Coordination Model Research Articles

How Can Digital–Real Economy Integration Affect Urban Green Innovation? Evidence from China

As the integration of the digital economy into the real economy accelerates and the goals of green and low-carbon development become increasingly clear, promoting green innovation (GI) through digital–real economy integration (DRI) is of great practical significance for achieving green, high-quality urban development. This study, based on a sample of 284 prefecture-level cities and above in China, used the entropy method to measure the development levels of the digital economy and real economy in each city and employed a coupling coordination model to calculate the degree of DRI. By constructing a bidirectional fixed effects model, a mediation effect model, a threshold regression model, and a spatial Durbin model, this study explored the impact of DRI on GI in cities. The research found that DRI has a non-linear promoting effect on GI. When a city’s DRI level surpasses the second threshold, each 1% increase in DRI leads to a 1.439% rise in GI. This effect also shows heterogeneity based on city location and resource endowment. In this process, transaction costs and the upgrading of the industry structure serve as mediating factors, with each 1% increase in DRI reducing transaction costs by 0.163% and enhancing industrial upgrading with a coefficient of 0.176. Additionally, DRI in one city can significantly enhance the level of GI in neighboring cities through spatial spillover effects. For instance, under the geographic distance weighting matrix, the indirect effect of DRI reaches 4.693, and similar significant spillover effects are observed under the economic distance and economic geography weighting matrices.

The Coordination of Water Resources and Economic Development in a Water-Scarce Area: An Ecosystem Service Perspective

In water-scarce areas, there is a complex interrelationship between water resources and economic development. This paper studies the relationship between water resources and economic development from an ecosystem services perspective. This paper selected the value of river ecosystem service functions and the comprehensive index of economic development in the Yellow River Basin (YRB) from 2007 to 2018 as the research object, tested the synergy of ecosystem service functions in the basin, and introduced a coupling coordination model to evaluate the synergy of developmental factors. The research results showed that (1) the overall river ecosystem service value in YRB was on the rise, and its distribution was characterized by a high value in the lower reaches and a gradual decrease from the middle reaches to the upper reaches; (2) the synergy of river ecosystem service functions in YRB was mainly reflected in the supply and regulation functions, and the synergy of cultural functions should be improved; (3) the overall coupling and coordination degree showed an upward trend. However, judging from the characteristics of coupled and coordinated degrees, backward ecological development is a long-term problem. This article will help to put forward countermeasures and suggestions for the coordinated development of the river ecosystem service value and regional economy in YRB.

Assessing the Impacts of Urbanization and Climate Change on NPP Under Different Habitat Quality Conditions over the Last Two Decades in the Tibetan Plateau, China

The processes of urbanization and climate change have exerted a marked influence on net primary productivity (NPP). However, the underlying mechanisms that drive these effects remain intricate and insufficiently understood. The processes of urbanization and climate change both have an adverse effect on habitat quality (HQ) and biodiversity loss. The HQ has a direct influence on the health and stability of ecosystems, which regulate the level of NPP. A higher HQ is associated with stronger NPP. Now, the quantification and assessment of the impacts of climate change and urbanization on NPP are still challenging because of the various driving factors and the intricate mechanisms influencing the production of terrestrial vegetation. Therefore, a new perspective was adopted to study the effects of urbanization and climate change on NPP in the Qinghai–Tibet Plateau in China during 2000–2020. The spatiotemporal analysis method was employed to investigate the impact of the night light urbanization index and climate factors on NPP in different HQ regions (the HQ is divided into five levels, with each area type corresponding to a specific HQ level). Then, the coupled coordination model (CCD) was used to analyze the coupling coordination relationship between NPP and HQ. Finally, the relative contribution of urbanization and climate change to NPP was studied using scenario simulation. The results showed that (1) NPP in the whole Tibetan Plateau increased very little, with an average growth rate of 0.42 g C m⁻2 per year. (2) It was surprising to find that NPP in urban areas did not decline significantly as a result of urbanization. However, there was a notable decline in NPP in higher HQ areas. (3) The mean contribution of urbanization to NPP change was found to be 17%, while the mean contribution of climate change and other factors to NPP change was 69% and 14%, respectively. These findings provide valuable insights into the interactions between human development and environmental factors, enhancing our comprehension of their role in the Tibetan Plateau’s carbon cycle.

