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This paper examines the coupling coordination degree between digital economy and green technology innovation in 19 urban agglomerations across China from 2011 to 2020. Through the analysis of the coupling coordination degree model, spatial autocorrelation, multi-distance spatial clustering analysis, kernel density analysis and grey correlation model, this study uncovers the mechanism of coupling between digital economy and green technology in Chinese urban agglomerations. Data analysis revealed a significant increase in the coupling coordination between the digital economy and green technology innovation within urban agglomerations. However, there are noticeable spatial imbalances in this trend. Additionally, the multi-distance spatial distance analysis highlights a shift from a random distribution to a clustered distribution of spatial characteristics. The polarization features vary among each urban agglomeration and exhibit a significant positive spatial correlation. Factors such as economic sustainability, creative talent, policy support, digital impetus, and technological support will affect the coupling mechanism of green technology innovation and the digital economy in China's urban agglomerations. Policy recommendations are proposed to foster the development of the digital economy, promote coordinated growth within and beyond urban clusters, and ultimately build a digital ecological civilization that is both green and intelligent. [ABSTRACT FROM AUTHOR]

Information and communication technology plays an essential role in affecting CO2 emissions and promoting green and sustainable development. This paper empirically examines the effect of the level of urban ICT development on CO2 emissions using panel data for Chinese cities from 2010 to 2020. On this basis, a spatial Durbin model is used to analyze the spatial spillover effects of ICT development level affecting regional CO2 emissions, and its direct, indirect and overall effects are further analyzed. The conclusions of the study are as follows. (1) The CO2 emissions of Chinese cities are correlated by spatial distance and show high-high or low-low clustering characteristics. (2) ICT development can reduce CO2 emissions in the region and increase CO2 emissions in neighboring regions. This conclusion still holds after several robustness tests. And when the level of ICT development increases by 1 standard deviation, CO2 emissions are reduced by 64%. (3) The mechanism of action shows that ICT can influence regional CO2 emissions through its technological innovation effect and industrial upgrading effect. (4) The impact of ICT development on regional carbon emissions is characterized by significant heterogeneity depending on the city's geographical location and whether or not environmental information is publicly available. [ABSTRACT FROM AUTHOR]

As China has entered a new stage of high-quality development, clarifying the mechanism and spatial characteristics of green development for urban agglomerations are critical to sustainable development. Based on the data of 11 major cities in the Harbin-Changchun urban agglomeration (HCUA) from 2010 to 2020, this study constructs an evaluation system of green development index (GDI) is composed of four dimensions, i.e. urban green construction (UGC), industrial green development (IGD), resource and environmental carrying capacity (RECC), and technological innovation support (TIS). Furthermore, using the entropy weight method to obtain the weights of evaluation indicators. And then, the comprehensive index calculation is used to evaluate the GDI. The driving factors of each level of GDI are determined by the Pearson correlation coefficient. The results infer some novel findings as follows: (1) the overall tendency of the GDI of the HCUA has gradually increased from 0.358 in 2010 to 0.379 in 2020 which is at the average level. The dimension of TIS shows the highest rate of contribution while IGD and RECC show a fluctuating trend over the time window. (2) The GDI in the HCUA exhibits a patchy clustering differentiation feature that spreads from the central area to the surrounding areas with a "high in the south and low in the north" pattern. Specifically, Changchun, Harbin, and Daqing form an "inverted triangle" structure in geographical location to drive the green development of neighboring areas. (3) The core cities of the HCUA, Changchun, and Harbin, show a much higher level than the other cities. Jilin and Daqing are at the average level, and besides, the rest of the cities of GDI are at the poor level with significant fluctuations in ranking. (4) There are different driving factors between each level of GDI. For cities with good and average levels should focus on protecting resources and the environment. Meanwhile, cities with poor level of GDI need to improve IGD to optimize the urban green structure. Thus, it is suggested to strengthen the flow of factors and implement differentiated strategies to promote coordinated development and spatial clustering. [ABSTRACT FROM AUTHOR]

We study the empirical relationship between green technologies and industrial production at very fine-grained levels by employing Economic Complexity techniques. Firstly, we use patent data on green technology domains as a proxy for competitive green innovation and data on exported products as a proxy for competitive industrial production. Secondly, with the aim of observing how green technological development trickles down into industrial production, we build a bipartite directed network linking single green technologies at time t 1 to single products at time t 2 ≥ t 1 on the basis of their time-lagged co-occurrences in the technological and industrial specialization profiles of countries. Thirdly, we filter the links in the network by employing a maximum entropy null-model. Our results emphasize a strong connection between green technologies and the export of products related to the processing of raw materials, notably crucial for the development of climate change mitigation and adaptation technologies. Furthermore, by looking at the evolution of the network over time, we observe a growing presence of more complex green technologies and high-tech products among the significant links, suggesting an increase in their importance in the network. [ABSTRACT FROM AUTHOR]