RESUMO
Efficiently utilizing the energy resources in the agriculture sector to produce more agricultural output with minimum environmental degradation is a shared global challenge. The Chinese government has introduced various policies aimed at enhancing energy efficiency (EE) and total factor energy productivity (TFEP) while addressing regional technological disparities in the agricultural sector. This study utilized DEA Super-SBM, Meta frontier Analysis, and the Malmquist-Luenberger index to assess energy efficiency, changes in total factor energy productivity, and the regional technology gap ratio (TGR) across 30 provinces in mainland China and three distinct regions during the period from 2000 to 2020. The findings reveal that the average EE in China's agricultural sector is 0.8492, indicating that, on average, there is a 15.08 % potential for improvement in EE growth within the sector. Qinghai (1.5828), Shanghai (1.3716), and Hainan (1.3582) are found to be the top 3 performers with the highest EE levels. The Eastern region demonstrates high excellence in EE, with a value of 1.0532. The TGR value of Zhejiang indicates the superior production technology utilized in the agriculture sector to utilize energy resources efficiently. Except for Zhejiang, the TGR of Liaoning, Jiangsu, Shanghai, Guangdong, Ningxia, and Hainan is above 0.96 and near 1, indicating superior production technology in the agriculture sector of China. The Technology Gap Ratio (TGR) of China's eastern region is superior to that of the central and western regions, consistently approaching 1. This suggests that the eastern provinces possess more advanced agricultural technologies, allowing them to optimize resource utilization for maximum output. The Malmquist-Luenberger index (MLI) score of 1.103 indicates a 10.3 % growth in the total factor energy productivity of China's agricultural sector. Further analysis reveals that this growth is primarily driven by technological change (TC), with a TC value of 1.080 surpassing the efficiency change (EC) value of 1.028. Among the three agricultural regions, the eastern region exhibits the highest total factor energy productivity. Specifically, Zhejiang (1.23), Shanghai (1.197), Liaoning (1.184), and Hebei (1.147) are identified as the top performers in total factor energy productivity growth in China's agricultural sector. Additionally, the Kruskal-Wallis test confirmed statistically significant differences in EE and TGR among the three regions.
RESUMO
Lessening energy-related carbon emissions has become a crucial measure to achieve Chinese carbon neutrality. This study is the first to construct a Difference in Carbon pressures-adjusted Human Development Index (DCHDI) model for the purpose of exploring the coupling effect between carbon emissions and human development variety from 2000 to 2019 in Chinese provinces. We demonstrate the following. (1) The total energy-related carbon footprint of 30 provinces in China reached 10.2 billion tons in 2019, with an average annual growth rate of 6.93% over the past two decades; and the provinces with the highest carbon emissions per capita are InnerMongolia, Ningxia, and Shanxi. (2) At the provincial level, we observed that the Human Development Index (HDI), which includes life expectancy, education, and income, has been rising, while Beijing, Shanghai, and Tianjin entered the super-high HDI level before 2008. (3) The entire coupling effect of 30 Chinese provinces has been broadly fortified in the last 20 years, but the growth rate of DCHDI values in 2011-2019 has slowed down compared with that in 2000-2010; the clustering phenomenon demonstrated that this discovery is associated with historical peaks in total carbon emissions. (4) The coordination degree of carbon emissions per capita and HDI was verified, and 96% of the data points were found in the range of super high coupling coordination degree. Overall, this study provides the government with worthwhile guidance for decision-making and carbon reduction strategies for other countries struggling to advance human sustainable development.