Search Results (9)

Enhancing market integration levels is crucial for advancing sustainable regional collaborative development and achieving ecological protection and high-quality development goals within the Yellow River Basin, fostering a balance between economic efficiency, social equity, and environmental resilience. This study analyzed the retail price data of goods from prefecture-level cities in the Yellow River Basin from 2010 to 2022, employing the relative price method to measure the market integration index. Additionally, it examined the temporal and spatial evolution patterns and driving factors using the Dagum Gini coefficient and panel regression models. The results indicate the following. (1) The market integration index of the Yellow River Basin shows a fluctuating upward trend, with an average annual growth rate of 9.8%. The spatial pattern generally reflects a situation where the east is relatively high and the west is relatively low, as well as the south being higher than the north. (2) Regional disparities are gradually diminishing, with the overall Gini coefficient decreasing from 0.153 to 0.104. However, internal differences within the downstream and midstream areas have become prominent, and contribution rate analysis reveals that super-variable density has replaced between-group disparities as the primary source. (3) Upgrading the industrial structure and enhancing the level of economic development are the core driving forces, while financial support and digital infrastructure significantly accelerate the integration process. Conversely, the level of openness exhibits a phase-specific negative impact. We propose policy emphasizing the need to strengthen development in the upper reach of the Yellow River Basin, further improve interregional collaborative innovation mechanisms, and enhance cross-regional coordination among multicenter network nodes. Full article

Studying the development of land green utilization efficiency and the factors that influence it in the Beijing–Tianjin–Hebei region can improve the distribution of land resources among regions and reinforce interregional integrated planning. By constructing a super-efficiency SBM model, calculating the Malmquist–Luenberger index, and constructing a Tobit model, this study explores the spatial features and temporal variations of land green use efficiency in the Beijing–Tianjin–Hebei region from 2010 to 2022. It also examines the mechanism that drives land green use efficiency in the context of the Beijing–Tianjin–Hebei synergistic development. According to this research, Beijing has consistently had the highest land green usage efficiency and a strong green development strength, whereas Baoding, Xingtai, Handan, and other cities in Hebei Province have lower land green utilization efficiency. According to the geographical dimension, the research area’s land green use efficiency exhibits a pattern of “high in the middle and low in the surroundings”, with Cangzhou, Langfang, and Tangshan standing out in terms of both industrial transformation and ecological building. Based on the results of the driving mechanism of land green use efficiency, it is evident that while the degree of urbanization and population concentration has a negative effect on land green use efficiency, the degree of economic development, industrial synergy, opening up to the outside world, environmental regulation, and ecological output all have positive and promoting associations with it. In summary, increasing the optimization of the economic and industrial structure, bolstering technological innovation and policy coordination, and attaining a harmonious coexistence of the economy and ecology are all essential steps in the process to increase the land green use efficiency in the research area when attempting to achieve the goal of sustainable development in the region. Full article

Revealing the linkage between interregional coordination and a green economy is crucial to economic resilience and high-quality development capabilities. Although local governments in China are increasingly emphasizing environmental policy coordination, academics have not fully investigated whether it can advance green economic development. This research aims to quantify interregional environmental policy coordination from the perspectives of policy actor coordination and policy tool coordination and further investigates its green development effects, particularly when considering the mediating role of natural resource endowment. The analysis is based on environmental policies and related data issued by 284 cities in China from 2003 to 2022. The results indicate that (1) interregional environmental policy coordination contributes to green economic development, in which policy actor coordination and policy tool coordination are complementary and indispensable. (2) It exhibits heterogeneity characteristics that have a stronger promoting effect in resource-rich areas, as well as spillover characteristics that gradually weaken with increasing distance. (3) Interregional environmental policy coordination promotes green economic development by reducing natural resource abundance and natural resource dependence; however, both policy actor coordination and policy tool coordination mainly play a role in lowering natural resource abundance. This study offers useful insights for policymakers seeking to maximize economic benefits while utilizing limited resources and protecting the environment. Full article

In recent years, the issue of PM_2.5 and O₃ pollution in China has gradually become a hot topic in air pollution control. Powerful, precise, and clear policies are important to guide the efficient control of PM_2.5 and O₃ pollution. However, research on PM_2.5 and O₃ pollution policies is very limited. Moreover, these reports have failed to identify all the specific characteristics of the PM_2.5 and O₃ pollution policies in China, leading to inefficient control of PM_2.5 and O₃ pollution. Therefore, based on the external features and internal structures of relevant policy documents, this paper conducts a detailed bibliometric analysis to elucidate the evolution of PM_2.5 and O₃ pollution control policies in China. The results reveal the following: (1) The PM_2.5 and O₃ pollution control policies in China exhibit a characteristic of “top-down cross-level response lag”, transitioning from individual pollutant control to coordinated control of PM_2.5 and O₃ pollution. (2) The Ministry of Environmental Protection and the Ministry of Ecology and Environment have been the two major policy issuers in China’s government, focusing on “Technology” and “Monitoring”, respectively. However, the aforementioned policies are mainly implemented by local governments, with limited interregional cooperation but an overemphasis on enterprise pollution control and emergency systems. (3) In terms of policy instruments, supply- and environment-oriented policy instruments are predominant, whereas demand-oriented policy instruments are inadequate. Therefore, it is suggested to utilize the synergistic effect of pollution reduction and carbon mitigation to achieve the goal of the “dual carbon” strategy, enhance public participation to strengthen cooperation among diverse stakeholders, strengthen cross-regional cooperation to overcome governance barriers, and reasonably optimize the use of policy instruments to form an effective combination of policy instruments. Full article

