摘要
城市交通是城市发展的重要组成部分,但同时也是城市碳排放的重要来源。文章以西安市为例,通过自下而上算法中的行驶里程法和周转量法对该市2011~2020年的城市交通碳排放进行核算,并进一步计算了人均交通碳排放量和单位GDP交通碳排放量,进而探讨城市交通碳排放的影响因素和减排策略。研究表明,西安市总碳排放量在3200万吨上下浮动,交通碳排放量在299万吨上下浮动,人均交通碳排放量和单位GDP交通碳排放量总体呈现下降的趋势。为探究影响因素,本文采用LMDI模型从旅客周转量、货运周转量、人口和GDP四个纬度进行分解。结果表明,旅客周转量和货运周转量既有促进作用,也有抑制作用,人口和GDP均为正向效应。
Urban transportation is an integral part of urban development,yet it is also a significant source of carbon emissions in cities.Taking Xi'an as a case study,this article calculates the urban transportation carbon emissions from 2011 to 2020 using the bottom-up approach,employing methods such as vehicle miles traveled and turnover volume.It further calculates per capita transportation carbon emissions and carbon emissions per unit of GDP,aiming to explore the influencing factors and mitigation strategies for urban transportation carbon emissions.The research findings indicate that the total carbon emissions in Xi'an fluctuated around 32 million tons,with transportation carbon emissions fluctuating around 2.99 million tons.Per capita transportation carbon emissions and carbon emissions per unit of GDP generally show a downward trend.To explore the influencing factors,this study utilizes the Logarithmic Mean Divisia Index(LMDI)model to decompose the effects from four dimensions:passenger turnover,freight turnover,population,and GDP.The results indicate that passenger turnover and freight turnover exert both promoting and inhibiting effects,while population and GDP exhibit positive effects.
作者
贾育鑫
付晶燕
JIA Yuxin;FU Jingyan(Business School,University of Shanghai for Science and Technology,Shanghai 200093,China;China Academy of Urban Planning&Design,Beijing 100044,China)
出处
《智能计算机与应用》
2024年第11期163-167,共5页
Intelligent Computer and Applications
关键词
碳排放
自下而上
交通运输
LMDI
carbon emissions
bottom-up algorithms
transportation
LMDI
