A spatial differentiation study on comprehensive carrying capacity of the urban agglomeration in the Yangtze River Economic Belt

Study on the urban state carrying capacity for unbalanced sustainable development regions: Evidence from the Yangtze River Economic Belt

Carbon emission efficiency of land use in urban agglomerations of Yangtze River Economic Belt, China: Based on three-stage SBM-DEA model

Urban land intensive use meets the requirements for the sustainable development of urban land and is an important part of urban sustainable development. The Yangtze River Economic Belt (YREB) spans the three major regions of China, which are the most active areas of China’s economy. The contradiction between humans and land is becoming more acute. There are also regional differences in land use patterns affecting the coordinated development of the YREB and the construction of an ecological civilization. Therefore, the scientific evaluation of urban land intensive use is a key area in the current research field of urban sustainable development. In this study, the YREB is chosen as the research object, and urban land intensive use is studied using nighttime light data and statistical data on the urban built-up area. An evaluation model based on urban nighttime light intensity and land urbanization is constructed with an allometric growth model. Considering that the impact of land urbanization on urban nighttime light has a possible lag effect, an evaluation model of land intensive use that considers the lag effect between urban nighttime light and the land urbanization level is proposed. Using urban agglomerations and some typical cities in the study area as research samples, the characteristics of urban nighttime light and land urbanization are analyzed to reveal the spatial and temporal characteristics of land development in the YREB. The results show that nighttime light remote-sensing data can better reflect the level of urban land use, the allometric growth model can better fit the intensity of urban light and the land urbanization level, and the allometric growth characteristics can reflect the land use characteristics of different cities and urban agglomerations. In regional experiments with typical cities and with urban agglomerations, compared to the original allometric growth model, the goodness of fit of the allometric growth model with the lag effect improves, on average, by 3.2% and 2%, respectively, with the highest increases being by 9.9% and 4.9%, respectively. The level of intensive land use in the YREB gradually decreases from east to west, and there are great differences among different cities in the provinces and urban agglomerations. The lower reaches of the Yangtze River have high land intensive use on the whole. In the middle reaches, multicenter cities have a greater efficiency of land use than the surrounding cities. In the upper reaches, only Chengdu and Chongqing have clear advantages in urban land intensive use. The results of this study can be helpful in providing an important reference for the sustainable development of land in the YREB and can provide a basis for future urban land optimization and sustainable development. Realizing the coordination and linkage between key cities and major cities is the key to enhancing the overall sustainable development ability of the core cities in the YREB.

Based on the data of 85 cities in the three major urban agglomerations in the Yangtze River Economic Belt from 2011 to 2020, this paper measures the level of high-quality economic development of each city through the improved entropy-weighted TOPSIS method and uses the kernel density estimation method, Dagum Gini coefficient, and convergence model to further study the dynamic evolution, regional differences, and convergence state of the high-quality economic development level of the three major urban agglomerations in the Yangtze River Economic Belt. The study finds that: 1) the high-quality economic development level of each city within the three major urban agglomerations of the Yangtze River Economic Belt has been continuously improved over time, but the development level of each urban agglomeration is not the same; 2) the high-quality economic development level of the three urban agglomerations in the Yangtze River Economic Belt has spatial differences, that is, the high-quality economic development level of the Yangtze River Delta urban agglomeration is better than the two urban agglomerations; 3) the σ convergence and β convergence characteristics exist in the three major urban agglomerations as a whole as well as in each urban agglomeration, and the β convergence rates of the urban agglomerations are not consistent. On the whole, the convergence rate of the middle reaches of the Yangtze River urban agglomeration is the fastest, followed by the Chengdu-Chongqing urban agglomeration, and the Yangtze River Delta urban agglomeration is the slowest. Finally, based on the findings of the study, targeted policy recommendations to promote the high-quality economic development of the three major urban agglomerations in the Yangtze River Economic Belt are proposed.