Study on the Coupling and Coordination Relationship Between Urban Living Environment and Economic Development

The coordinated development of urban human settlements and the economy is a crucial indicator for assessing regional development and is essential for achieving sustainable high-quality development. Therefore, urban planning and management need to introduce scientific concepts to achieve a win–win situation for both the economy and the environment. (1) Background: Since the reform and opening up of China’s economy, it has undergone rapid development and urbanization. However, the improvement of human settlements has not kept pace. Some regions pursue economic development while neglecting environmental construction. To achieve a win–win situation for both the economy and the environment, urban planning and management need to incorporate scientific concepts. (2) Methods: This paper adopts a literature analysis method to construct a coupling coordination model and evaluate the level of coupling coordination between urban human settlements and economic development in 31 provinces and cities in China from 2011 to 2021. (3) Results: The level of coupling coordination has gradually increased year by year, but there are significant regional differences, with the East outperforming the West. Spatial analysis reveals a positive spatial correlation, indicating that provinces with similar development levels tend to cluster together. (4) Conclusions: The degree of economic outwardness, industrial structure, and residents’ income and consumption system are the main internal obstacles, while economic strength, urbanization, technological innovation, and human capital are positive external factors.

Analysis of EU’s Coupled Carbon and Electricity Market Development Based on Generative Pre-Trained Transformer Large Model and Implications in China

With increasing global attention on carbon emission control and sustainable development, the carbon market has become an important tool for promoting environmental sustainability and carbon emission regulation. As an important part of energy trading, the electricity market is closely related to the carbon market and their effective coupling is critical for achieving sustainable energy transitions. Power generation can effectively link carbon prices and electricity prices. Through the promulgation of reasonable policies, we can promote the coupling of the carbon market and the electricity market, and then, through macro-control, promote the steady and joint development of the carbon and electricity markets, improve the construction of the carbon rights market, reduce greenhouse gas emissions, and create a sustainable future for humanity. Given the relative maturity of the EU carbon market and electricity market, this paper identifies key points of market volatility through the coupling coordination model analysis and uses the GPT large model analysis to analyze policy factors that have a greater impact on carbon market and electricity market transactions. The research results show that market-regulating policies and expectation management policies have the greatest impact on the degree of coupling between the carbon and electricity markets. The impact of secondary policies such as international cooperation policies and structural adjustment policies is relatively insignificant. Although the development of China’s carbon market faces many challenges, reasonable policy interventions are expected to achieve significant results in the domestic carbon market. Finally, this paper also draws on analogy analysis to draw corresponding implications for China from the EU’s carbon–electricity coupling policy promulgation.

Study on the coupling coordination characteristics and influencing factors of ecological environmental civilization and resident public health in China-based on a modified coupling coordination model.

As industrial technologies advance, climate change and environmental pollution increasingly pose threats to human health. This study examines the coupling coordination characteristics between ecological environmental civilization (EEC) and resident public health (RPH) to promote both higher public health standards and enhanced societal sustainability. Utilizing panel data from 31 provinces in China spanning from 2010 to 2022, this paper constructs evaluation indices for EEC and RPH. Initially, the entropy method is employed to determine the development levels of each domain. Subsequently, a modified coupling coordination degree (CCD) model is applied to assess the CCD between EEC and RPH. This research further investigates the spatiotemporal evolution trends of the CCD using methods such as the Dagum Gini coefficient, kernel density estimation (KDE), and Markov chains. Finally, the panel Tobit model is utilized to analyze factors influencing the CCD. Findings reveal that during the study period, both EEC and RPH in China exhibited a stable upward trend, although the overall development level remained relatively low. The CCD showed consistent growth both nationally and across three major regions. Overall inequality in coupling coordination, as measured by Dagum Gini coefficient, has decreased, with the coefficient reducing from 0.0316 in 2010 to 0.0199 in 2022. KDE results indicate a rightward shift in the density curve of the CCD, suggesting a significant reduction in absolute disparities. Panel Tobit regression analysis shows that economic development, urbanization, and education levels significantly and positively influence the CCD on a national scale, with urbanization having the most substantial impact, followed by economic development and education levels.

