Coupling Interaction Study of New-Type Urbanization and Low-Carbon Development in Ningxia Urban Agglomeration Along the Yellow River

ZHOU Tao¹, WANG Yajuan¹, LIU Xiaopeng²,³

¹School of Economics and Management, Ningxia University, Yinchuan 750021, Ningxia, China
²Undergraduate School, Ningxia University, Yinchuan 750021, Ningxia, China
³School of Geography and Planning, Ningxia University, Yinchuan 750021, Ningxia, China

Abstract

This study examines the coupling and interactive relationship between new-type urbanization and low-carbon development to support the transformation of new urbanization, promote carbon emission reduction, and foster regional high-quality development. Based on panel data from the Ningxia urban agglomeration along the Yellow River from 2012 to 2022, this research investigates the spatiotemporal evolution of coupling coordination, interactive response relationships, and influencing factors between new-type urbanization and low-carbon development using a modified coupling coordination model, panel vector autoregression (PVAR) model, and Tobit model. The results indicate: (1) The coupling coordination degree between new-type urbanization and low-carbon development in the Ningxia urban agglomeration along the Yellow River continues to improve, gradually forming a spatial pattern characterized by "one pole with multiple cores." (2) A long-term equilibrium relationship exists between new-type urbanization and low-carbon development, though the degree of interaction remains relatively low. The promoting effect of new-type urbanization on low-carbon development is stronger than that of low-carbon development on new-type urbanization. (3) Factors such as urbanization level and environmental governance contribute to enhancing the coupling coordination degree, while industrialization level emerges as a key factor hindering the benign coordinated development of the two systems.

Keywords: new-type urbanization; low-carbon development; coupling coordination; interactive response; Ningxia urban agglomeration along the Yellow River

Introduction

With the acceleration of urbanization in China, urban population growth, infrastructure expansion, and the proliferation of energy-intensive industries have significantly increased energy consumption, leading to a substantial rise in carbon emissions. The contradiction between rapid urbanization construction and carbon reduction goals has become increasingly prominent. Urbanization represents an essential path to modernization, and urban agglomerations serve as the primary spatial carriers for new-type urbanization. The National New-Type Urbanization Plan (2014–2020) explicitly states that urban agglomerations should be economically vibrant, offer excellent quality of life, and maintain a beautiful ecological environment. During the 14th Five-Year Plan period, China has issued a series of documents including the National New-Type Urbanization Report (2020–2021) and the 14th Five-Year Plan Implementation Plan for New-Type Urbanization, emphasizing the continued focus on urban agglomerations as the main spatial form and striving to build green cities that are efficient, clean, and low-carbon. The high-quality development of new urbanization and low-carbon transformation in urban agglomerations are inseparable, with their successful implementation urgently relying on low-carbon development models that complement each other. Therefore, exploring the coupling and interaction between new-type urbanization and low-carbon development in urban agglomerations is crucial for achieving new urbanization goals, realizing the "dual carbon" objectives, and constructing high-quality urban agglomerations.

New-type urbanization, as a high-quality urbanization model centered on people, featuring industry-city integration, intensive resource use, and ecological livability, provides support for low-carbon development. By improving public service systems and constructing ecological spatial networks, it enhances resource allocation efficiency and environmental quality, thereby promoting residents' well-being. It drives industrial restructuring, facilitates the specialized upgrading of the service sector and the clean transformation of manufacturing, and accelerates improvements in energy utilization efficiency. Through rational planning, it creates industrial spaces with high technology and low energy consumption, high-quality living spaces for residents, and urban ecological carbon sink spaces, significantly enhancing urban ecological carrying capacity and sustainable development levels. Meanwhile, low-carbon development promotes new-type urbanization. Green economic growth injects economic vitality and technological momentum into urbanization, while resource and environmental constraints compel enterprises to optimize energy consumption patterns, driving urbanization toward intensive, efficient, and green transformation. Under the guidance of ecological concepts and policy drivers, low-carbon development guides industrial upgrading and spatial layout optimization, facilitating high-quality new-type urbanization. Additionally, low-carbon development emphasizes development goals of "prosperous living and sound ecology," which highly aligns with the "people-oriented, ecologically livable" concept of new-type urbanization, providing value orientation and practical foundation for their coupling and interaction.

