大气与环境光学学报 ›› 2024, Vol. 19 ›› Issue (4): 440-455.doi: 10.3969/j.issn.1673-6141.2024.04.005

• 环境光学监测技术 • 上一篇    下一篇

2000―2019年中国能源消费碳排放时空特征研究

廖聪聪 , 郝泷 *, 崔玉环 , 李鹏飞 , 许亚洲 , 盛亮亮   

  1. 安徽农业大学资源与环境学院, 安徽 合肥 230036
  • 收稿日期:2022-09-13 修回日期:2022-10-21 出版日期:2024-07-28 发布日期:2024-07-30
  • 通讯作者: E-mail: haoshuang@ahau.edu.cn E-mail:haoshuang@ahau.edu.cn
  • 作者简介:廖聪聪 (2000- ), 女, 安徽宿州人, 主要从事资源环境与遥感方面的研究。E-mail: liaocongcong@ahau.edu.cn
  • 基金资助:
    国家自然科学基金项目 (41801332), 国家级大学生创新创业训练项目 (202210364036), 安徽省高校自然科学研究重点项目 (KJ2021A0178)

Spatio-temporal characteristics of carbon emission from energy consumption in China during 2000−2019

LIAO Congcong , HAO Shuang *, CUI Yuhuan , LI Pengfei , XU Yazhou , SHENG Liangliang   

  1. School of Resources and Environment, Anhui Agricultural University, Hefei 230036, China
  • Received:2022-09-13 Revised:2022-10-21 Online:2024-07-28 Published:2024-07-30
  • Contact: Shuang Hao E-mail:haoshuang@ahau.edu.cn
  • Supported by:
    Support by National Natural Science Foundation of China

摘要: 精准把握碳排放的时空格局变化, 因地制宜制定区域差异化减排政策是当前社会广泛关注的问题。基于 2000―2019 年融合后夜间灯光数据和全国能源碳排放估算建立拟合模型, 反演出地级市碳排放数据, 从碳排放类型、 空间聚集、重心转移3 个方面对城市化进程快速发展的背景下的碳排放空间依赖性进行研究。研究结果表明: 2000― 2019 年我国碳排放总量呈上升趋势, 增长速度与碳排放强度在整体上逐渐放缓; 在2000―2019 年夜间灯光总量和省 级碳排放数据的反演模型中, 二次项模型拟合度最高, R2达到0.8261; 中国能源碳排放在空间上呈现不均匀分布, 基 本格局为东高西低、北高南低; 2000―2019 年全国碳排放空间特征区域性差异和空间聚集现象越来越明显, 碳排放的 空间分布重心总体方向是由西向东迁移。

关键词: 夜间灯光, 碳排放, 时空特征, 重心转移

Abstract: To accurately grasp the changes of the temporal and spatial pattern of carbon emissions and formulate regional differential emission reduction policies according to local conditions is a widely concerned in current society. Based on the night lighting data from 2000 to 2019 and the estimation of national energy carbon emissions, a fitting model is established to deduce the carbon emission data of prefecture-level cities, and then the spatial dependence of carbon emissions under the background of the rapid development of urbanization is studied from three aspects: carbon emission type, spatial aggregation and center of gravity transfer. The results show that the total carbon emission in China shows an upward trend from 2000 to 2019, with the growth rate and carbon emission intensity gradually slowing down as a whole. In the five inversion models for total night lighting data and provincial carbon emission data from 2000 to 2019, the quadratic model has the highest fitting degree, with R2 reaching 0.8261. Energy carbon emissions in China show an uneven distribution in space, with a basic pattern of high in the east and low in the west, and high in the north and low in the south. From 2000 to 2019, the regional differencesand spatial accumulation of carbon emissions is becoming more and more obvious, and the spatial distribution of carbon emission center has generally shifted from west to east.

Key words: nighttime light data, CO2 emissions, spatio-temporal characteristics, center of gravity transfer

中图分类号: