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基于LMDI模型的交通运输业碳排放影响因素研究——以山东省为例
Research on the Influencing Factors of Carbon Emission in the Transportation Industry Based on LMDI Model—Taking Shandong Province as an Example

DOI: 10.12677/ojtt.2024.136041, PP. 379-387

Keywords: 交通碳排放量,影响因素,碳达峰,LMDI模型
Transportation Carbon Emissions
, Influencing Factors, Carbon Peaking, LMDI Model

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Abstract:

交通运输业是全球第二大碳排放源,为研究交通碳排放影响因素及未来发展形式,以达到交通运输业实现碳达峰的目的。本文以山东省为例,利用“自上而下”的方法计算山东省2014~2022年交通运输业的碳排放量,并构建LMDI模型,对交通运输碳排放的各项驱动因素进行分解,确定显著性明显的影响因素。研究表明:2014~2022年山东交通碳排放量受疫情影响呈先增后减的趋势,其中汽油、柴油能源消耗量占比分别为10%和43%;能源结构、能源强度、产业结构对山东省交通运输业碳排放的增加起抑制作用,经济产出、人口规模对山东省交通运输业碳排放的增加起促进作用;为实现碳达峰目标,山东省需要采取积极措施以降低交通运输业的碳排放量。
The transportation industry is the second largest source of carbon emissions in the world, and the research on the influencing factors and future development forms of transportation carbon emissions is to achieve the goal of carbon peak in the transportation industry. Taking Shandong Province as an example, this paper uses the “top-down” method to calculate the carbon emissions of the transportation industry in Shandong Province from 2014 to 2022, and constructs an LMDI model to decompose the driving factors of transportation carbon emissions and identify significant influencing factors. The results show that from 2014 to 2022, the carbon emissions of Shandong’s transportation will increase first and then decrease due to the impact of the epidemic, of which gasoline and diesel energy consumption will account for 10% and 43% respectively. Energy structure, energy intensity and industrial structure inhibit the increase of carbon emissions of the transportation industry in Shandong Province, and economic output and population size play a role in promoting the increase of carbon emissions of the transportation industry in Shandong Province. To achieve the carbon peak goal, Shandong Province needs to take proactive measures to reduce carbon emissions from the transportation sector.

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