Current research on new-type urbanization and low-carbon development primarily focuses on three aspects. First, studies on the relationship between urbanization and carbon emissions have verified their correlation through quantitative analysis models, demonstrating that various factors affect carbon emissions during urbanization. Second, research on specific pathways for low-carbon urbanization development has proposed recommendations from perspectives such as planning system optimization, institutional innovation, and governance mechanism improvement. Third, studies on coupling coordination between new-type urbanization and low-carbon development have applied coupling coordination models for empirical analysis. For instance, Zong et al. analyzed the spatiotemporal coupling relationship between new-type urbanization and low-carbon development at the provincial scale from 2005 to 2019. Overall, existing research provides important references for clarifying the relationship between urbanization and low-carbon development and achieving high-quality urban development. However, content-wise, previous studies have focused more on the unidirectional impact of urbanization on carbon emissions and specific pathways, with insufficient explanation of the internal mechanisms of coupling interaction between the two systems and limited research on influencing and constraining factors for their coordinated development. Methodologically, coupling coordination models have been primarily used to explore coordination relationships, with less attention paid to dynamic relationships and temporal characteristics. From a research perspective, existing literature has concentrated on eastern coastal regions and economically developed urban agglomerations, while relatively less attention has been paid to less-developed urban agglomerations with fragile ecological environments. These urban agglomerations face multiple pressures from economic development, resource and environmental constraints, and carbon reduction during urbanization, making coordinated development of new-type urbanization and low-carbon development a key challenge.

The Ningxia urban agglomeration along the Yellow River, a typical underdeveloped urban agglomeration in Northwest China and an important component of the national "two vertical and three horizontal" urbanization strategic pattern, faces challenges in urbanization construction including insufficient basic public services, low-level county service facilities, limited integrated development of the urban agglomeration, and inadequate ecological construction and protection. Resource-based cities also face heavy industrial structures and path dependency in green and low-carbon transformation. Against this backdrop, the synergistic advancement of new-type urbanization and low-carbon development demonstrates regional complexity and interactivity, urgently requiring analysis from a systematic perspective. This study takes cities in the Ningxia urban agglomeration along the Yellow River as research objects to explore their coupling coordination relationship and spatiotemporal evolution characteristics, clarify the interactive response relationship between the two systems, and identify influencing factors of their coupling coordination degree, aiming to provide references for low-carbon urbanization construction in this region and similar areas.

1 Data and Methods

1.1 Study Area Overview

The Ningxia urban agglomeration along the Yellow River is located in the middle and upper reaches of the Yellow River, geographically situated between 36°66′–39°58′N and 104°28′–106°89′E, with terrain gradually transitioning from hills to plains from south to north. The region specifically includes Yinchuan City, Shizuishan City, Wuzhong City (Litong District), Shapotou District, Qingtongxia City, Lingwu City, Zhongning County, Yongning County, Helan County, and Pingluo County—ten cities and counties in total. This region accounts for approximately 43% of the province's land area but carries 80% of its urban population and economic activities, having initially formed an urban agglomeration pattern that serves as the core area for Ningxia's economy, culture, and ecology, occupying an important position in national and autonomous region development strategies.

1.2 Indicator System and Data Sources

Referring to existing studies, this research constructs an indicator system for new-type urbanization in the Ningxia urban agglomeration along the Yellow River from five dimensions: economy, society, population, ecology, and land use. Using the DPSIR model, it builds a low-carbon development indicator system from five aspects: low-carbon driving force, low-carbon pressure, low-carbon state, low-carbon impact, and low-carbon response (Table 1). The entropy method is employed to calculate indicator weights.

Social and economic data primarily come from official statistical sources including the Ningxia Statistical Yearbook (2013–2023), China Urban and County Construction Statistical Yearbook (2013–2023), and statistical yearbooks of various cities, with some data obtained through secondary calculations. Carbon emission data are derived from the EDGAR v6.0 annual grid data provided by the Global Atmosphere Research Emission Database. PM2.5 data are obtained from the Atmospheric Composition Group of Washington University in St. Louis. Data on the frequency of energy conservation and emission reduction-related terms in government work reports are extracted from government work reports of the Ningxia urban agglomeration along the Yellow River, quantifying terms such as "energy conservation," "emission reduction," "low-carbon," and "dual carbon" using text计量 methods. Missing data are supplemented by consulting national economic and social development statistical bulletins, government work reports, and using linear interpolation.