The spatio-temporal evolution and influencing factors of the coupling coordination degree between tourism supply and demand in the Yangtze river economic belt

The imbalance between supply and demand is a pressing issue in the development of the tourism industry. Understanding the coupling coordination relationship and impact mechanism of supply-demand in the tourism system can help achieve high-quality tourism development. This study focuses on the Yangtze River Economic Belt (YREB) as the research area, quantifies the tourism supply index (TSI) and tourism demand index (TDI) from 2011 to 2020 using the tourism development index model, calculates the coupling coordination degree (CCD) of TSI and TDI based on the coupling coordination model, and explores the factors influencing the CCD using the geographic detector. The findings indicate that: (1) The TSI and TDI in various provinces show fluctuation but exhibit an overall upward trend. (2) There were apparent spatial disparities of the CCD, with a distribution characteristic of high in the east and low in other regions. The CCD gradually improved, with its gravity center slowly shifting toward the southwest. All provinces entered the intermediate stage of tourism development since 2014. (3) Basic service guarantee, consumption drive, and innovation drive are identified as the dominant factors influencing the CCD. The study can provide valuable insights for tourism coordination and sustainable development.

Temporal and Spatial Variations in Landscape Pattern–Function Risk Coupling over 20 Years in the Dry–Hot Valley of the Jinsha River in China

Extensive and profound landscape alterations significantly contribute to ecological vulnerability in environmentally delicate regions. Existing research primarily emphasizes ecological risks caused by landscape alterations, while overlooking vulnerable characteristics of landscape functions; particularly lacking are studies on the driving mechanism of landscape ecological risk through the reciprocal relationship between landscape pattern risk and function risk. Based on these issues, this paper constructed a landscape pattern risk index (LPRI), a landscape function risk index (LFRI), and a landscape ecological risk index (LERI) in the counties of the dry–hot valley of the Jinsha River in southwest China. By employing a coupling degree and a coordination model, we analyzed temporal and spatial variations in the interaction between two types of ecological risk, thereby revealing the driving mechanisms of landscape ecological risk. The results indicated that the average LPRI values of the study area were 0.373, 0.327, and 0.427, respectively, while the average LFRI values were 0.451, 0.356, and 0.442 in 2000, 2010, and 2020, respectively. More than 90% of the study area exhibited a medium coupling relationship between the two types of ecological risks. The area proportion of the coupling coordination regions has increased from 25.58% to 31.07% from 2010 to 2020. The two types of risk exhibited a low level of constraint inhibition. Extremely evident expansion of high pattern–function risk areas and the area increase of coupling coordination region resulted in the acceleration of regional landscape ecological risk level. Increasing competition between market-driven land-use activities and ecological regulations from the government has rendered the diversification of landscape ecological risk sources and its underlying mechanisms intricate. This study serves as a model reference for assessing landscape ecological risk and a theoretical basis for sustainable landscape management and ecological regulation in the Yangtze River basin.

Coupling Coordination and Driving Mechanisms of Regional Protection and Development in Traditional Villages of the Loess Hilly and Gully Region, Northern Shaanxi Province

With the rapid urbanization in China, traditional villages are undergoing simultaneous construction and destruction, making it crucial to scientifically balance the protection and development of these villages. The Loess Hilly Area of Northern Shaanxi, one of the most severely eroded regions in the world, was chosen as the study area. Socio-economic, land use, and natural ecological data from 152 traditional villages in this area were analyzed. First, an evaluation model was developed to assess the comprehensive level of protection and development in these villages. Next, a coupling coordination model and spatial autocorrelation model were employed to measure the coordination level and spatial distribution of protection and development. Finally, a coordination influence model was combined with a geographically weighted regression model to reveal the driving mechanisms promoting the coupling coordination between protection and development. The results indicate that (1) the protection and development levels of traditional villages in the study area exhibit contrasting patterns of “high in the east and low in the west” and “high in the west and low in the east”, respectively; (2) nearly half of the regions show a low level of coordination between protection and development, with a few counties and districts in the east achieving better coordination; and (3) the spatial variation in the coupling of protection and development is influenced by regional economic capacity, social development, resource endowment, and policy inclination, with various factors influencing the coordination in different ways. This study helps to further elucidate the relationship between the protection and development of traditional villages and provides valuable references for the protection and development of traditional villages in other ecologically fragile areas.

