CO_(2)emissions by 78.1%in the optimal scenario.
关 键 词:Carbon neutrality Well-to-wheel emission Emission characteristics License plate recognition data Geographical and temporal weighted regression model Emission reduction policy
分 类 号:O57[理学—粒子物理与原子核物理]
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