This paper develops a novel hybrid Trigonometric Envelopment Analysis for Ideal Solutions (TEA-IS) model to assess the ecological efficiency of 248 Chinese cities for a 14-year period and employs a difference-in-difference approach to reveal the mechanism of the impact of low-carbon pilot city policies on ecological efficiency from the perspective of green technology innovation. This TEA-IS approach not only combines the advantageous features that exist in each individual model, but also allows an analysis of ecological efficiency in terms of the synergistic effects that may exist among correlated positive and negative criteria. Machine learning methods are also employed to predict high-low performance and synergistic Chinese cities in terms of the socio-economic and demographic context. Results indicate that ecological efficiency is generally low in Chinese cities. The low-carbon pilot city policy does help to improve ecological efficiency, which results from the mechanism of green technology innovation.

As one of the major sources of carbon emissions, the significant spatial disparities in agricultural carbon emissions (ACE) pose a serious challenge to coordinated regional carbon reduction efforts. In order to precisely identify the sources of these ACE differences, this study estimates the ACE of China from 2005 to 2020 across four main emission sources and applies the bidimensional decomposition method of the Gini coefficient to measure and decompose their spatial disparities. Finally, the key factors driving ACE disparities are analyzed using the Quadratic Assignment Procedure (QAP). The results show that China’s total ACE initially declined, followed by an upward trend over the study period. Spatially, emissions were higher in eastern regions compared to western regions, and higher in southern regions compared to northern regions. The differences in paddy field emissions between the central and western regions were identified as the primary contributor to east–west disparities, while differences in agricultural materials emissions between northern and southern regions were the dominant source of north–south disparities. Furthermore, regional differences in agricultural development levels and mechanization capacity were found to be the strongest drivers of spatial ACE disparities. This study provides empirical evidence for formulating region-specific and source-targeted carbon reduction policies. Our findings highlight the importance of addressing regional imbalances, particularly in paddy field management and agricultural material usage, to promote more coordinated and sustainable agricultural carbon reduction across China.

Education, as an investment in human capital, is regarded as an important determinant of sustainable economic growth [¹,²]. The purpose of this study is to explore the cointegration and causality between the investment in education and sustainable economic growth in Guangdong province by using the panel data of 21 cities from 2000 to 2016. We construct a variable intercept panel data model with an individual fixed effect based on the Cobb-Douglas production function, estimating the contribution of the investment in education to economic growth by introducing lags. The findings show the existence of the feedback causality between education and sustainable economic growth. Also, the results reveal that the local financial investment in education plays a positive and statistically significant role in promoting sustainable economic growth. However, the contribution of the local financial investment in education to economic growth varies in different areas. The investment in education in the Pearl River Delta region have the most obvious pull effects on its regional economy, whereas the Western region takes the second place. Meanwhile, the local financial investment in education for its role in promoting economic growth obviously has a two-year hysteresis effect. These findings have important implications for Guangdong’s solution to the imbalance between regional educational investment and sustainable economic growth.