The Averaged Hydrostatic Boussinesq Ocean Equations in Generalized Vertical Coordinates

AbstractDue to their limited resolution, numerical ocean models need to be interpreted as representing filtered or averaged equations. How to interpret models in terms of formally averaged equations, however, is not always clear, particularly in the case of hybrid or generalized vertical coordinate models, which limits our ability to interpret the model results and to develop parameterizations for the unresolved eddy contributions. We here derive the averaged hydrostatic Boussinesq equations in generalized vertical coordinates for an arbitrary thickness‐weighted average. We then consider various special cases and discuss the extent to which the averaged equations are consistent with existing ocean model formulations. As previously discussed, the momentum equations in existing depth‐coordinate models are best interpreted as representing Eulerian averages (i.e., averages taken at fixed depth), while the tracer equations can be interpreted as either Eulerian or thickness‐weighted isopycnal averages. Instead we find that no averaging is fully consistent with existing formulations of the parameterizations in semi‐Lagrangian discretizations of generalized vertical coordinate ocean models such as MOM6. A coordinate‐following average would require “coordinate‐aware” parameterizations that can account for the changing nature of the eddy terms as the coordinate changes. Alternatively, the model variables can be interpreted as representing either Eulerian or (thickness‐weighted) isopycnal averages, independent of the model coordinate that is being used for the numerical discretization. Existing parameterizations in generalized vertical coordinate models, however, are not always consistent with either of these interpretations, which, respectively, would require a three‐dimensional divergence‐free eddy tracer advection or a form‐stress parameterization in the momentum equations.

Comparative Analysis of Higher‐Order Ionospheric Delay on PPP Long‐Term Coordinate Time Series and Residual Modeling Using Horizontal Gradients and RINEX Data

AbstractHigher‐order ionospheric corrections, including second‐ and third‐order effects and signal bending, are essential for improving Global Navigation Satellite System (GNSS) time series accuracy. However, their influence on long‐term Precise Point Positioning (PPP) time series, particularly signal bending, remains underexplored. Most studies rely on Global Ionosphere Maps (GIMs) for second‐order delay corrections due to the complexity of RINEX‐based inversions. Analyzing data from 37 International GNSS Service stations (2009–2020), we found that higher‐order ionospheric effects predominantly impact the North component of mid‐ and low‐latitude stations. Second‐ and third‐order delays contribute 50% and 20% to annual and semi‐annual amplitudes, respectively, while signal bending accounts for 5% and 2%. Additionally, signals traveling along the magnetic field direction induce phase delays, with equatorial regions experiencing more frequent and intense ionospheric activity. This leads to maximum horizontal velocity impacts of 0.45 mm/yr at the equator and a distinct southern trend at mid‐ and low‐latitudes. GIM‐based corrections increase seasonal signal amplitudes and root mean square error (RMSE) at some stations due to discrepancies with RINEX‐based corrections, which generate higher‐order ionospheric residuals. These residuals contribute 48.6% of the RMSE in RINEX‐based corrections, surpassing the 39.8% from second‐ and third‐order delays. To address this, we propose a GIM‐based residual model incorporating horizontal gradients, reducing RMSE by 48%, 26%, and 52% for the East, North, and Up components, respectively. Monthly or quarterly gradient updates during quiet ionospheric periods ensure precise corrections, enhancing GNSS time series and coordinate system accuracy.

Development and Analysis of a Treatment Timeliness Dashboard for Patients With Head and Neck Cancer at a Tertiary Academic Multidisciplinary Clinic

Improving timeliness represents a critical opportunity to maximize patient experience, quality of care, and overall health of a co-located multidis­ciplinary cancer (MDC) program. The primary objective was to develop a timeli­ness dashboard using a primary nursing care coordination model to track met­rics selected for care efficiency. The secondary objective was to identify whether timeliness improved with implementation of an MDC clinic with expanded visi­bility to care coordination. A nursing care coordination model was developed to perform data collection alongside frontline patient care to track patients’ jour­ney with cancer. A spreadsheet was first used but then transitioned to a web-based database based on nursing feedback. Timeliness metrics were collected from May 2019 through April 2023 with descriptive analysis performed to iden­tify trends. Results signify implementation of a co-located MDC with primary nursing care coordination has improved timeliness. The project showcases the importance of nursing care coordination in a high-volume clinic with increased visibility to patients’ journeys with cancer. It also demonstrates establishing and updating standardized work procedures for data collection, cleaning, and analy­sis for quality of care monitoring.

