Based on the perspective of the theory of urban-rural continuum and the composite ecosystem, the connotation framework of the high-quality development of urban-rural integration was constructed. The measurement model, which included three levels of economy, society, ecology, was developed, incorporating the degrees the static integration and the dynamic coupling coordination. This study measured the high-quality development level of urban-rural integration in the 16 cities in the core area of the Yangtze River Delta from 2006 to 2021. The spatial and temporal evolution characteristics were explored and the major obstacles were identified. This study found that: （1） The high-quality development level of urban-rural integration had been growing steadily. The regional development gap narrowed first and then expanded. There existed a tendency of polarization, eventually forming a distribution pattern of "high in the west, low in the east, high in the north and low in the south". （2） The high-quality development form of urban-rural integration in the study area  included nine combination types from low to high. Some regions experienced a good transition from low-level I-I types to high-level III-III and III-IV types. However, there was a certain imbalance in the structure of static integration and dynamic coupling coordination, which blocked the continuous improvement of high-quality development level of urban-rural integration. （3） The major obstacle layer restricting the high-quality development of urban-rural integration was the social integration layer. The key obstacle factors were urban-rural population mobility structure, urban-rural information network density, urban-rural air quality and urban-rural healthcare equalization.

Technology cooperation is the main way and an important support to promote regional collaborative innovation and high-quality integrated development. Based on the data of joint patent applications for inventions, the study analyzed the spatial and temporal evolutionary characteristics of the technology cooperation network in the Yangtze River Delta region from 2000 to 2019, and identified its cooperation patterns and evolutionary paths with the help of social network analysis and GIS spatial analysis techniques. The results showed that: (1) Technical cooperation network in the Yangtze River Delta expanded rapidly, showing obvious small-world and scale-free characteristics, and a hierarchical feature dominated by a few core cities such as Shanghai, Hangzhou and Nanjing. Network centripetal development trend slowed but remained significant. (2) The spatial distribution of the technical cooperation network was extremely heterogeneous, showing decreasing characteristics from the coast to the interior and along the river to the two wings. The evolution of the network structure demonstrated spatial stickiness and temporal inertia. (3) From the perspective of breadth and depth of cooperation, technology cooperation patterns were classified into four types: high breadth-high depth (H-H), high breadth-low depth (H-L), low breadth-high depth (L-H) and low breadth-low depth (L-L), which were spatially characterized by a continuous patchwork of plates. (4) There existed three main paths of upgrading, transformation and locking in the evolution of technology cooperation patterns in the Yangtze River Delta region. The corresponding optimization directions were proposed according to the risks faced by each pattern. This study made attempts to provide reference and guidance for building innovation communities, improving regional innovation systems and achieving high-quality integrated development in the Yangtze River Delta region.

In the green development era, the construction of a high-level regional green innovation network can help to promote the high-quality development of cities and regions. Based on the co-application data of green invention patents, the intercity collaborative green innovation networks of urban agglomerations in the middle and lower Yangtze River were constructed from 2016 to 2020. This study comparatively explored the network structure characteristics and the driving forces of green innovation network of urban agglomeration in the study area through network descriptive analysis and the Exponential Random Graph Model. Results showed that: (1) the green innovation network of the Yangtze River Delta urban agglomeration was more densely developed with strong integrity and accessibility, and presented a multi-center spatial structure with Shanghai, Nanjing and Hangzhou as the core. The green innovation network of the urban agglomeration in the middle reaches of the Yangtze River was relatively sparse with significant core-edge structural characteristics, weak integrality and accessibility, and presented the dual-core radial pattern with Wuhan and Changsha as the core. (2) The municipalities or capital cities of the Yangtze River Delta urban agglomeration had stronger organizational function, but weaker intermediary function, compared with the weak organizational function and strong intermediary function of the municipalities of the urban agglomeration in the middle reaches of the Yangtze River. (3) The green innovation networks of urban agglomerations in the middle and lower Yangtze River were both characterized by self-organized growth. Geographic proximity, institutional proximity and industry similarity influenced the formation of the two networks in the same direction, but to different degrees. The phenomenon that cities at high levels of economic development were more likely to cooperate with each other only occurred in the green innovation network of the Yangtze River Delta urban agglomeration. The structure and driving forces of green innovation networks of the two urban agglomerations were quite different. It is, therefore, crucial to promote the integrated development of regional green innovation according to the local conditions. Yangtze River Delta urban agglomeration should accelerate the integration of Anhui cities. Urban agglomeration in the middle reaches of the Yangtze River should break the administrative barriers as the primary task.

