文献类型：期刊文献

中文题名：基于LMDI法和STIRPAT模型的贵州省道路交通业碳排放分析及预测

英文题名：Analysis and Prediction of Carbon Emissions from Road Traffic Industry in Guizhou Province Using LMDI Method and STIRPAT Model

作者：方宏萍 陈小草 刘俊 宋彩霞 王洪飞 韦小焕

第一作者：方宏萍

机构：[1]贵州理工学院资源与环境工程学院,贵州贵阳550025;[2]贵州省城乡规划设计研究院有限责任公司,贵州贵阳550081

第一机构：贵州理工学院资源与环境工程学院

年份：2026

卷号：39

期号：4

起止页码：853-860

中文期刊名：环境科学研究

外文期刊名：Research of Environmental Sciences

收录：;北大核心:【北大核心2023】；

基金：贵州理工学院高层次人才科研启动项目资助项目(No.2025GCC030);贵州省基础研究计划(自然科学类)(No.黔科合基础-ZK[2024]一般518)。

语种：中文

中文关键词：贵州省道路交通业;行驶里程法;LMDI模型;STIRPAT模型;碳排放量预测

外文关键词：transportation industry of Guizhou Province;travel mileage method;LMDI model;STIRPAT model;carbon emission forecast

摘要：贵州省道路交通业作为贵州省经济发展的重要支撑行业,其是否能完成碳达峰碳中和目标关乎贵州省经济的未来发展趋势。采用行驶里程法对2013-2023年贵州省道路交通业碳排放量进行估算,基于LMDI模型对碳排放量的影响因素进行分解,并构建STIRPAT模型对2025-2050年的碳排放量进行预测。结果表明:①2013-2023年贵州省道路交通业碳排放量总体呈上升趋势。在不同车辆类型的碳排放情况中,微小型客车碳排放量最高,而大型客车的碳排放量占比最小。②根据LMDI模型影响因素分析,人口规模变动效应对碳排放量的累积贡献率为53%,其对贵州省道路交通业碳排放有强烈的促进作用,而经济发展规模对道路交通业碳排放促进作用的影响力度较弱。③采用STIRPAT模型进行碳排放量预测,根据政府对低碳政策执行和管理力度的不同设定低、中、高发展模式,对人口、GDP和能源消费的增长速率进行预测。在3种模式中,低发展模式下的碳排放量预测值最高。3种模式的预测量均能在2030-2035年实现碳达峰,在2047-2050年实现碳中和,与我国碳达峰碳中和目标基本吻合。研究显示,人口规模变动效应是贵州省道路交通业碳排放的主要驱动因素,未来贵州省道路交通业的碳排放量整体呈先升后降的趋势。
Achieving carbon peaking and carbon neutrality in Guizhou Province′s road transport sector,a critical component of the provincial economy,will play a decisive role in shaping its future development trajectory.In this study,carbon emissions from the road transportation industry from 2013 to 2023 were estimated using the mileage-based method.The influencing factors of carbon emissions were decomposed using the LMDI model,and a STIRPAT model was constructed to predict the carbon emissions from 2025 to 2050.The results show that:(1)Carbon emissions of the road transportation industry in Guizhou Province exhibited an overall increasing trend from 2013 to 2023.Among different vehicle types,micro and small passenger cars contributed the largest share of carbon emissions,whereas large passenger cars accounted for the smallest proportion of carbon emissions.(2)According to the analysis of the influencing factors of the LMDI model,the cumulative contribution rate of the effect of population size change to carbon emissions is 53%,exerting a strong promoting effect on the carbon emissions in the road transportation industry in Guizhou Province.In contrast,the influence of economic development on the promoting effect of carbon emissions in the road transportation industry was relatively weak.(3)The STIRPAT model show that carbon emissions under the low-development scenario are the highest among the three scenarios.The varying degrees of government implementation and management of low-carbon policies may lead to different rates of development in the transportation industry.Therefore,low,medium and high development models are set to predict the growth rates of population,GDP and energy consumption.All three scenario models predict that China will achieve carbon peaking between 2030 and 2035 and reach carbon neutrality between 2047 and 2050,which is basically in line with China′s goals of carbon peaking and carbon neutrality.Overall,the results demonstrate that population size change is the primary driving force behind carbon emissions in the road and transportation industry in Guizhou Province.In the future,carbon emissions of the road and transportation industry in Guizhou Province are expected to follow a trajectory of initial growth followed by a gradual decline.