This study used a two-stage network data envelopment analysis model to measure the water use efficiency of 108 cities in the Yangtze River Economic Belt in the initial water use and wastewater treatment phases from 2009 to 2019. We divided the urban water use efficiency of six significant urban clusters in the Yangtze River Economic Belt using the Dagum Gini coefficient. We also tested the convergence characteristics of urban water use efficiency in six significant urban clusters in the Yangtze River Economic Belt using convergence and convergence kinds. According to this report, the Yangtze River Economic Zone’s cities often have low levels of water use efficiency, which is primarily due to ineffective wastewater treatment. The 108 cities in the Yangtze River Economic Zone are divided into four types based on the average values of water use efficiency in the initial use and wastewater treatment phases; the highest number of cities are in the double-low category, with low average values of water use efficiency in the initial use and wastewater treatment phases. During the study period, spatial differences in urban water use efficiency in the Yangtze River Economic Zone narrowed, with the differences stemming mainly from hyperdensity, followed by intra- and inter-regional differences. Meanwhile, there is convergence in urban water use efficiency in the Yangtze River Economic Belt, significant β convergence in the urban agglomerations of the Yangtze River Delta, Jianghuai, middle reaches of the Yangtze River, Chengdu–Chongqing, and Central Yunnan, and insignificant β convergence in the Central Qian urban agglomeration. After considering control factors, such as industrial structure, financial development level, environmental regulation, economic development level, and science and education development level, the water use efficiency of the six major urban clusters in the Yangtze River Economic Belt converges faster, but the influence of these control factors on the water use efficiency of each urban cluster is heterogeneous. Research results have reference value for the development of improvement strategies on differentiated urban water use efficiency in the Yangtze River Economic Belt. By measuring the regional differences in water use efficiency of urban agglomerations in the Yangtze River Economic Belt and clarifying their convergence mechanism, it provides a basis for analyzing the spatial pattern of water use efficiency in urban agglomerations and has reference value for formulating differentiated urban water use efficiency improvement strategies in the Yangtze River Economic Belt.

Monitoring of the indicator Sustainable Development Goal (SDG) 11.3.1 is important for understanding the coordination between land consumption rate (LCR) and population growth rate (PGR). However, the spatiotemporal indicator SDG 11.3.1 changes at the urban agglomeration (UA) level, and the relationship between LCR and PGR in the prefecture-level cities from different UAs remains unclear. In this study, we monitored the spatiotemporal indicator SDG 11.3.1 in the Yangtze River Economic Belt (YREB) and its three major UAs (i.e., Chengdu–Chongqing (CC), the Middle Reaches of the Yangtze River (MRYR), and the Yangtze River Delta (YRD)) for the periods 2000–2010, 2010–2015, and 2015–2018, using the space–time interaction (STI) method and Pearson’s method. Our major findings were as follows: (1) Compared with the world average of 1.28 for LCRPGR (i.e., ratio of LCR to PGR), except for the LCRPGR of the YRD (2000–2018) and CC (2000–2010), the LCRPGR of CC, the MRYR, and the YREB was lower than 1.28 during 2000–2018. (2) The gaps in both population and built-up area between the YREB and the three UAs did not narrow, but widened. (3) Compared with the LCRPGR in China, except for the LCRPGR of the YRD (2000–2018) and CC (2000–2010), the LCRPGR of the YREB increased from 1.21 to 1.23 between 2000–2010 and 2010–2015, and then decreased to 1.16 in 2015–2018, indicating that the relationship between LCR and PGR in the YREB is relatively stable. (4) A significant positive relationship (p < 0.001) was found between LCR and PGR in CC, the MRYR, the YRD, and the YREB. We conclude that the indicator SDG 11.3.1 is a helpful tool for evaluating land-use efficiency caused by the LCR and PGR at the UA level. Our results provide information support for promoting sustainable and coordinative development between LCR and PGR.