Based on the coupling and coordinated development mechanism of urban human settlements environment and digital economy, the evaluation index system of urban human settlements environment and digital economy was constructed in this paper. The spatial relationship and dynamic factors of coupling and coordination between human settlements environment and digital economy in urban agglomerations in the middle reaches of the Yangtze River and surrounding cities were studied by using entropy method, coupling coordination degree and social network analysis method. We found that: (1) The coupling and coordination level of urban human settlements environment and digital economy presented the characteristics of spatial imbalance. There existed great differences between the internal and external regions of urban agglomerations, and the coupling and coordination level of provincial capitals was more prominent; (2) Compared with the urban agglomeration around Poyang Lake, the coupling coordination correlation strength of Wuhan metropolitan area and the urban agglomeration around Changsha-Zhuzhou-Xiangtan was higher, and the external radiation driving ability was stronger; (3) Under the joint action of the central city and the surrounding cities of the urban agglomeration, the members of Hubei Province and Hunan Province were more connected and had obvious cohesion; (4) Spatial adjacency, spatial geographical distance and industrial structure were the main driving factors for the formation of the internal spatial correlation network of urban agglomerations. This study revealed the dynamic coupling and coordination relationship between human settlement environment and digital economy, which provided policy basis for improving the digital governance capacity of human settlement environment in the middle reaches of the Yangtze River urban agglomeration.

County industrial agglomeration is conducive to the development of agglomeration economy externalities, and is an important way to accelerate the high-quality development of regional economy. Based on the two fundamentals of economic growth and social achievements, this paper constructed a comprehensive index system to evaluate the high-quality development level of county economy in the Shuangcheng economic Circle of Chengdu-Chongqing area. The high-quality development level of 95 counties in the Shuangcheng economic Circle from 2007 to 2021 was calculated, based on the entropy method. It was found that the high quality development level of county economy presented a spatial agglomeration trend, and there existed a significant positive correlation. On this basis, by using the spatial econometric model, the impact of county industrial agglomeration on the high-quality development of regional economy was analyzed from the spatial perspective. The results showed that: (1) the county industrial agglomeration of Shuangcheng economic Circle in Chengdu-Chongqing area demonstrated the characteristics of significant spatial dependence; (2) County industrial agglomeration significantly promoted the high-quality development of county economy in Shuangcheng Economic Circle in Chengdu-Chongqing area, but its spatial spillover effect was significantly negative, which promoted the high-quality development of county economy in the region and hindered the high-quality development of surrounding county economy. In this regard, in order to steadily promote the high-quality development of county economy, it is suggested to promote the development of industrial agglomeration, expand the radiation effect of industrial agglomeration, take advantages of the assistance and driving role of developed counties, optimize the industrial layout, and form an industrial pattern of mutual cooperation and mutual promotion.

Based on the panel data of listed enterprises in the Yangtze River Economic Belt from 2011 to 2021, an OLS model was used to examine the impact of digital financial inclusion on enterprises' total factor productivity. The impact mechanism of digital inclusive finance was identified, on enterprise total factor productivity from five dimensions of "innovative development, coordinated development, green development, open development, and shared development". The moderating effect of the external factors of "market-government" on the total factor productivity of enterprises was examined. The results showed that: (1) digital inclusive finance significantly promoted the total factor productivity of enterprises, with relatively significant effects on upstream and midstream enterprises and limited effects on downstream enterprises. (2) Digital inclusive finance effectively enhanced total factor productivity of enterprises by increasing R&D investment, promoting digital transformation, strengthening corporate green governance, expanding overseas business and improving employee compensation. (3) The enabling effect of digital inclusive finance was significantly enhanced by the external factors of "market-government". To further enhance the total factor productivity of enterprises in the Yangtze River Economic Zone, it is necessary to strengthen the digital innovation and entrepreneurship ecosystem, optimize the financial service system, and improve the financial regulatory system.

