气候变化研究进展 ›› 2018, Vol. 14 ›› Issue (5): 505-512.doi: 10.12006/j.issn.1673-1719.2018.069

• 温室气体排放 • 上一篇    下一篇

全球碳排放格网化格局的变化

范志欣1,2,方修琦1,2(),苏筠1,2   

  1. 1 北京师范大学环境演变与自然灾害教育部重点实验室,北京 100875
    2 北京师范大学地理科学学部,北京 100875
  • 收稿日期:2018-05-08 修回日期:2018-06-24 出版日期:2018-11-30 发布日期:2018-09-30
  • 作者简介:范志欣,女,硕士研究生
  • 基金资助:
    资助项目:国家重点研发计划“全球变化与应对”专项(2016YFA0602704)

Changes in global grid pattern of carbon emissions

Zhi-Xin FAN1,2,Xiu-Qi FANG1,2(),Yun SU1,2   

  1. 1 Key Laboratory of Environmental Change and Natural Disaster, Ministry of Education, Beijing Normal University, Beijing 100875, China
    Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
  • Received:2018-05-08 Revised:2018-06-24 Online:2018-11-30 Published:2018-09-30

摘要:

基于世界各国年碳排放总量数据和人口密度数据,将人口密度作为一项经济-人口综合指标来对碳排放进行空间分配,运用ArcGIS空间分析工具,做出了1950年、1980年、2014年共3期的全球碳排放空间分布格局图 (0.1?×0.1?),并对各期分布格局及变化进行了比较分析。结果显示:1950年主要碳排放区为美国的东部和欧洲地区,1980年新增中国东部、日本、韩国等为全球碳排放的主要区域,2014年新增印度、东南亚为主要排放区。各碳排放区的排放量总体上大幅增加,少数地区略有减少,这与其工业发展所处的不同阶段有关。该数据能够反映当前全球不同区域的碳排放水平的空间格局,为全球变化研究提供基础数据。

关键词: 碳排放, 空间分布, 高分辨率, 气候变化, 全球

Abstract:

Based on the global carbon emissions data from the Carbon Dioxide Information Analysis Center, and population density data from the Socioeconomic Data and Applications Center, the ArcGIS spatial analysis tools were used to integrate population density as an economic-population composite indicator for weighted carbon emissions for 1950, 1980, and 2014. The resulting Global Population-Weighted Carbon Emissions Dataset (at 0.1° × 0.1° resolution) shows that: In 1950, the main carbon emission areas were the eastern part of the United States and Europe. In 1980, the eastern part of China, Japan, and South Korea were added as the main areas of global carbon emissions. In 2014, India and Southeast Asia were newly added as major emission areas. Carbon emissions have increased substantially in general and decreased slightly in a few areas, which is related to the different stages of industrial development. The dataset can reflect the change of global carbon emissions spatial distribution and provide basic data for global climate change research.

Key words: Carbon emissions, Spatial distribution, High resolution, Climate change, Globe

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