The ecological environment of urban water resources in the Yangtze River Economic Belt (YREB) is in a huge challenge; yet, while myriad studies have investigated the carrying capacity or sustainable utilization of Chinese water resources, few to none have looked at the inclusive sustainable development of water resources. In this article, a new concept of urban water inclusive sustainability (UWIS) is firstly proposed, and the conceptual framework of ASFII and a five-dimensional indicator system are developed, integrating availability, sustainability, friendliness, inclusiveness and innovation. The panel data of 38 cities in the YREB are adopted from 2008 to 2018 to measure UWIS and five development indexes by the TOPSIS (technique for order preference by similarity to ideal solution) and entropy method. Moreover, the characteristics of the temporal–spatial evolution of the overall system and subsystems coupling coordination are described using the coupling coordination degree model. Key factors that hinder UWIS are identified through the obstacle degree model. The results indicate that the overall UWIS showed a gradual upward trend at a lower to medium level from 2008 to 2018 and a friendliness > sustainability > inclusiveness > innovation > availability index. The UWIS from high to low is YRDUA (Yangtze River Delta urban agglomeration), MRYRUA (middle reaches of the Yangtze River urban agglomeration) and CCUA (Chengdu–Chongqing urban agglomeration). The 38 cities are in low-level coordination, and their temporal characteristics show a trend of economy > science and technology > water resources > environment > societal system, YRDUA > MRYRUA > CCUA. The spatial differentiation is manifested as high in the east and low in the west. The main obstacles come from 12 factors, such as the water resources utilization rate, etc. The findings of our study will be a scientific reference for the Chinese government to track UWIS and ensure urban water resources security in the YREB.

Industrialization in China has faced severe problems such as resource depletion and environmental degradation. The Yangtze River economic belt (YREB) strategy is one of the essential strategies for the sustainable development of the Chinese economy. Maximizing economic benefits while using the least resources and the least pollution to the environment is critical for China’s sustainable development strategy. This paper proposed the DEA to measure industrial eco-efficiency in the YREB from 2009 to 2018. It analyzed its temporal evolution and spatial differentiation and adopted a spatial econometric model to study how interference in influencing factors affects industrial eco-efficiency. The results revealed that (1) the eastern area of YREB has the highest industrial eco-efficiency compared with the other regions. (2) The industrial total factor productivity in the YREB has been rising over the years, and its change trend shows an inverted “W” pattern of first rising, then falling, then rising, then falling. (3) By further analysis, we observed a statistically significant spatial difference in the Industrial eco-efficiency among the areas in YREB, which suggests that the change scale presents the rule of “downstream bigger than Midstream region and midstream region bigger than “upstream region.” (4) The level of economic development, science and technology innovation, and human resources have significantly positive effects on industrial eco-efficiency, and the effect of economic development is of most significant importance. The industrial agglomeration demoted the efficiency of industrial ecology; Science and technology innovations, on the other hand, had a positive spillover effect, while the industrial concentration had a negative spillover effect.

The Yangtze River Economic Belt (YREB) is an important part of China’s “two screens and three belts” strategic ecological security barrier, and the urban agglomeration along the YREB is the core of its economic development. However, it has suffered the most from frequent and severe flood disasters that were affected by torrential rains, urbanization, and human activities, with climate change intensifying the potential occurrence of flood disasters in this area. Based on the CMIP6 climate data, this study constructed a flood risk assessment index system and assessed the temporal and spatial changes of the flood risk in the YREB during 2020–2050 under four shared socioeconomic pathways (SSP) scenarios, including SSP126, SSP245, SSP370, and SSP585. From the perspective of temporal change, the results showed that at the grid level, the area of middle-low risk (0.55 < R ≤ 0.65) accounted for 60% of the total area of the YREB and area of high-risk (R > 0.85) fluctuated first and then decreased under the four scenarios, with the area of high-risk being largest in the future under the SSP585 scenario. Specifically, at the city level, around half of the cities in the YREB had faced high flood risk and the risk showed an increasing trend during 2020–2050 under the SSP370 scenario. From the perspective of spatial change, the flood risk of the YREB presented a spatial pattern of low in the west and high in the east, with high risk mainly concentrated in the cities in the lower reaches of the YREB and also Chongqing and Sichuan. Compared with SSP126 and SSP245 scenarios, it showed that high-risk areas were larger under high emission scenarios SSP370 and SSP585, which were mostly concentrated in middle and lower reaches of the YREB and the cities of Chongqing and Chengdu during 2020–2050. Especially, flood risk showed an increasing trend in the middle and lower reaches of the YREB during 2020–2050, and the regions with high vulnerability would have greater socio-economic losses. The finding would provide scientific support for resilience improvement, risk reduction and management, and formulating policies to achieve green and sustainable development in the YREB.