The Yangtze River Economic Belt, as a crucial driving force for the high-quality development of the entire nation, holds significant implications for the establishment of a new paradigm in China's artificial intelligence (AI) development. Employing a comprehensive evaluation index system for AI development, this study utilized a stepwise longitudinal and latitudinal approach to appraise the AI development levels across 71 cities in the three principal city clusters of the Yangtze River Economic Belt from 2010 to 2020. Furthermore, sophisticated methodologies such as the Dagum Gini coefficient, kernel density estimation, spatial Markov chain, and spatial Durbin model were leveraged for an in-depth exploration of the disparities, dynamic evolution trends, and the factors affecting AI development. The findings revealed that: (1) AI development levels demonstrated a consistent upward trajectory. Notably, the Yangtze River Delta city cluster held a leading role, followed by the Chengdu-Chongqing city cluster, and the Yangtze River Midstream city cluster. Overall, the spatial distribution pattern of AI development shifted from a "V"-shaped distribution to an increasing pattern from upstream to downstream; (2) Gini coefficients for the Yangtze River Delta and Yangtze River Midstream city clusters decreased during the study period, while the Chengdu-Chongqing city cluster exhibited an increasing trend. The widening gaps of AI development levels among the three city clusters were the major contributor to spatial unevenness; (3) Notable "polarization" effects were observed in the AI development of each city cluster. Both the Yangtze River Delta and Yangtze River Midstream city clusters exhibited "multipolar" differentiation, while the Chengdu-Chongqing city cluster was in the transition from "multipolar" differentiation to "bipolar" differentiation; (4) Different levels of AI development exhibited a distinct transfer "inertia," with cities boasting higher AI development levels exerting a substantial spatial influence on the AI development of surrounding cities. Both siphon and spillover effects coexisted; (5) The regional population density, level of economic development, industrial upgrading, and marketization significantly promoted the development of artificial intelligence in the Yangtze River Economic Belt. However, the development of science and technology finance exerted a notable inhibitory effect.

Promoting common prosperity and increasing residents' income is a crucial task in China. As one of the most rapidly developed transportation infrastructure, high-speed railway (HSR) plays a pivotal role in enhancing residents' income. This study evaluated the accessibility of HSR networks in Jiangsu, Zhejiang, and Shanghai from new perspectives of internal and external accessibility for the years of 2012, 2016, and 2020. Furthermore, this study analyzed the coupling and coordination development between HSR accessibility and residents' income. The findings were: (1) The overall HSR accessibility was gradually increasing; However, there existed an imbalance in the spatial distribution with higher accessibility in Shanghai, Central Jiangsu, Southern Jiangsu, and Northern Zhejiang, compared to Northern Jiangsu and Southern Zhejiang. (2) Among the studied regions, Shanghai demonstrated the highest income level, followed by Southern Jiangsu and Southeastern Zhejiang. Central Jiangsu along with Southwestern Zhejiang were ranked the next, while Northern Jiangsu was lagged behind. (3) Most cities exhibited a coherent developmental relationship between HSR accessibility and residents' income; However, when comparing internal versus external accessibility measures, the coupling coordination degree between internal accessibility and residents' income demonstrated a slower growth. (4) In Northern Jiangsu, the HSR development outpaced the improvement rate of residents’ income level, which indicated a need of an enhanced utilization of HSR infrastructure. Conversely, in Southeastern Zhejiang, the slower pace of internal transportation infrastructure development hampered resident's income growth, resulting in an imbalanced relationship. It was imperative to strengthen transportation links between HSR stations and surrounding areas within this region. In summary, the enhancement of HSR network accessibility promoted residents' income. However, the sluggish development of the internal HSR transportation network in certain regions hampered residents' income growth. In order to foster residents' income and expedite coordinated regional development, it is imperative to strategically advance HSR alongside other transportation infrastructure.

Exploring the coupling coordination relationship between the new-type urbanization process and the farmland utilization eco-efficiency is of great significance for urban-rural integration development and ecological civilization construction. Taking 79 counties in Hubei Province as the research objects, this paper explored the temporal and spatial evolution characteristics of the new-type urbanization level and the farmland utilization eco-efficiency from 2000 to 2018. The entropy method, SBM-undesirable model and coupling coordination degree model were adopted. The results showed that: (1) The county level of new-type urbanization showed a slow upward trend with minor fluctuations. Spatially, there was a "core- periphery" pattern centered on Wuhan. (2) The overall farmland utilization eco-efficiency was at a relatively low level, but it showed a significant increasing trend. The spatial pattern tended to be stable with a general characteristic of high in the central and eastern and low in the western. (3) The coupling coordination degree showed a slow upward trend. By 2020, the coupling coordination level of the majority of counties had reached a barely coordinated or higher level, and the spatial differences of the coupling degree in the "east-west" direction were gradually apparent. In the future, Hubei Province may promote the urbanization construction and sustainable farmland utilization according to local conditions, and establish a comprehensive coordination mechanism to actively promote the cross-regional flow of production factors.