The spatial-temporal evolution characteristics and influencing factors of the coupling between the industrial chain and innovation chain in China

Exploring the theoretical logic, development characteristics and improvement paths of the deep coupling of innovation chains and industrial chains (two-chain) is of great importance for building a modern industrial system and developing productive forces. However, empirical evidence on the spatial-temporal characteristics and influencing factors of two-chain coupling is still lacking. In this study, the degree of coupling coordination model is applied to assess the degree of two-chain coupling in China using provincial panel data from 2013 to 2022. In addition, spatial analysis is applied to investigate the spatial-temporal evolution characteristics of the variables in question. On this basis, the fuzzy set qualitative comparative analysis (fsQCA) method is applied to identify influential factors. The results indicate that: (1) Temporally, the coupling level of the two-chain shows a consistent upward trend and gradually develops a distribution pattern characterized by high values in the east and weak values in the west. (2) Spatially, there is a significant positive spatial correlation between the two-chain coupling. (3) In terms of drivers, the increase in two-chain coupling is attributed to multiple factors. Three models can be identified: human-driven, capital-driven and information-driven, which are influenced by the cooperation between government and market. The novelty of this article lies in its exploration of the theoretical logic and developmental characteristics of two-chain coupling, while empirically demonstrating its driving factors. This study provides a new perspective for governments and relevant departments to improve two-chain linkages and promote economic development.

Challenges for Antepartum Care of the Individual with Perinatal Substance Use: An Empirical Integrative Review of Novel Approaches to Improve Care.

Perinatal substance use continues to rise across the United States presenting unique challenges to providing antepartum care. Polysubstance use, limited and late engagement in health care, co-occurring mood disorders, and several social barriers are well documented. This review seeks to summarize these barriers and present novel approaches to caring for this high-risk population. Inclusion criteria for this study focused on peer-reviewed articles that explicitly detailed a direct impact on the provision or receipt of antenatal care in the setting of substance use within the United States that were published in the last 5 years. PubMed and Web of Science were used to find applicable articles. Of the 156 articles found, 10 relevant articles were selected for the final empirical integrative review that entailed data evaluation using the Mixed Methods Appraisal Tool (MMAT) and thematic analysis. 10 review articles met inclusion; 3 were qualitative, 6 were quantitative and nonrandomized, and one was quantitative descriptive. Six articles met MMAT quality criteria, and there were significant limitations in every article. Topics included opioid use disorder (n = 6), general substance use (n = 3), and tobacco use (n = 1). Themes included integrated models of prenatal care, colocated care, resource coordination, and peer support along with the role of the perinatal health care professional and consistent use of a substance use screening tool. A comprehensive and multidisciplinary care model is necessary to meet the complex and urgent needs of individuals with perinatal substance use that not only meets recommendations for opioid maintenance therapy or substance use cessation but the important areas of accessibility and interpersonal support. Future research should focus on the development, implementation, and evaluation of new models of care for this vulnerable population.

The spatial differentiation mechanism of intangible cultural heritage and its integration with tourism development based on explainable machine learning and coupled coordination models: a case study of the Jiang-Zhe-Hu in China

As a vital carrier of traditional culture, Intangible Cultural Heritage (ICH) not only preserves historical value but also fosters cultural identity and confidence. This study utilizes explainable machine learning and coupled coordination models to analyze the spatial distribution and formation mechanisms of ICH resources in the Jiangsu-Zhejiang-Shanghai (Jiang-Zhe-Hu). The results indicate that (1) ICH resources in the Jiang-Zhe-Hu exhibit a clustered distribution pattern characterized by “three primary cores and two secondary cores.” The primary core areas are Shanghai, Hangzhou, and Suzhou, while the secondary core areas are Yangzhou and Nanjing. (2) Population, number of religious places, and GDP have a significant positive impact on the distribution of ICH in the Jiang-Zhe-Hu. NDVI and road mileage have relatively minor effects on ICH distribution. (3) In terms of ICH resources, Zhejiang Province overall has a higher level than Jiangsu Province, with Lishui having the highest evaluation value and the most abundant resources. Regarding the level of tourism industry development, Shanghai has the highest comprehensive evaluation value, followed by Suzhou, Nanjing, Hangzhou, Wuxi, and Changzhou, all of which have relatively high levels of tourism development. (4) According to the coupled coordination model analysis, Shanghai demonstrates the best coupling degree between ICH resources and the tourism industry, achieving a good coordination level. In Jiangsu Province, the integration of ICH resources and the tourism industry is relatively better in the southern (e.g., Nanjing, Suzhou), but there are still imbalances in development in the northern. Zhejiang Province has an overall higher degree of integration between ICH and the tourism industry compared to Jiangsu, with more balanced development. However, there is still room for improvement in the deep integration of ICH resources with the tourism industry.