Ecological welfare performance contributes directly to human well-being and regional sustainable development. Improving the regional ecological welfare performance in the process of pursuing green and sustainable development demands theoretical innovation and empirical exploration. Based on the super-efficiency SBM model, this study evaluated the ecological welfare performance of 108 cities during the period of 2009 to 2019. The Dagum Gini coefficient decomposition and spatial convergence model were employed to analyze the differences in ecological welfare performance across and within the study area and explore the underlining causes of such spatial differentiation in the Yangtze River Economic Belt and the upper, middle and lower reaches. It can be seen from the results that: (1) the overall difference in the ecological welfare performance of the Yangtze River Economic Belt is associated with a fluctuating downward trend during the study period. Regional and inter-regional differences were revealed and hypervariable density was identified as the main source of the differences. (2) The ecological welfare performance of the Yangtze River Economic Belt has absolute and conditional β convergence, and the ecological welfare performance of each city-region and surrounding urban areas has a positive impact on each other. (3) The difference in the spatial-temporal differentiation trend is manifested by the difference in the convergence rate. The cities in the middle reaches of the Yangtze River have the fastest convergence rate, followed by the cities in the upper reaches, and the cities in the lower reaches are the slowest. This geographic difference is mainly driven by the combined effects of industrial structure, urban characteristics, environmental regulation, foreign direct investment, and transportation accessibility. Finally, it is proposed that future policies should focus on the imbalanced regional development in the study area, and each region needs to explore ways to improve local ecological welfare performance according to local conditions, and ultimately promote the overall green, coordinated and high-quality development in the Yangtze River Economic Belt.

IntroductionUnder the current situation of increasingly severe environmental problems, carbon emission intensity (CEI) has become an essential indicator for evaluating the degree of environmental pollution, and sustainable development has become an eternal issue pursued by human beings. Along with the deepening of the concept of green sustainable development, green finance (GF) and digital economy (DIEC) have gradually become environmentally friendly and reliable tools that play an active role in controlling carbon emissions. Therefore, to promote sustainable economic development, it is necessary to promote GF, DIEC, and CEI in an integrated way, and there are relatively few studies on the synergistic promotion of these three aspects.MethodsUsing the entropy method, the coupling coordination degree model (CCDM), and the spatial analysis method, this study thoroughly examines the spatio-temporal pattern of the coupling and coordination of GF, DIEC, and CEI in the Yangtze River Economic Belt using panel data from 11 provinces in the region from 2013 to 2022.ResultsThe findings demonstrate that: (1) The Yangtze River Economic Belt’s general extent of GF and DIEC advancement is increasing, and the DIEC’s level exhibits a pattern of a declining gradient from the downstream to the upstream areas. (2) The Yangtze River Economic Belt’s CEI is on the decline, with the upstream region having a higher CEI than the middle and downstream regions. (3) Although there is regional diversity, the Yangtze River Economic Belt’s three systems exhibit a growing trend in connection and coordination degree. (4) The Yangtze River Economic Zone shows a declining trend in the spatial difference in the coupling coordination degree (CCD) of the three systems(overall Gini coefficient reduced by 31% from 2013 to 2022), with the upstream showing the smallest discrepancy and the downstream showing the biggest. The discrepancy between upstream and downstream is mainly caused by the different economic structures as well as the levels of progress of the two regions. The source of the discrepancy is mainly interregional.DiscussionThis paper puts forward some suggestions in light of the advancement status of the three systems in the region, hoping that it can provide a reference basis for the sustainable development of the region.