The Poyang Lake Basin of Jiangxi Province is an important part of the inland aquaculture area in China. Exploring aquaculture economic efficiency is conducive to the utilization of fishery resources and the sustainable and high-quality transition of fisheries in this area. Based on the input-output panel data of aquaculture, this study integrated the SBM-XTTobit-GWR model to explore the spatial-temporal evolution of aquaculture economic efficiency from 2016 to 2021. The spatial differences of influencing factors in the Poyang Lake Basin were analyzed. The results showed that: (1) The spatial difference of aquaculture economic efficiency was significant, showing a fluctuating upward trend. The average value of efficiency increased from 0.30 to 0.56, and efficiency value in the north was obviously higher than that in the south. (2) The scale of aquaculture, GDP per capita, population density, fishery economic conversion rate and elevation were positively correlated with the aquaculture economic efficiency. The effect of GWR regression coefficient of these factors increased or decreased in steps from the north to the south. The positive effect of mechanization degree on aquaculture economic efficiency was more obvious in the large surface aquaculture area in north Jiangxi. The proportion of professional aquaculture employees and the utilization degree of natural waters were positively or negatively correlated with the aquaculture economic efficiency. (3) In the future, government should reassign fishery resources according to the efficiency zones and the spatial differences of influencing factors, promote the specialization and high efficient development of fishery industry in large-scale.

The changes in land use and the assessment of landscape ecological risk are of significant importance for regional ecological conservation and planning management. This study took the Qingzang Plateau as an example and employed the Patch-generating Land Use Simulation model (PLUS) to analyze the driving factors of land use changes. Three future scenarios, namely inertial development, economic expansion, and ecological protection, for the period of 2030 to 2050 were constructed. These scenarios were used to simulate changes in land use and landscape ecological risk under each scenario. Results indicated that: (1) Over the past decade, the primary land use conversion pattern on the Qingzang Plateau involved the transformation of grassland and unused land. There was a tendency for conversion between grassland and forest, as well as between grassland and unused land. Factors contributing significantly to land use changes in unused land, grassland, and forest included DEM (Digital Elevation Model) and annual average temperature.  (2) Between 2030 and 2050, different regional land use changes may vary significantly across the three scenarios. Under the inertia development scenario, there is a noticeable expansion of water bodies and construction land, with areas of 1 627 km2and 10 km2, respectively. In the ecological protection scenario, forest and grassland may increase, covering areas of 232 km2 and 15 143 km2, respectively. In the economic development scenario, forest and grassland may decrease, covering areas of 224 km2 and 7 653 km2, while arable land and construction land is likely to increase, covering 146 km2and 24 km2.Therefore, protection policies for the Qingzang Plateau should be region-specific and tailored to the actual circumstances. (3) The landscape ecological risk on the Qingzang Plateau was found to exhibit a spatial distribution pattern with higher risk in the northwest and lower risk in the southeast, primarily in areas of lower risk. Under the inertial development scenario, ecological risk between 2030 and 2050 exhibit a trend of first decreasing and then increasing. In the economic expansion scenario, ecological risk may significantly increase between 2030 and 2050, with the highest-risk areas experiencing the most significant increase, covering an area of 56 051 km2. Conversely, in the ecological protection scenario, ecological risk substantially may decrease between 2030 and 2050, with lower-risk areas experiencing the most substantial increase, covering an area of 16 136 km2.These findings can serve as a decision reference for ecological protection and governance on the Qingzang Plateau.

To gain a comprehensive understanding of the spatiotemporal patterns of agricultural non-point source pollution in Jiangxi Province, we conducted an analysis at the county scale of the Province. Factors such as regional topography and climate variations were systematically considered for the refinement of the traditional output coefficient model. This involved the incorporation of influential driving factors, including rainfall, soil characteristics, and surface runoff. The calculation of the comprehensive river input coefficients for nitrogen and phosphorus pollutants in each region allowed for the transformation of the original regional pollution load production into quantifiable pollutant input into rivers. Our investigation extended to the analysis of pollution levels associated with various aspects, such as farmland cultivation, livestock and poultry farming, aquaculture, and rural living, spanning the years 2010 to 2020.The findings revealed that, in 2020, the average comprehensive river input coefficients for TN and TP in agricultural non-point source pollution in Jiangxi Province were 0.473 and 0.567, respectively. These values exhibited a general distribution pattern characterized by higher concentrations in the northern regions and lower concentrations in the southern areas. The comprehensive river input loads of nitrogen and phosphorus non-point source pollution were determined to be 95 000 tons and 14 100 tons, respectively. These values demonstrated an overall trend of an initial increase followed by a subsequent decrease, with elevated concentrations observed in central areas and lower concentrations in the surrounding regions. Regions with heightened emission intensity were predominantly concentrated in the central part of the Province. While the overall pollution load emissions from livestock and poultry farming, as well as farmland cultivation, exhibited a consistent annual decline, they persisted as primary sources of agricultural nitrogen and phosphorus pollution, accounting for over 80% of the total pollution load. Livestock farming and mixed farming emerged as the predominant types of pollution load in agricultural non-point source pollution. This study provided a valuable reference for decision-makers in Jiangxi Province for future initiatives related to agricultural non-point source pollution prevention and water pollution control at watershed scales.

