曲靖师范学院学报 ›› 2018, Vol. 37 ›› Issue (1): 84-87.

• 交通物流研究 • 上一篇    下一篇

美国交通运输能耗监测统计大数据应用对我国的启示

沈凌云   

  1. 曲靖师范学院 教师教育学院,云南 曲靖 655011
  • 收稿日期:2017-12-20 出版日期:2018-01-26
  • 作者简介:沈凌云,曲靖师范学院教师教育学院经济师,主要从事区域经济和企业管理研究。
  • 基金资助:
    国家社会科学基金项目“‘一带一路’沿线国物流节点安全预警系统建设研究”(16BGL185);商务部国际贸易经济合作研究院基金“中国企业‘一带一路’沿线跨国并购的风险管理研究”(2017SWBZD02)。

Enlightenment of the Application of Big Data of Traffic Energy Monitoring Statistics in America

Shen Lingyun   

  1. School of Teacher Education, Qujing Normal University, Qujing Yunan 655011 China
  • Received:2017-12-20 Published:2018-01-26

摘要: 发展绿色交通是我国建设交通强国的重要内容,也是我国在可持续发展框架下应对气候变化、解决环境危机的必由之路。美国交通运输能耗排放监测统计中大数据的应用,组织架构上从统计组织体系、统计指标体系、统计法律法规体系等三方面对能源消耗排放统计、交通运输统计体系及交通运输领域能耗排放统计进行分析;交通数据来源包括宏观和微观两个维度,数据应用到能耗排放统计上主要采用综合移动源排放模型,并从法律、法规、政策、教育等相关配套措施实现高能效、低污染、可持续,对我国具有组织层面、数据采集、模型应用、法律政策等方面的启示和借鉴意义。

关键词: 交通运输, 交通强国, 绿色交通, 大数据, 能耗排放监测统计

Abstract: Developing green traffic is an important part of the construction of traffic power in China, and also the only way for China to deal with climate change and solve environmental crisis under the sustainable development framework. China could take examples from America as to the application of Big Data in the monitoring statistics of traffic energy emission. This paper analyzes three aspects of the enlightenment: energy consumption emissions statistics, transportation statistics system and transportation field energy emission statistics from perspectives of statistical organization system, statistical Index system, and statistical laws and regulations system. The sources of traffic data include two dimensions: macroscopic and microscopic. Data is mainly applied to energy emission statistics through the comprehensive mobile source emission model. In addition, it analyzes the referential experience of America from laws, regulations, policies, education and other related measures which could achieve energy efficiency, low pollution and sustainable development. And those things have certain experience to China in the aspects of organization level, data collection, model application, legal policy and so on.

Key words: transportation, Traffic Power, green traffic, Big Data, energy emission statistic monitoring

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