首页|东部某省交通运输领域碳排放影响因素分解与达峰预测

东部某省交通运输领域碳排放影响因素分解与达峰预测

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目的:省域交通运输是CO2排放的重要来源之一.为加速实现我国的双碳目标,本文以东部某省为例,研究交通运输领域影响CO2排放的因素,对碳达峰进行了预测.方法:首先通过LMDI模型确定交通运输领域碳排放的主要影响因素,然后根据灰色模型、Logistic人口预测模型及多元回归模型对交通基本参数进行预测,最后通过情景设定及参数设置,运用LEAP模型分析了 2022-2050年不同情景的CO2排放趋势.结果:经济和人口的发展是该地区交通运输碳排放增长的主要因素;基准情景下CO2排放量将持续增长,绿色情景、理想情景的CO2排放量分别在2043年、2039年达到峰值8 219.9万t和4 344.2万t.结论:东部某省交通运输领域应进一步加大减排力度,尽快实现交通碳达峰.上述研究为交通运输领域碳减排政策的制定奠定了理论基础.
Decomposition of influencing factors of carbon emissions and peaking prediction in the transportation sector of an eastern province in China
Aims:Provincial transportation is one of the important sources of CO2 emissions.To accelerate the achievement of China's dual carbon goals,we took an eastern province as an example to study the factors that affected CO2 emissions in the transportation sector and predicted the peak of carbon emissions.Methods:Firstly,the LMDI model was used to determine the main influencing factors of carbon emissions in the transportation sector.Then,the basic parameters of transportation were predicted using the grey model,the logistic population prediction model,and the multiple regression model.Finally,through scenario and parameter settings,the LEAP model was used to analyze the CO2 emission trends in different scenarios from 2022 to 2050.Results:Economic and demographic development was the main factor for the growth of carbon emissions from transportation in the region.CO2 emissions would continue to grow in the baseline scenario.The peaks would be at 82.199 million tons in 2043 and 43.442 million tons in 2039 for the green scenario and the ideal scenario,respectively.Conclusions:The transport sector in an eastern province should further increase its emission reduction efforts to achieve transport carbon peaking as soon as possible.The above study lays a theoretical foundation for the formulation of carbon emission reduction policies in the field of transportation.

carbon peaking forecaststransportationLMDI modelLEAP model

温丽雅、冯冬焕、黄月红、姚诗汝、戴之希、董文杰

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中国计量大学能源环境与安全工程学院,浙江杭州 310018

浙江省交通运输科学研究院,浙江杭州 311305

杭州市生态环境局临安分局,浙江杭州 311300

碳达峰预测 交通运输 LMDI模型 LEAP模型

浙江省教育厅科研项目浙江省科技计划

Y2022494222022C35068

2024

中国计量大学学报
中国计量学院

中国计量大学学报

CHSSCD
影响因子:0.357
ISSN:2096-2835
年,卷(期):2024.35(1)
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