River Basin is a typical life community of "mountains, rivers, forests, fields, lakes and grasses". Study of spatio-temporal evolution characteristics of habitat quality at basin scales is of great significance to the regional ecological environmental protection and sustainable development. Based on land use data from 1980 to 2020 and by using InVEST model, PLUS model, spatial autocorrelation, cold and hot spot analysis, and standard deviation ellipse, this study analyzed and predicted the spatio-temporal evolution characteristics of habitat quality in Ganjiang River Basin (in Poyang Lake of Jiangxi Province) for the period of 1980-2030. The results showed that: (1) From 1980 to 2030, the main land use type was paddy field, dry land and forest. In general, the area of paddy field and forest continued to decrease whereas the area of urban land, rural settlement and other construction land continued to increase. (2) The habitat quality showed a spatial distribution pattern of "high in the upper reaches and low in the middle and lower reaches". The average value of habitat quality decreased from 0.824 4 in 1980 to 0.804 6 in 2030, indicating an overall decreasing habitat quality. (3) The habitat quality showed significant spatial clustering characteristics with obvious hot and cold spots. The cold spots were mainly distributed in the Poyang Lake Plain in the northern part of the Basin, the Jitai Basin in the central part of the Basin, and the riverside plains in the south, while the hot spots were mainly distributed in Yushan Mountain Range and Wuyi Mountain Range. The cold spots in 2030 would spread outward, and the north-south direction would be more powerful than the east-west direction. The hot spots may have a weaker tendency of spreading out in the "northwest-southeast" direction than that of contracting in the "northeast - southwest" direction. (4) The intensity of habitat degradation in the Basin increased from 1980 to 2030, and the trend of habitat degradation became more obvious. The sub-basins where the degree of habitat degradation was increasingly deteriorated included Jinjiang River Basin, Xiaojiang River Basin, Yuanshui River Basin, Wujiang River Basin, Taihe section of Ganjiang River, Meijiang River Basin, Mianshui River Basin, Taojiang River Basin and Xiangshui River Basin. These results may provide scientific basis for decision-making towards a better management of habitat protection and regional coordination in Ganjiang River Basin.

The simulation of carbon emissions and carbon sequestration under different scenarios and the prediction of carbon peaking and carbon neutrality are the keys to developing the path of "Double Carbon" goals. In this paper, the improved IPAT model and InVEST model were used to estimate and predict the carbon emissions and carbon sequestration in the Yangtze River Delta during 2010—2060. The spatio-temporal variation characteristics as well as the time of carbon peaking and carbon neutrality were analyzed. It was found that: (1) During the study period, the spatial variations of carbon emissions in the Yangtze River Delta showed a positive growth trend, with the mean annual carbon emissions of 6 317.30 t·km-2. The growth rate of carbon emissions gradually decreased outward from the core area of the Shanghai Sea. The carbon sequestration showed a spatial pattern of high in the south and low in the north, with the mean annual carbon sequestration of 607.23 t·km-2. (2) In the baseline scenario, Shanghai, Jiangsu and Anhui provinces would reach their carbon peaks in 2030, while Zhejiang Province might reach its carbon peak in 2040. In the sustainable development scenarios, all provinces might reach carbon peaks in 2030. Under the scenario of rapid economic development, all provinces would reach their carbon peaks in 2040. (3) By 2060, the three provinces and one city in the Yangtze River Delta would not be able to achieve carbon neutrality as a whole under the three scenarios. However, at the prefecture-level city level, 10 cities could achieve carbon neutrality by 2060, in the base scenario; Under the sustainable development scenario, 21 cities could achieve carbon neutrality; Under the scenario of rapid economic development, two cities could achieve carbon neutrality. Therefore, it is necessary to optimize and upgrade the energy structure, guide the rational layout of low-carbon industries, optimize the land use structure, pay attention to ecological environmental protection, in an attempt to achieve the "Double Carbon" goals.

