Suppr超能文献

中国重点城市碳排放驱动因素分解及峰值预测

Decomposition of driving factors and peak prediction of carbon emissions in key cities in China.

作者信息

Zhang Yuxin, Zhang Yao, Chen Wei, Zhang Yongjian, Quan Jing

机构信息

Graduate School of Environmental Engineering, The University of Kitakyushu, Kitakyushu, Fukuoka, 808-0135, Japan.

College of Mechanical and Electrical Engineering, Shaanxi University of Science and Technology, Xi'an, 710021, Shaanxi, People's Republic of China.

出版信息

Carbon Balance Manag. 2025 Jul 3;20(1):20. doi: 10.1186/s13021-025-00310-7.

Abstract

Urban areas are pivotal contributors to carbon emissions, and achieving carbon peaking at the urban level is crucial for meeting national carbon reduction targets. This study estimates the carbon emissions and intensity changes of 19 cities from 2000 to 2023 using urban statistical data. By employing the logarithmic mean Divisia index (LMDI) method, the driving factors of carbon emissions across these cities are analyzed. Additionally, a multi-scenario prediction approach is utilized to forecast the timing of carbon peaking and trends in carbon emission intensity under various scenarios. The findings reveal that, during the study period, carbon emissions exhibited an overall upward trend, while carbon emission intensity demonstrated a year-by-year decline. The population effect and per capita GDP effect were identified as significant drivers of urban carbon emissions during urban development. Conversely, reducing energy intensity and the carbon intensity of energy consumption can effectively curb the growth of carbon emissions. Under the low-carbon scenario, all cities are projected to achieve carbon peaking before 2030. In the baseline scenario, the vast majority of cities (89.47%) are expected to reach carbon peaking before 2030. However, under the high-carbon scenario, only 63.16% of cities are anticipated to achieve carbon peaking by the same deadline.

摘要

城市地区是碳排放的关键贡献者,在城市层面实现碳达峰对于实现国家碳减排目标至关重要。本研究利用城市统计数据估算了2000年至2023年19个城市的碳排放及强度变化。采用对数平均迪氏指数(LMDI)方法,分析了这些城市碳排放的驱动因素。此外,运用多情景预测方法预测了不同情景下碳达峰时间和碳排放强度趋势。研究结果表明,在研究期间,碳排放总体呈上升趋势,而碳排放强度逐年下降。人口效应和人均GDP效应被确定为城市发展过程中城市碳排放的重要驱动因素。相反,降低能源强度和能源消费的碳强度可以有效抑制碳排放增长。在低碳情景下,预计所有城市将在2030年前实现碳达峰。在基准情景下,绝大多数城市(89.47%)预计将在2030年前达到碳达峰。然而,在高碳情景下,预计到同一期限只有63.16%的城市能够实现碳达峰。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77c3/12225531/556f5e7cdf51/13021_2025_310_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验