Dynamic evolution characteristics and driving factors of carbon emissions in prefecture-level cities in the Yellow River Basin of China

• Published in: Environmental science and pollution research international 2023-05, Vol.30 (25), p.67443-67457
• Main Authors: Chen, Ruimin, Ma, Xiaojun, Zhao, Yanzhi, Wang, Shuo, Zhang, Shiqi
• Format: Article
• Language: English
• Subjects: Aquatic Pollution; Atmospheric Protection/Air Quality Control/Air Pollution; Carbon; Carbon Dioxide; Carbon neutrality; China; Cities; Convergence; Divisia decomposition; Earth and Environmental Science; Economic Development; Ecotoxicology; Emissions; Emissions control; energy; Energy consumption; Energy utilization; Environment; Environmental Chemistry; Environmental Health; Environmental science; Evolution; Head; probability; R&D; Research & development; research and development; Research Article; River basins; Rivers; Transition probabilities; Waste Water Technology; Water Management; Water Pollution Control; watersheds; Yellow River
• ISSN: 1614-7499; 0944-1344; 1614-7499
• DOI: 10.1007/s11356-023-27190-z

This paper focuses on the spatiotemporal evolution characteristics, as well as the driving factors, of carbon emissions in the prefecture-level cities in the Yellow River Basin (YB). The paper’s findings will aid in promoting ecological conservation and high-quality development in the region. The initiatives undertaken in the YB are a significant national strategy towards achieving carbon peaking and carbon neutrality. To fully investigate the spatiotemporal evolution process, as well as the typical characteristics of their carbon emissions, conventional, and spatial Markov transition probability matrices were developed utilizing YB’s panel data for 55 prefecture-level cities from 2003 to 2019. The generalized Divisia index decomposition method (GDIM) cleverly uses this data to conduct a complete analysis of the dynamics and driving processes influencing the change in carbon emissions in these cities. However, the evolution of carbon emissions in prefecture-level cities has reached a point of stability that maintains the original state, making it challenging to make meaningful short-term progress. The data indicates that prefecture-level cities in the YB are emitting more carbon dioxide on average. Neighborhood types in these cities significantly influence the transformation of carbon emissions. Low-emission areas can encourage a reduction in carbon emissions, whereas high-emission areas can encourage an increase. The spatial organisation of carbon emissions exhibits a “high-high convergence, low-low convergence, high-pulling low, low-inhibiting high” club convergence phenomenon. Carbon emissions rise with per capita carbon emissions, energy consumed, technology, and output scale, whereas it falls with carbon technology intensity and output carbon intensity. Hence, instead of enhancing the role of increase-oriented variables, prefecture-level cities in the YB should actively engage these reduction-oriented forces. The YB’s key pathways for lowering carbon emissions include boosting research and development, promoting and applying carbon emission reduction technologies, lowering output carbon intensity and energy intensity, and improving energy use effectiveness.