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作 者:陈文婕[1] 吴小刚 肖竹 CHEN Wenjie;WU Xiaogang;XIAO Zhu(Business College,Central South University of Forestry and Technology,Changsha 410004,Hunan,China;College of Computer Science and Electronic Engineering,Hunan University,Changsha 410082,Hunan,China)
机构地区:[1]中南林业科技大学商学院,中国湖南长沙410004 [2]湖南大学信息科学与工程学院,中国湖南长沙410082
出 处:《经济地理》2022年第7期44-52,共9页Economic Geography
基 金:国家社会科学基金项目(19CGL043)。
摘 要:“双碳”目标的实现与低碳经济发展都要求重点关注道路交通碳减排问题。文章首先以私家车轨迹数据为切入口,通过逆地理编码、BP神经网络与广义回归神经网络(GRNN)的仿真对比,对四大经济区域私家车碳排放量进行预测,发现各区域按照道路交通碳排放量排序,由高到低依次为东部、西部、中部和东北部区域;其次,模拟不同碳税情景,基于效率、效果和公平三重视角构建指标体系评估四大经济区域道路交通领域减排潜力,发现不同碳税情景下,东部道路交通领域减排潜力最优,各区域道路交通领域减排潜力差距较大,并且随着税率的增加,东部、中部和西部呈上升趋势,东北部呈下降趋势;最后,针对各区域道路交通领域减排潜力差异,提出政策建议。The emission reduction of road traffic is an important way to realize the'carbon peak and neutrality'target and the low-carbon economic development.Firstly,this paper takes the urban private vehicle trajectory data as the starting point,uses reverse geocoding,BP neural network and generalized regression neural network(GRNN)for simulation comparison,and predicts the carbon emission of private vehicle in major economic regions.It is found that the carbon emission of road traffic is highest in the eastern region,and the following are in the western region,central region and northeast region.Secondly,different carbon tax scenarios are simulated to evaluate the emission reduction potential of road traffic in the four major economic regions from the perspectives of equity,efficiency and effect.In terms of different carbon tax scenarios,it is found that it has the best emission reduction potential in the eastern region,and the emission reduction potential of road traffic in different regions varies greatly.Moreover,with the increase of tax rate,it shows an upward trend in the eastern,central and western regions,while it shows a downward trend in the northeast region.Finally,according to the difference of road traffic emission-reduction potential in different regions,some policy proposals are put forward.
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