资源科学 ›› 2019, Vol. 41 ›› Issue (10): 1824-1836.doi: 10.18402/resci.2019.10.06

• 能源与碳排放 • 上一篇    下一篇

五大交通运输方式碳达峰的经验分解与情景预测-----以东北三省为例

王勇1,2,韩舒婉1(),李嘉源3,李博1   

  1. 1. 东北财经大学统计学院,大连 116025
    2. 东北财经大学博士后科研流动站,大连 116025
    3. 大连海事大学轮机工程学院,大连116026
  • 收稿日期:2019-04-22 修回日期:2019-07-30 出版日期:2019-10-25 发布日期:2019-10-25
  • 通讯作者: 韩舒婉
  • 作者简介:王勇,男,山东临沂人,博士,副教授,硕士生导师,从事资源环境统计分析。E-mail: ywang@dufe.edu.cn
  • 基金资助:
    教育部人文社会科学研究青年项目(18YJC910013);辽宁省财政科研基金项目(重点课题18B010);辽宁省教育厅科研项目(LN2019Q48);国家社会科学基金项目(19FTJB004)

Empirical decomposition and forecast of peak carbon emissions of five major transportation modes:Taking the three provinces in Northeast China as examples

WANG Yong1,2,HAN Shuwan1(),LI Jiayuan3,LI Bo1   

  1. 1. School of Statistics, Dongbei University of Finance and Economics, Dalian 116025, China
    2. Postdoctoral Research Station, Dongbei University of Finance and Economics, Dalian 116025, China
    3. School of Marine Engineering, Dalian Maritime University, Dalian 116026, China
  • Received:2019-04-22 Revised:2019-07-30 Online:2019-10-25 Published:2019-10-25
  • Contact: HAN Shuwan

摘要:

交通业是国民经济发展和居民生活必需的基础产业之一,也是碳排放的主要来源之一。高能耗、高污染一直都是交通业的问题,有效控制交通业碳排放量,对于实现中国的碳排放达峰目标具有重要意义。本文以中国东北三省为研究区,对公路、铁路、航空、水路和管道5种不同交通运输方式的碳排放进行了细分研究。首先,使用广义迪氏指数(GDIM)模型分别考察了2005—2016年5种交通运输方式碳排放的影响因素,在此基础上使用蒙特卡洛模拟对2017—2030年的五大交通运输方式碳排放的年平均变化率进行动态情景分析。结果显示:投资规模是影响铁路、公路、航空及管道运输碳排放量的首要因素,运输规模是影响水路运输的碳排放量的首要因素;在同一时间段内,各影响因素对不同类型运输方式碳排放的作用并非完全相同;不同时间段内,同一影响因素对碳排放的促增效应与促降效应也不同;除基准情景外,2017—2030年5种运输方式的碳排放量均逐渐下降;技术突破情景下,5种运输方式碳排放量预期下降幅度最大。研发使用清洁能源的运输设备、提高其使用性能并进行大力推广等应当作为未来交通业节能减排的主要发展路径。

关键词: 交通业, 碳达峰, 经验分解, 情景预测, 蒙特卡洛模拟, 东北三省

Abstract:

The transportation industry is one of the key industries necessary for the development of the national economy and the everyday life of residents, and it is also one of the main sources of carbon emissions. High energy consumption and high pollution have always been problems in the transportation industry. The effective control of carbon emissions in the transportation industry is greatly important for achieving China’s carbon emission peak target. This study took the three provinces in Northeast China as the research object and conducted a detailed examination on the carbon emissions of five different modes of transportation: road, railway, air, waterway, and pipeline transportation. First, we used the generalized divisia index method (GDIM) to examine the factors affecting the carbon emissions of the five transportation modes from 2005 to 2016 and Monte Carlo simulation to calculate the carbon emissions of the five major transportation modes in 2017-2030. The annual average rate of change was used for dynamic scenario analysis. The results show that the scale of investment is the primary factor affecting the carbon emissions of railway, road, air, and pipeline transportation. The transportation scale is the primary factor affecting the carbon emissions of waterway transportation. During the same period, the influencing factors are different. In different time periods, the same factors also affect growth or reduction of carbon emissions differently. Except under the baseline scenario, the carbon emissions of the five modes of transportation in 2017-2030 will gradually decline; the carbon emissions of the five types of transportation are expected to decline the most under the technological breakthrough scenario. The development of transportation equipment using clean energy, performance improvement, and vigorous promotion should be the main development path for energy conservation and emission reduction in the future transportation industry.

Key words: transportation industry, carbon peak, empirical decomposition, scenario simulation, Monte Carlo simulation, three provinces in Northeast China