Scenario Analysis of Carbon Emissions in Jiangxi Transportation Industry Based on LEAP Model

被引:4
|
作者
Liu, Yan-yan [1 ]
Wang, Yan-feng [2 ]
Yang, Jun-qing [1 ]
Zhou, Ye [3 ]
机构
[1] Nanchang Univ, Sch Environm & Chem Engn, Nanchang 330029, Peoples R China
[2] Ocean Univ China, Sch Econ, Qingdao 266071, Peoples R China
[3] Nanchang Hangkong Univ, Sch Econ & Management, Nanchang 330063, Jiangxi, Peoples R China
关键词
Carbon emissions; LEAP model; Transportation industry; Scenario analysis;
D O I
10.4028/www.scientific.net/AMM.66-68.637
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Transportation industry is an important field to reduce greenhouse gas emissions and climate change. Scenario analysis of transportation industry can provide theoretical support to the formulation and implementation of carbon emissions reduction policy. In view of this, The transportation industry of Jiangxi province will be given into four departments including civil aviation, railways, highways and waterways, and it was used the LEAP model to set three scenarios in the different application of economic development mode and different traffic development mode, then forecasted the main carbon emissions of Jiangxi transportation industry in 2010-2030, and analyzed the result of forecasting. It shown that the way to ease the nervous energy supply and the pressure of carbon emissions, and achieve the sustainable development of energy and the environment, must be set the four departments of reasonable transportation distribution under the condition of different energy sources, and increase the scope of using the new energy and renewable energy.
引用
收藏
页码:637 / +
页数:2
相关论文
共 50 条
  • [1] Prediction on Peak Values of Carbon Dioxide Emissions from the Chinese Transportation Industry Based on the SVR Model and Scenario Analysis
    Zhu, Changzheng
    Wang, Meng
    Du, Wenbo
    [J]. Journal of Advanced Transportation, 2020, 2020
  • [2] Prediction on Peak Values of Carbon Dioxide Emissions from the Chinese Transportation Industry Based on the SVR Model and Scenario Analysis
    Zhu, Changzheng
    Wang, Meng
    Du, Wenbo
    [J]. JOURNAL OF ADVANCED TRANSPORTATION, 2020, 2020
  • [3] A scenario analysis of the energy transition in Japan's road transportation sector based on the LEAP model
    Meng, Linghao
    Li, Mei
    Asuka, Jusen
    [J]. ENVIRONMENTAL RESEARCH LETTERS, 2024, 19 (04)
  • [4] The Scenario Analysis of Carbon Emissions Based on Improved IPAT Model in China
    Shan Xu
    Shao Hua Wang
    [J]. SUSTAINABLE DEVELOPMENT OF NATURAL RESOURCES, PTS 1-3, 2013, 616-618 : 1484 - 1489
  • [5] Calculation decoupling analysis and scenario prediction of carbon emissions of transportation in China
    Yang, Qi
    Zhu, Rong-Hui
    Zhao, Xiao-Qiang
    [J]. Chang'an Daxue Xuebao (Ziran Kexue Ban)/Journal of Chang'an University (Natural Science Edition), 2014, 34 (05): : 77 - 83
  • [6] Scenario analysis of transportation carbon emissions in China based on machine learning and deep neural network models
    Tang, Jianxin
    Gong, Rizhao
    Wang, Huilin
    Liu, Yuxi
    [J]. ENVIRONMENTAL RESEARCH LETTERS, 2023, 18 (06)
  • [7] Carbon peak forecast and low carbon policy choice of transportation industry in China: scenario prediction based on STIRPAT model
    Chuang Li
    Zhecong Zhang
    Liping Wang
    [J]. Environmental Science and Pollution Research, 2023, 30 : 63250 - 63271
  • [8] Carbon peak forecast and low carbon policy choice of transportation industry in China: scenario prediction based on STIRPAT model
    Li, Chuang
    Zhang, Zhecong
    Wang, Liping
    [J]. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2023, 30 (22) : 63250 - 63271
  • [9] Analysis of the Influencing Factors of Regional Carbon Emissions in the Chinese Transportation Industry
    Zhu, Changzheng
    Wang, Meng
    Yang, Yarong
    [J]. ENERGIES, 2020, 13 (05)
  • [10] Economic growth and carbon emissions analysis based on tapio-ekc coupled integration and scenario simulation: a case study of china's transportation industry
    Hou, Lingchun
    Wang, Yuanping
    Hu, Lang
    Wang, Ying
    Li, Yuelong
    Zheng, Yingheng
    [J]. ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY, 2024, 26 (07) : 18855 - 18881