Natural Peak Characteristics and Peak Forecast of Carbon
 Emissions in Transportation Industry

doi:10.16097/j.cnki.1009-6744.2024.02.004

Abstract

Abstract: The peak of carbon emissions in the transportation industry is a natural long-term evolutionary process. In order to study the process of carbon peaking in China's transportation industry, this paper adopts the international analogy method, selects typical foreign countries, and compares the time of the peaks of the overall national carbon emissions, transportation industry carbon emissions, and converted turnover. The natural peak characteristics of transportation industry carbon emission are analyzed and the time of the natural peaks of carbon emissions in China's transportation industry is predicted according to transportation demand forecast. Then, the STIRPAT (Stochastic Impacts by Regression on Population, Affluence, and Technology) prediction model is constructed by introducing the core influencing factors such as carbon emissions per unit of converted turnover and the ratio of railroad to road freight transportation. Finally, through analogical analysis and model prediction, the time and volume of peak carbon emissions of China's transportation sector are obtained. The results of the international analogy show that there is no clear causal relationship between the peak carbon emissions of the transportation industry and the national peak carbon emissions, but it is closely related to the peak converted turnover, and the converted turnover reaches the peak or is close to the peak when the carbon emissions of the transportation industry reach the peak. It is predicted that China's converted turnover will reach a plateau period of 26 trillion ton-kilometers in about 2048. From the perspective of the international analogy, the time of the natural peak of China's carbon emissions from transportation is roughly roughly between 2040 and 2043. The STIRPAT model shows that the carbon emissions of China's transportation industry will increase by 1.201%, 0.259%, 0.454%, and-0.389%, respectively, for every 1% increase in urbanization rate, per capita GDP, carbon emissions per unit converted turnover, and railway- road freight ratio. Based on the combination prediction of international analogy and STIRPAT model, China's transportation industry will achieve peak carbon emissions in 2038-2040, with about 1.3 billion tons.

Key words: integrated transportation, carbon peaking, international analogy, STIRPAT model, peak prediction

摘要： 交通运输行业碳排放达峰是一项长期的自然演变过程。为研究中国交通运输行业碳达峰进程，本文首先采用国际类比法，选取国外典型国家，对比国家总体碳排放量、交通运输行业碳排放量以及换算周转量三者峰值出现的时间，分析交通运输行业碳排放的自然达峰特征，结合交通需求预测，预判中国交通运输行业碳排放自然达峰时间。然后，引入单位换算周转量碳排放量、铁路公路货运比等核心影响因素，构建交通运输碳排放STIRPAT(Stochastic Impacts by Regression on Population, Affluence, and Technology)预测模型。最后，通过类比分析与模型预测，得到中国交通运输行业碳达峰时间及峰值排放量。国际类比结果表明：交通运输行业碳达峰与国家碳达峰之间没有明确的因果关系，但与换算周转量达峰紧密相关，交通运输行业碳排放达峰时换算周转量达峰或接近峰值；预测中国换算周转量在2048年左右达到26万亿吨公里的平台期，从国际类比的角度判断，中国交通运输行业实现碳排放自然达峰时间约在2040—2043年。STIRPAT模型显示：城镇化率、人均GDP、单位换算周转量碳排放量、铁路公路货运比每增加1%，中国交通运输行业碳排放量将分别增加1.201%、0.259%、0.454%、-0.389%。基于国际类比与STIRPAT模型组合预测判断，中国交通运输行业将在2038—2040年实现碳排放达峰，峰值排放量约为13亿t。

关键词: 综合运输, 碳达峰, 国际类比, STIRPAT模型, 峰值预测

CLC Number:

YANGDong, LIYanhong, TIAN Chunlin. Natural Peak Characteristics and Peak Forecast of Carbon Emissions in Transportation Industry[J]. Journal of Transportation Systems Engineering and Information Technology, 2024, 24(2): 34-44.

杨东, 李艳红, 田春林. 交通运输行业碳排放自然达峰特征与峰值预测研究[J]. 交通运输系统工程与信息, 2024, 24(2): 34-44.

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Natural Peak Characteristics and Peak Forecast of Carbon Emissions in Transportation Industry

交通运输行业碳排放自然达峰特征与峰值预测研究

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