It is of great significance to explore the regional differences of land use carbon emission （LUCE） in the Yangtze River Economic Belt and the path of coordinated emission reduction for regional sustainable development. Based on the LUCE estimation method, this study scientifically calculated the LUCE of the three major urban agglomerations of the Yangtze River Economic Belt （Yangtze River Delta, middle reaches of the Yangtze River, and Chengdu-Chongqing urban agglomeration） from 2010 to 2020. Kernel density estimation and the spatial convergence model were used to study the dynamic evolution, regional differences, and convergence characteristics of LUCE. The results showed that： ① The carbon absorption of forest land, water areas, grassland, and unused land were relatively small in terms of carbon emissions from cultivated land and construction land. The carbon emission of construction land increased gradually, whereas the carbon absorption of four carbon sinks fluctuated little during the study period. ② The core density curves of different urban agglomerations showed different distribution patterns, extensibility, and polarization characteristics but generally tended to be balanced. ③ From 2010 to 2020, the LUCE of the Yangtze River Economic Belt as a whole showed the spatio-temporal characteristics of increasing first and then decreasing and high in the east and low in the west. The LUCE of the central cities of the three urban agglomerations were at the highest level steadily, and stable coupling mechanisms had not been established between the economic development level and the ecological environment. ④ The LUCE of the three urban agglomerations in the Yangtze River Economic Belt all had absolute β convergence and also had conditional β convergence under the model control variables such as economic development level, urbanization level, industrial structure, population density, and environmental regulation, etc., and the conditional convergence speed was greater than the absolute convergence speed in each region. The convergence speed of the Yangtze River Delta urban agglomeration was the slowest. The above conclusions provide support for the coordinated emission reduction path of the three urban agglomerations in the Yangtze River Economic Belt and are also conducive to actively and steadily promoting the realization of the goals of carbon peak and carbon neutralization.

Relevance evaluation and spatial differentiation analysis between green development and environmental footprint in China's three typical mega-urban agglomerations

Sustainable development is a critical theory and strategy to promote the development of the regional economy. The sustainable development of the Yangtze River Economic Belt (YEB) has essential significance for the development of China. In this paper, 11 provinces and cities in the YEB are taken as the research object, and the analytic hierarchy process is used to construct an evaluation index system for the sustainable development capacity of the YEB from the three aspects of the economy, society, and ecology, and quantifies the sustainable development capacity of the 11 provinces and cities. The results show that the overall level of sustainable development capacity of the YEB in China is low, the gap between provinces and cities is large, and the differences between provinces and cities with high levels of sustainable development are more pronounced. The economic, social, and ecological subsystems imply that scientific research and technological progress are essential components of the sustainable development index of the YEB and one of the essential means to promote the sustainable development of the YEB in the future. The economic development level, urbanization rate, and greening rate of provinces and cities also play an essential role.

As a fusion point of innovation-driven green development, green technology innovation has become an essential engine for green transformation and high-quality economic development of the Yangtze River Economic Belt. Based on the panel data of 110 cities in the Yangtze River Economic Belt from 2006 to 2020, this paper uses the super-SBM model to measure the efficiency of industrial green technology innovation. Then, the Dagum Gini coefficient and its subgroup decomposition method, kernel density estimation, and the spatial Markov chain will discuss the convergence characteristics and dynamic evolution law of industrial green technology innovation efficiency in the Yangtze River Economic Belt. The results indicate several key points. (1) On the whole, the industrial green innovation efficiency of the Yangtze River Economic Belt shows a trend of the “N” type, which increases slowly at first and then decreases and then increases, and shows a non-equilibrium feature of “east high and west low” in space. (2) The average GML index of industrial green technology innovation efficiency in the Yangtze River Economic Belt is greater than 1, and technological progress is the main driving force in promoting efficiency growth. (3) There are spatial and temporal differences in industrial green technological innovation efficiency in the Yangtze River Economic Belt. Interregional differences and hypervariable density are the primary sources of overall differences. (4) During the study period, the absolute difference in industrial green technology innovation efficiency among regions showed a trend of “expansion-reduction-expansion”, and the innovation efficiency gradually converged to a single equilibrium point. (5) The industrial green technology innovation efficiency transfer in the Yangtze River Economic Belt shows a specific spatial dependence. Accordingly, policy suggestions are put forward to further improve industrial green technological innovation in the Yangtze River Economic Belt.