Regional integration refers to the free flow of production factors to achieve market openness and full competition. To achieve China's 'dual carbon' strategic goal, the impact of regional integration on the ecological environment has attracted widespread attention. Diverse energy consumption preferences in various regions inevitably lead to the spatial transfer of carbon emissions and the flow of production materials. Therefore, the relationship between regional integration and carbon emission transfer should be critically examined to achieve high-quality green development. This study used 41 cities in the Yangtze River Delta as empirical objects and selected 2011, 2014, 2017 and 2020 as the time nodes. The regional integration network was built based on five dimensions: transportation, market, industry, information and culture. Night light data were used to estimate urban carbon emissions. The carbon emission transfer network between cities was simulated using the multi-regional input-output table. From the perspective of network form, structural correlation and interaction, we used social network analysis, cumulative distribution function, bivariate local spatial autocorrelation, ordinary least squares (OLS) and random forest regression model to quantitatively analyse the intensity, direction, trend and geographical difference of regional integration and its impact on carbon emission transfer. We found that the Yangtze River Delta had a heterogeneous spatial organisation pattern of regional integration and carbon emission transfer networks; however, the network topology had a significant correlation. The Yangtze River Delta's regional integration had a positive effect on carbon emission transfer and also showed distinct stage characteristics, implying that building integration would accelerate the flow of carbon emissions in the current stage. However, with the continuous optimisation of economic geography patterns and resource allocation, the positive relationship between regional integration and carbon emission transfer was likely to change. Influenced by the level of development, coordination mechanism, and spatial proximity, the spatial optimisation effect of integration construction within the Yangtze River Delta was better than that between its sub-regions. However, administrative barriers continued to hinder the low-carbon and the coordinated development of the Yangtze River Delta.

Balancing the relationship between emission reduction and development is crucial for the Yangtze River Delta urban agglomeration to achieve the "dual carbon" goal and economic transformation and upgrading. Based on the constructed evaluation index system of carbon emission reduction and high-quality economic development, this study analyzed the spatial-temporal evolution characteristics and the driving factors of the coupling coordination degree between carbon emission reduction and high-quality economic development from 2006 to 2021. The coupling coordination degree, spatial autocorrelation model and geographic detector were used. The results showed that:（1）the comprehensive level of carbon emission reduction and high-quality economic development in the urban agglomeration showed an increasing trend during the study period, but the latter had obvious fluctuations.（2）the coordination between carbon emission reduction and high-quality economic development was good, but the degree was not high, and there was a large gap between the coordination degree of the internal regions. In terms of coordination type, the reluctant coordination level was dominant, and the general dissonance level was relatively small.（3）the coupling coordination degree had significant spatial differentiation and spatial agglomeration.（4）the coordination degree of the urban agglomeration  was mainly affected by five factors, including green travel, urban greening, structural adjustment, technological innovation and public service supply. Regionally, due to the different natural and economic environments of Jiangsu, Zhejiang, Anhui and Shanghai,  differences in the factors driving the coordination degree were found.

ased on panel data from the Yangtze River Delta urban cluster from 2011 to 2021, this study employed a global technology super-efficiency hybrid distance function and a mediation effects model to analyze the impact of new infrastructure construction, particularly in the areas of information, innovation, and integration infrastructure, on the "quality and efficiency" of low-carbon economic development. Additionally, this study explored the mediating role of green technological innovation. The findings were as follows: (1) New infrastructure and information infrastructure had a significantly positive impact on the "quality and efficiency" of low-carbon economic development in the study area. The green technological innovation was found to play a significant mediating role. (2) Innovation infrastructure primarily had a significantly positive impact on the quality level of low-carbon economic development. Innovation infrastructure enhanced the transformation and upgrading of the economic structure and promoted the research and application of green technologies. However, due to the factors of diminishing marginal returns on capital, inefficient resource allocation, and low technological conversion efficiency, the driving force on the efficiency level of low-carbon economic development was limited. (3) Integration infrastructure faced certain challenges including insufficient synchronicity between information technology and integration infrastructure, low maturity and stability of emerging technologies, and difficulties in applying them within the complex open systems. These constraints hindered the driving capacity of integration infrastructure on regional low-carbon economic development. Finally, we provided recommendations including strengthening regional and industry collaboration, improving technological conversion efficiency, optimizing resource allocation mechanisms, and establishing a multidimensional evaluation system.