1.3 Methods

1.3.1 Modified Coupling Coordination Model

The coupling coordination model can reflect the strength of interaction between subsystems or sub-elements and the overall development degree of the system. Due to issues such as low validity and simplified calculations in traditional coupling coordination models, this study adopts a modified model to measure the coupling coordination relationship between new-type urbanization and low-carbon development. The calculation formulas are as follows:

$$
C = \frac{1}{n-1} \left( \frac{\prod_{i=1}^{n} U_i}{\sum_{i=1}^{n} U_i} \right)
$$

$$
T = \sum_{i=1}^{n} \alpha_i U_i, \quad \sum_{i=1}^{n} \alpha_i = 1
$$

$$
D = \sqrt{C \times T}
$$

Where: C represents the coupling degree, with higher values indicating stronger interconnection between subsystems; T represents the coordination degree, indicating the contribution of subsystems to coordination; D represents the coupling coordination degree; U_i and U_j are the comprehensive evaluation indices of the i-th and j-th systems; n is the number of subsystems; α_i are undetermined coefficients representing the contribution share of subsystems. This study involves two subsystems, with α_1 = α_2 = 0.5, indicating equal importance. Referring to existing literature, the coupling coordination degree between new-type urbanization and low-carbon development is classified (Table 2).

1.3.2 Relative Development Model

To clarify the relationship between the two subsystems, this study introduces a relative development model to judge the synchronous development status of the two systems in the Ningxia urban agglomeration along the Yellow River. The formula is as follows:

$$
E = \frac{U_1}{U_2}
$$

Where: E represents the relative development degree; U_1 and U_2 are the comprehensive evaluation indices of new-type urbanization and low-carbon development, respectively. Based on existing research, the types are classified as follows: when E > 1.2, new-type urbanization leads low-carbon development; when 0.8 ≤ E ≤ 1.2, new-type urbanization and low-carbon development develop synchronously; when E < 0.8, low-carbon development lags behind new-type urbanization.

1.3.3 PVAR Model

This study establishes a Panel Vector Autoregression (PVAR) model and employs impulse response and variance decomposition to analyze the dynamic interactive response relationship between the two systems. The model is specified as follows:

$$
Y_{it} = \theta_0 + \sum_{j=1}^{p} \theta_j Y_{i,t-j} + \eta_i + \mu_t + \varepsilon_{it}
$$

Where: Y_{it} represents the comprehensive evaluation indices of new-type urbanization and low-carbon development; i and t represent region and year, respectively; θ_0 is the intercept term; θ_j is the parameter matrix; j is the lag order; η_i and μ_t represent individual and time effects, respectively; ε_{it} is the random disturbance term.

2 Results

2.1 Temporal Evolution Characteristics of New-Type Urbanization and Low-Carbon Development Levels

Using the entropy method, the comprehensive evaluation indices of new-type urbanization and low-carbon development in the Ningxia urban agglomeration along the Yellow River are calculated (Figure 2). Overall, from 2012 to 2022, the new-type urbanization level in the Ningxia urban agglomeration along the Yellow River steadily increased, with the mean comprehensive evaluation index rising from 0.168 to 0.350. Yinchuan City and Shizuishan City ranked at the forefront, with their evaluation indices exceeding 0.4 since 2015 and maintaining continuous growth. In contrast, Helan County started from a lower baseline, with a comprehensive evaluation index of only 0.089 in 2012, but significantly improved its new-type urbanization level during the 12th and 13th Five-Year Plan periods through infrastructure strengthening and industrial upgrading, reaching 0.185 in 2022—a 107.73% increase and the fastest growth rate among all cities. This indicates that while the overall trend of new-type urbanization in the Ningxia urban agglomeration along the Yellow River is positive, significant differences exist among cities in terms of progress speed and effectiveness.

The low-carbon development level in the Ningxia urban agglomeration along the Yellow River showed a fluctuating upward trend overall, with the mean comprehensive evaluation index increasing from 0.210 to 0.323. Yinchuan City stood out in low-carbon development, with its comprehensive evaluation index reaching 0.510 in 2012, ranking first in the region and maintaining its lead. Lingwu City lagged behind in low-carbon development, with its evaluation index at only 0.134 in 2012, consistently ranking last, and increasing to merely 0.194 by 2022, indicating significant challenges in low-carbon transformation. This is because Lingwu City, as an energy production base, relies primarily on fossil fuels in its energy structure and has a high proportion of secondary industry, which constrains the pace of low-carbon development. Overall, while gaps among cities in the agglomeration narrowed during the study period, differences in resource endowments and industrial structures led to varying progress in urban low-carbon development pathways.

