Analysis of carbon emission drivers and multi-scenario projection of carbon peaks in the Yellow River Basin

Social and economic driving forces of recent CO2 emissions in three major BRICS economies

The study examines the driving factors of total energy-related and power-related (electricity-heat) CO2 emissions for China, India and Brazil, three BRICS countries with vital economic and demographic dynamics. The paper applies decoupling and decomposition analysis in order to investigate the influence of those factors that are prominent in the contemporary literature as well as factors reflecting important social and demographic dynamics which affect the ecological footprint of society. Household size and number of households are introduced into the relevant literature for the first time to reflect demographic factors with substantially different trends from population size, the predominant factor in the existing literature. This novelty together with the simultaneous application of decoupling and decomposition analysis adds importance to the findings of the study, which covers the period of 2000-2018. The results show that increasing income and population significantly enlarge the energy-related CO2 emissions. Household size, number of households and income effects are crucial in the increase of power-related CO2 emissions. The crucial factor for the decrease of energy-related CO2 emissions is the decreasing energy intensity, while for power-related CO2 emissions it is the emission factor effect reflecting the recent shift towards less carbon intensive energy types.

Research on the spatial patterns and evolution trends of the coupling coordination between digital finance and sustainable economic development in the Yellow River Basin, China

In the current global context, digital finance (DF) and sustainable economic development (SED) are important topics. The synergies between DF and SED have already been proven. However, the measurement and quantitative analysis of the coupling coordination degree (CCD) of DF and SED have not received sufficient attention to date. Based on data from 55 cities in the Yellow River Basin (YRB) from 2011 to 2021, this study constructs an evaluation index system of DF and SED and measures their level, respectively. The proposed CCD model is then used to measure the CCD between the two systems. In addition, kernel density estimation, Markov chain, σ-convergence, β-convergence, and the quadratic assignment procedure (QAP) method are used to study the spatial pattern, distribution dynamic evolution trend, convergence, and influencing factors of the regional differences in the CCD. The results show that: (1) From 2011 to 2021, the CCD level showed a stable upward trend and regional heterogeneity, and the time stage characteristics were more obvious. (2) The center position and change interval of the overall distribution curve of the kernel density estimation gradually shifted to the right. The Markov transfer probability matrix shows that the CCD is more stable among different levels, indicating a phenomenon of "club convergence". (3) A convergence analysis shows that there are significant σ-convergence, absolute β-convergence, and conditional β-convergence. (4) The QAP regression shows that factors such as the regional differences in GDP per capita have a significant impact on the regional differences in the CCD. This study offers a comprehensive structure that can be used to examine the synergistic effects between DF and SED; the research findings can also provide perspectives for other areas.