A Human Pose Estimation Method Based on the BlazePose Model

Objective: This study aims to evaluate the performance of the BlazePose model in human pose estimation for sports actions to improve the accuracy and computational efficiency of the model. Methods: The research employed a variety of datasets for training and evaluating the model, investigating the generalization capability of the model under different experimental conditions. Detection and tracking were carried out through the two-stage mechanism of the BlazePose model, identifying the human figure contours and initially predicting the key points, and then refining the positions of the key points through the tracking module. Different parameters such as model complexity and key point smoothing were set, and the steps including image preprocessing, feature extraction, key point detection, naming, and skeleton construction were conducted. Results: The research outcomes yielded the two-dimensional keypoints of single-frame human body images and the construction of 3D coordinate models, and obtained the visualization line charts of PCK experimental data. Through the comparison of PCK scores of different models, it was concluded that on the basketball Dataset, the performance of BlazePose was superior to that of OpenPose, particularly in terms of FPS performance. Although the PCK score of the lightweight version of BlazePose was slightly lower, its FPS performance was higher, making it suitable for scenarios with high requirements for speed. Furthermore, BlazePose effectively reduced the model complexity by offering models of different complexities and using occlusion simulation in training, without sacrificing too much accuracy. Conclusion: This research presents the efficacy of lightweight neural networks in real-time human pose estimation and, through further experimental analyses, investigates the possibilities of enhancing their performance advantages and application effects.

Coupling Coordination Analysis Between Reclaimed Water Utilization Capacity and Effect in China

Reclaimed water utilization is one of the major strategies used to achieve sustainable development in China and for alleviating issues linked to insufficient water supply. This study leverages panel data encompassing 30 provinces in mainland China from 2011 to 2022 to establish a comprehensive evaluation index system for measuring the development level of reclaimed water utilization capacity and utilization effect. On the basis of this index, the development rule of coupling coordination between reclaimed water utilization capacity and utilization effect is explored using the coupling coordination degree model, Moran’s I index, and the grey GM (1,1) model. Experimental results show that the current utilization capacity and effect of reclaimed water in most provinces of China do not match. Moreover, China’s reclaimed water utilization capacity index was shown to gradually increase from 2011 to 2022. The reclaimed water utilization capacity index of the eastern region is significantly higher than the central region, which is lower than the national average, followed by the northeast region, and the western region obtains the lowest index. The calculation results of the coupling coordination model further demonstrate the coupling coordination degree between the reclaimed water utilization capacity; moreover, the effects of provinces and cities in China steadily increased, and there is a clear spatial clustering. The predicted results indicate that the abovementioned situation will likely continue until 2030. This study is anticipated to become a point of reference for relevant departments to optimize the coupling coordination degree of reclaimed water systems across different regions in China, implement differentiated measures, and promote a rational allocation of reclaimed water resources.

Spatiotemporal Changes and Influencing Factors of the Coupled Production–Living–Ecological Functions in the Yellow River Basin, China