2.2 Coupling and Coordination Development Analysis

Based on formula (1), the coupling coordination degree between new-type urbanization and low-carbon development for each city in the Ningxia urban agglomeration along the Yellow River from 2012 to 2022 is calculated (Figure 3). From a temporal perspective, the coupling coordination interval evolved from "transitional development" to "coordinated development," with the mean coupling coordination degree increasing from 0.497 to 0.564, showing a slight upward trend, though significant variations exist among cities.

In 2012, only Yinchuan City (0.512) and Zhongning County (0.498) were in the "on the verge of imbalance" stage, while other cities were in the "barely coordinated" stage. By 2016, Wuzhong City (0.527), Qingtongxia City (0.523), Shapotou District (0.521), and Lingwu City (0.521) entered the "primary coordination" stage, while Helan County (0.494) remained in the "barely coordinated" stage. By 2022, Yinchuan City (0.654) and Shizuishan City (0.617) reached the "primary coordination" stage, Helan County (0.543) and Zhongning County (0.545) entered the "barely coordinated" stage, and Yinchuan City (0.654) became the first to reach the "intermediate coordination" stage. The gaps among cities narrowed, though coordination levels in southern regions remained relatively low. Overall, the spatiotemporal evolution of coupling coordination in the Ningxia urban agglomeration along the Yellow River exhibits certain radiation effects, with cities like Yinchuan and Shizuishan leveraging their economic, technological, and industrial advantages to drive coordinated development in surrounding cities through regional cooperation, demonstration effects, and resource factor flows.

Spatially, the coupling coordination spatial pattern evolved from "high in the north, low in the south" to "one pole with multiple nuclei" (Figure 4). In 2012, Yinchuan City had the highest coupling coordination degree, while most cities in the central and southern regions had lower coordination levels, presenting a "high in the north, low in the south" pattern. Subsequently, Shizuishan City, Shapotou District, and other cities saw significant improvements in their coupling coordination degrees, gradually forming a "one pole with multiple nuclei" pattern. Helan County and Zhongning County remained in the "on the verge of imbalance" or "barely coordinated" stages for some time, lagging behind other cities. By 2022, all cities in the agglomeration achieved coupling coordination degrees above 0.5, entering the primary coordination stage, indicating good interaction between new-type urbanization and low-carbon development and significant progress in high-quality development and low-carbon urbanization transformation.

The mean relative development degree of the Ningxia urban agglomeration along the Yellow River was below 0.8, indicating overall characteristics of new-type urbanization lagging behind low-carbon development. From 2012 to 2022, low-carbon development led new-type urbanization in all cities, with no cities achieving synchronous development. This may be because the Ningxia urban agglomeration along the Yellow River faces relatively slow new-type urbanization progress due to weak infrastructure, large urban-rural gaps, and insufficient public service supply, with long-term planning and capital investment needs further exacerbating development pressures. In contrast, low-carbon development has advanced relatively faster, benefiting from policy support and resource advantages. Documents such as the Ningxia Hui Autonomous Region Climate Change Action Plan provide institutional guarantees and policy foundations for low-carbon construction, with pilot cities like Yinchuan, Shizuishan, and Wuzhong demonstrating exemplary effects that drive regional low-carbon development. Lingwu City, due to its high dependence on resource-based industries, experienced persistent low-carbon development lag from 2012 to 2022, facing considerable challenges in industrial transformation.

2.3 Interactive Response Analysis

The PVAR model is estimated with a lag order of 2, and Monte Carlo simulations with 500 iterations are used to obtain impulse response functions between new-type urbanization and low-carbon development, thereby exploring the interactive effects and response relationships between the two systems. Figure 5 shows that when new-type urbanization faces a one-unit shock from itself, it exhibits strong positive effects, peaking in the current period and then declining slowly, without fully converging by period 10, indicating strong dynamic cumulative effects and path dependency in its improvement. When low-carbon development faces a one-unit shock from new-type urbanization, the response is strong in period 2, then begins to decline but remains positive. This demonstrates that industrial structure upgrading and green infrastructure construction have stable and lasting effects on low-carbon development, though these positive impacts do not manifest immediately due to lag effects from industrial adaptation, changes in residents' concepts, and policy implementation.

