干旱区研究 ›› 2022, Vol. 39 ›› Issue (5): 1631-1641.doi: 10.13866/j.azr.2022.05.27

• 生态与环境 • 上一篇    下一篇

黄土高原典型县域碳排放特征与时空格局——以庆城县为例

龙志1,2,3(),孙颖琦1,4,郎丽霞1,2,3,陈兴鹏1,2,3(),张子龙1,4,庞家幸1,5,6   

  1. 1.兰州大学资源环境学院,甘肃 兰州 730000
    2.兰州大学西部环境教育部重点实验室,甘肃 兰州 730000
    3.兰州大学中国西部循环经济研究中心,甘肃 兰州 730000
    4.兰州大学黄河流域绿色发展研究院,甘肃 兰州 730000
    5.兰州大学县域经济发展研究院,甘肃 兰州 730000
    6.兰州大学生态文明建设研究与评估中心,甘肃 兰州 730000
  • 收稿日期:2022-02-24 修回日期:2022-05-15 出版日期:2022-09-15 发布日期:2022-10-25
  • 通讯作者: 陈兴鹏
  • 作者简介:龙志(1991-),男,博士,研究方向为低碳与区域可持续发展. E-mail: longzh18@lzu.edu.cn
  • 基金资助:
    国家重点研发计划项目(2018YFC0704702)

Spatiotemporal patterns and characteristics of carbon emissions in the Loess Plateau: A case study of Qingcheng County

LONG Zhi1,2,3(),SUN Yingqi1,4,LANG Lixia1,2,3,CHEN Xingpeng1,2,3(),ZHANG Zilong1,4,PANG Jiaxing1,5,6   

  1. 1. College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, Gansu, China
    2. Key Laboratory of Western China’s Environmental Systems (Ministry of Education), Lanzhou University, Lanzhou 730000, Gansu, China
    3. Research Institute for Circular Economy in Western China, Lanzhou University, Lanzhou 730000, Gansu, China
    4. Institute of Green Development for the Yellow River Drainage Basin, Lanzhou University, Lanzhou 730000, Gansu, China
    5. Institute of County Economic Development, Lanzhou University, Lanzhou 730000, Gansu, China
    6. Research and Evaluation Center for Ecological Civilization Construction, Lanzhou University, Lanzhou 730000, Gansu, China
  • Received:2022-02-24 Revised:2022-05-15 Online:2022-09-15 Published:2022-10-25
  • Contact: Xingpeng CHEN

摘要:

县域是中国碳排放的重要组成部分和碳汇功能的主要承载空间,更是双碳目标和政策落实的关键行政单元。以庆城县为例,探讨黄土高原典型县域的碳排放特征和时空格局,为推动黄河流域生态保护,实现高质量发展和绿色低碳转型提供启示和参考。结果表明:(1) 欠发达地区县域碳排放变化和结构具有鲜明的特征。规模以下工业是庆城县最大的碳排放来源,工业碳排放比重低,第三产业和生活碳排放比重相对较高。(2) 庆城县碳排放空间分布符合帕累托法则,即80%的碳排放集中在20%的区域,总体表现为“整体分散,局部集聚”的空间分布特征。高碳区主要集中在川区、残塬区和县城区;中碳区主要分布在残塬区和交通沿线;低碳区则广泛分布于梁峁沟壑区。(3) 受地形地貌影响,黄土高原县域碳排放呈现出明显的时空格局差异。县城、工业集中区、主要乡镇等中、高碳区最大斑块指数增加,整体性提高,碳源多样性减少,类型趋于单一化。交通沿线和城乡居民聚居区等中碳区与低碳区交错地带碳源多样性增加,聚集度降低。

关键词: 黄土高原, 碳排放, 时空格局, 庆城县

Abstract:

In China, the county is not only an important contributor to carbon emissions and a major carbon sink zone but also a key administrative unit for the implementation of China’s national goals for carbon peak and carbon neutrality. Focusing on Qingcheng County as a typical county in the Loess Plateau, we investigate the carbon emission characteristics and spatiotemporal patterns, to raise awareness of the need for ecological protection of the Yellow River Basin, while achieving high-quality development and green and low carbon transformation. The key results of our study are as follows. (1) The change and structure of county carbon emission in underdeveloped areas have distinct characteristics. Industries below the designated size are the largest source of carbon emissions in Qingcheng County, having a low proportion of industrial carbon emissions but a relatively high proportion of service sector and household carbon emissions. (2) The spatial distribution of carbon emissions in Qingcheng County conforms to the Pareto Principle: 80% of carbon emissions are concentrated in 20% of the region, which is characterized by “overall dispersion and local agglomeration”. The high carbon zones are mainly concentrated in the valley, broken plateau area, and urban area. The medium carbon zones are mainly distributed in the broken plateau area and along the traffic line. Low carbon zones are widely distributed in ridge, hill, and gully areas. (3) The county carbon emissions in the Loess Plateau show clear temporal and spatial pattern differences that are affected by differences in topography. The largest patch index of medium and high carbon zones, such as urban areas, industrial zones, and major towns, increases, the integrity improves, the diversity of carbon sources decreases, and the types tend to be single. The carbon source diversity increases and the aggregation degree decreases in the ecotone between medium carbon zones and low carbon zones, such as transportation lines and residential areas.

Key words: Loess Plateau, carbon emissions, spatiotemporal pattern, Qingcheng County