The imbalance in the “production–living–ecology” function (PLEF) has become a major issue for global cities due to the rapid advancement of urbanization and industrialization worldwide. The realization of PLEF coupling and coordination is crucial for a region’s sustainable development. Existing research has defined the concept of PLEF from the perspective of land function and measured its coupling coordination level using relevant models. However, there is still room for improvement in the indicator system, research methods, and other aspects. This work builds a PLEF coupling coordination evaluation-index system based on the perspective of human habitat using multi-source data in order to examine the spatial differences in PLEF coupling coordination level and the influencing factors in the Yellow River Basin (YRB). Using the modified coupling coordination model, the Moran index, spatial Markov chain model, and geographically weighted random forest model were introduced to analyze its spatial and temporal differentiation and influencing factors. The results found that (a) the level of PLEF coupling coordination in the YRB from 2010 to 2022 has been improving, and the number of severely imbalanced cities has been reduced from 23 to 15, but the level of downstream cities’ coupling coordination is significantly higher than that of upstream cities. The probability of cities maintaining their own level is greater than 50%, and there is basically no cross-level transfer. (b) The Moran index of the PLEF coupling coordination level has risen from 0.137 to 0.229, which shows a significant positive clustering phenomenon and is continually strengthening. The intercity polarization effect is being continually enhanced as seen in the LISA clustering diagram. (c) There is significant heterogeneity between the influencing factors in time and space. In terms of importance level, the series is per capita disposable income (0.416) > nighttime lighting index (0.370) > local general public budget expenditure (0.332) > number of beds per 1000 people (0.191) > NO2 content in the air (0.110). This study systematically investigates the dynamic evolution of the coupled coordination level of PLEF in the YRB and its influencing mechanism, which is of great practical use.

The Temporal and Spatial Evolution and Influencing Factors of the Coupling Coordination Degree Between the Promotion of the “Dual Carbon” Targets and Stable Economic Growth in China

Coordinating the relationship between “dual carbon” targets and stable economic growth is crucial for promoting high-quality development in China. This study utilizes the coupling coordination model, kernel density estimation, and spatial econometric models to explore the temporal and spatial evolution characteristics and influencing factors of the coupling coordination degree between the promotion of the “dual carbon” targets and stable economic growth in 287 Chinese cities from 2011 to 2021. The results indicate that, in terms of temporal evolution, the promotion of China’s “dual carbon” targets increases yearly, while stable economic growth follows a “year-on-year increase—short-term decline—sustained recovery” pattern with the coupling coordination degree fluctuating upward. Regarding spatial evolution, the coupling coordination degree between the promotion of the “dual carbon” targets and stable economic growth in China presents a “higher in the east, lower in the west” spatial pattern, with varying gradient effects and polarization across the country and its regions. Influencing factors include government intervention, environmental regulations, energy efficiency, financial development, and R&D investment intensity. These findings provide scientific insights for addressing the mutual constraints between “dual carbon” targets and stable economic growth.

Exploring the Realization Level and the Obstacles Affecting Different Types of Ecological Product Value—A Typical Case from Zhejiang, China

The realization of ecological product value (EPV) is a crucial pathway for green economic development and the practical implementation of both the United Nations Sustainable Development Goals and China’s “Two Mountains Theory”, which emphasizes the need for harmony between ecological protection and economic growth. While China has initiated several pilot projects, there remains no consensus on the classification of ecological products or the measurement of EPV realization levels, largely due to limitations in the existing accounting systems, which fail to address EPV’s complexity. This study introduces a novel framework for measuring EPV realization, categorizing ecological products into pure public, quasi-public, and operational types. It demonstrates the economic value of ecological conservation, providing viable economic incentives for green development. This framework allows governments and businesses to see that protecting and sustainably utilizing natural resources can also yield economic benefits, thus offering a new feasible pathway for green development. Using Zhejiang Province as a case study, the authors present an improved coupling coordination model and a mechanical equilibrium model to assess EPV levels, emphasizing the importance of tailored regional strategies. Additionally, an obstacle degree model is employed to identify and analyze the factors limiting EPV realization. The results show that (1) different types of ecological products follow distinct value realization paths within the “economic–ecological–social” system; (2) EPV realization varies significantly across regions, with a trend of being lower in the southwest and higher in the northeast; (3) obstacles to value realization differ across subsystems, with particular attention needed to improve quasi-public ecological products in the ecological and social domains; (4) factors such as pesticide use and the number of tourist attractions affect EPV realization at the provincial and municipal levels, respectively. This study presents a new EPV measurement framework and highlights the spatial–temporal variability of EPV realization across regions. It provides valuable insights for developing countries and ecologically vulnerable areas seeking to optimize their EPV realization, supporting sustainable development and advancing “Two Mountains Theory” transformation.