When new-type urbanization faces a one-unit shock from low-carbon development, the effect intensity increases from period 1 to period 2, then declines and gradually stabilizes. This indicates that mechanisms such as capital investment, resource and environmental constraints, and technological innovation effectively drive urbanization toward intensive, efficient, and green transformation. When low-carbon development faces a shock from itself, it peaks in the current period, then declines and approaches convergence after period 5. This suggests that while initial investment and policy support can stimulate emission reduction potential in the short term, their effects gradually weaken over time, and achieving sustained and stable low-carbon development still requires reliance on technological innovation and institutional optimization.

Variance decomposition is further employed to examine the contribution degree of shock variables to endogenous variables at period 10. The results for the Ningxia urban agglomeration along the Yellow River (Table 4) show that new-type urbanization's contribution to itself remains stable at over 98%, demonstrating strong self-driving mechanisms. Low-carbon development's contribution to new-type urbanization increases from 1.833% in period 1 to 9.167% in period 10, with its influence gradually strengthening. This indicates that the low-carbon transformation development of the urban agglomeration has a driving effect on new-type urbanization, though its significant improvement still mainly relies on its own development inertia. Low-carbon development's variance decomposition shows that its contribution rate is 100% in period 1, with all impact coming from itself, but drops to only 66.738% in period 2, rapidly declining to 33.262% by period 10. This suggests that low-carbon development has significant short-term effects but requires external momentum for long-term sustainability. The horizontal comparison indicates that new-type urbanization's contribution rate to low-carbon development is consistently higher than low-carbon development's contribution rate to new-type urbanization, demonstrating that new-type urbanization has a more significant promoting effect on low-carbon development.

2.4 Analysis of Influencing Factors of Coupling Coordination Degree

Referring to existing studies, this research constructs a panel Tobit model selecting economic development level, urbanization level, industrialization level, government capacity, city size, and environmental governance level as explanatory variables, with the coupling coordination degree between new-type urbanization and low-carbon development as the dependent variable, to analyze the impact of various factors on the agglomeration's coupling coordination degree. The specific model is set as follows:

$$
D_{it} = \beta_0 + \beta_1 Gdp_{it} + \beta_2 Ur_{it} + \beta_3 Ind_{it} + \beta_4 Gov_{it} + \beta_5 Ucl_{it} + \beta_6 Env_{it} + u_{it}
$$

Where: D_{it} is the coupling coordination degree between new-type urbanization and low-carbon development; Gdp_{it} is economic development level, measured by per capita GDP; Ur_{it} is urbanization level, measured by the proportion of urban population to total permanent population; Ind_{it} is industrialization level, measured by the proportion of secondary industry value-added; Gov_{it} is government capacity, measured by per capita fiscal expenditure; Ucl_{it} is city size, measured by the proportion of urban construction land area to urban district area; Env_{it} is environmental governance, measured by the harmless treatment rate of domestic waste; β_0 is the constant term; β_1–β_6 are coefficients of explanatory variables; u_{it} is the random disturbance term.

The regression results (Table 5) show that economic development level, urbanization level, government capacity, city size, and environmental governance have positive effects on the coupling coordination degree between new-type urbanization and low-carbon development, with the magnitude of positive effects being urbanization level (0.003) > environmental governance (0.002) > economic development level (0.001). Industrialization level has a negative effect (-0.005). Economic development level shows a positive impact on coupling coordination at the 5% significance level, though the estimated coefficient is small. While economic growth drives infrastructure improvement and upgrading, it fails to simultaneously enhance urban functional quality and low-carbon development levels. Moreover, the quality and structure of economic growth in the urban agglomeration still require optimization. In 2022, the operating income of high-tech industries in Ningxia accounted for only 14.0% of regional GDP, with the industrial structure still dominated by resource-based and traditional manufacturing industries, and the agglomeration effects of capital, technology, and other factors not yet fully realized.