In the Yangtze River Delta region, where the agricultural economy is well developed and agricultural pollution and carbon emissions are significant, a regional study of AEE (Agricultural Eco-Efficiency) is crucial to reducing agricultural environmental pollution, improving the rationalization of agricultural production layout, and promoting the realization of low-carbon goals. The SBM-Tobit model and GIS were employed to analyze AEE based on the carbon emission evaluation system in the spatial and temporal characteristics, as well as the influencing factors and the migration path of the center of gravity in the “low carbon” context. A rational plan of agricultural production was proposed according to the results. The following results were obtained: (1) The level of AEE in the Yangtze River Delta region was high, and the region exhibited a U-shaped curve change from 2000 to 2020, with a fluctuating decrease from 2000 to 2003 and a fluctuating increase from 2004 to 2020. The regional spatial development balance was enhanced, while there was a spatial incongruity in the development process of AEE enhancement, high in the southwest and low in the northeast; (2) AEE generally had a high regionalized agglomeration of low–low in the southwest and high–high in the northeast. Nonetheless, temporal heterogeneity was observed in spatial correlation, and the correlation weakened with time variation; (3) Urbanization level, agricultural production structure, crop cultivation structure, and fertilizer application intensity were the main factors influencing AEE in the Yangtze River Delta region; (4) The center of gravity of AEE in the Yangtze River Delta region shifted to the southwest under the influence of “low-carbon” related policies. Therefore, the improvement of AEE in the Yangtze River Delta region should focus on inter-regional coordination and linkages, rational planning of production factors, and the formulation of measures under relevant carbon policies. Full article

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. Full article

With the development of cities, the relationship between cities is becoming closer, and the study of urban livability based on a single city can no longer meet the guidelines and suggestions for urban agglomerations. A scientific evaluation of livability in urban agglomerations can better help cities to recognize the advantages and disadvantages. However, most studies on urban livability focus on its connotation and history and neglect simulations and analyses of the future. Based on the Yangtze River Delta agglomeration, this paper establishes an index system using data from 2011 to 2019 to simulate urban livability from 2020 to 2025 through the ARIMA model and analyzes the historical and future data by using GIS methods. The results show the following: (1) The ARIMA model has good simulation accuracy when applied to urban livability analysis and can provide a reference for future urban livability development. (2) The urban livability of the Yangtze River Delta agglomeration has obviously changed both on the whole and in subsystems. Cities in the upper ranking of livability have developed rapidly, and the difference in urban livability has increased. (3) The spatial autocorrelation of urban livability in the Yangtze River Delta agglomeration is obvious both on the whole and in subsystems. (4) The influencing factors of urban livability development are diverse. The general public budget expenditure for social security and employment, fixed assets investment in municipal public facilities, total retail sales of consumer goods, and education and medical expenditures have positive effects on the development of urban livability, while industrial ${\mathrm{SO}}_2$ emissions have a negative effect. The results show that cities should strengthen inter-city relationships, promote the coordinated development of inter-regional cities, and formulate relevant policies to improve the level of urban environmental governance in the region. Full article

Ecological well-being performance (EWP) is central to achieving coordinated and sustainable economic and social development and environmental protection. This study constructed an evaluation index system of EWP, measured the EWP of 30 Chinese provinces or cities from 1997 to 2018 using the super-efficiency slack-based model (Super-SBM), and analyzed the spatial and temporal evolutionary characteristics of EWP. Under the division of four regions and eight regions, the Dagum Gini coefficient decomposition is applied to analyze the regional differences and sources of differences in EWP in China. Then, the Geographically and Temporally Weighted Regression (GTWR) model analyzes the factors influencing EWP. Results show that the inter-provincial differences in EWP in China are significant, with the eastern region having significantly higher EWP than the western, central, and northeastern regions. From 1997 to 2018, the overall spatial differences in EWP in China decreased. The four regions and eight regions show that reducing inter-regional differences is the key to mitigating regional unbalance in China. Urbanization significantly enhances EWP in China and the degree of openness and industrial structure has a significant heterogeneous effect on EWP. Therefore, future policy formulation should focus on transforming the economic development model, promoting coordinated regional development, and exploring the optimal ways to improve EWP according to local conditions. This study aims to provide a scientific basis and reference for promoting sustainable regional economic and social development and improving the imbalance. Full article

With the advent of the Energy 4.0 era, the adoption of “Internet + artificial intelligence” systems will enable the transformation and upgrading of the traditional energy industry. This will alleviate the energy and environmental problems that China is currently facing. The integrated development of artificial intelligence and the energy industry has become inevitable in the development of future energy systems. This study applied a comprehensive evaluation index to the energy industry to calculate the comprehensive development index of the energy industry in 30 provinces of China from 2000 to 2017. Then, taking Guangdong and Jiangsu as examples, the synthetic control method was used to explore the direction and intensity of the integrated development of artificial intelligence and the energy industry on the comprehensive development level of the local energy industry. The results showed that when artificial intelligence (AI) and the energy industry achieved a stable coupled development without the need to move to the coordination stage, the coupling effect promoted the development of the regional energy industry, and the annual growth rate of the comprehensive development index was above 20%. This coupling effect passed the placebo test and ranking test and was significant at the 10% level, indicating the robustness and validity of the experimental results, which strongly confirmed the great potential of AI in re-empowering traditional industries from the data perspective. Based on the findings, corresponding policy recommendations were proposed on how to promote the development of inter-regional AI, how the government, enterprises, and universities could cooperate to promote the coordinated development of AI and energy, and how to guide the integration process of regional AI and energy industries according to local conditions, in order to maximize the technological dividend of AI and help the construction of smart energy in China. Full article