Urbanization level has a significant positive effect on coordinated development at the 1% level. Holding other variables constant, a one-unit increase in urbanization level raises the coupling coordination degree by 0.003 units. Urbanization reduces production costs and enhances inter-firm collaboration and communication through population, industry, and resource agglomeration, generating technological spillover effects that improve resource utilization efficiency and accelerate low-carbon technology diffusion, thereby promoting coordinated development. The industrialization level coefficient is negative, indicating that an increase in the proportion of secondary industry negatively impacts the coupling coordination degree between new-type urbanization and low-carbon development. Holding other variables constant, a one-unit increase reduces the coupling coordination degree by 0.005 units. In 2022, the proportion of secondary industry in the Ningxia urban agglomeration along the Yellow River reached 47.6%, significantly higher than the national average of 39.9%. The industrial system dominated by resource-intensive industries has high energy consumption, constraining the coordinated development process. Although cities are promoting energy conservation, carbon reduction, and green industry development in traditional industries, technological path dependence, insufficient environmental protection investment, and weak regulatory mechanisms still fail to effectively support the low-carbon urbanization process. This echoes the variance decomposition results showing weak feedback from low-carbon development to new-type urbanization.

Government capacity has a positive but non-significant impact on coupling coordination degree. This may be because current fiscal expenditure in Ningxia is biased toward basic needs such as social security and employment, with limited support for low-carbon urbanization. As low-carbon policies advance, increased fiscal support for urban function optimization and low-carbon technology research and development may make the promoting effect of government capacity more apparent. City size has a positive impact on coupling coordination at the 5% significance level. Holding other variables constant, a one-unit increase raises the coupling coordination degree by 0.002 units. This result supports compact city theory, where high-density and multi-functional land development effectively curbs urban sprawl, promotes intensive resource utilization, and reduces carbon emissions while improving urbanization levels. Environmental governance positively affects coupling coordination degree. Holding other variables constant, a one-unit improvement raises the coupling coordination degree by 0.002 units. Strengthening environmental governance enhances urban carrying capacity and ecological environmental quality, thereby promoting the coupling coordination degree between new-type urbanization and low-carbon development.

3 Discussion and Conclusion

3.1 Discussion

Examining the coupling interaction relationship and influencing factors between new-type urbanization and low-carbon development is significant for enhancing the new-type urbanization level of the Ningxia urban agglomeration along the Yellow River, promoting regional high-quality development, and achieving the "dual carbon" goals. The study finds that the coupling coordination degree between new-type urbanization and low-carbon development in the Ningxia urban agglomeration along the Yellow River shows a continuous growth trend, consistent with research conclusions that the coupling coordination degree between urbanization and ecological protection in the Yellow River Basin is generally rising. This study reveals the phenomenon of low coupling coordination degree in the upper Yellow River Basin urban agglomerations from a smaller micro-scale perspective. The PVAR model demonstrates the relationship between the two systems from another dimension. Impulse response graphs show that a long-term equilibrium relationship exists between the two systems, with mutual promotion in the early stage but relatively low benign interaction, gradually stabilizing thereafter. Variance decomposition results indicate that the development of both systems mainly relies on their own inertia, with new-type urbanization having a more significant promoting effect on low-carbon development.

Overall, the Ningxia urban agglomeration along the Yellow River has achieved certain results in economic, social, and ecological development, but achieving the "dual carbon" goals and advancing new-type urbanization still requires multi-level and multi-faceted efforts. First, differentiated low-carbon development pathways should be constructed. As a central city, Yinchuan should fully leverage its leading function, promoting the integration of technological innovation and "Internet+" economy in low-carbon scenarios. Resource-based cities like Shizuishan should optimize energy structures and explore green industry substitution pathways. Lingwu City should strengthen collaborative development with the Ningdong Base, promoting green upgrading of the coal industry. All cities should develop "six new, six special, and six excellent" industries according to local conditions, building a complementary industrial system that promotes regional coordinated development and green low-carbon transformation. Second, the quality of county-level urbanization should be improved. Counties such as Helan and Zhongning should accelerate the improvement of infrastructure and public service shortcomings, building a satellite town system with complementary functions and industrial coordination to enhance county-level urban carrying and agglomeration capacities. Third, regional联动 development should be strengthened. As an important component of the Yellow River "Ji" character bay metropolitan circle, the urban agglomeration should leverage its location advantages to deepen industrial cooperation and ecological co-governance with surrounding urban agglomerations, enhancing its own development resilience and competitiveness.

3.2 Conclusion

1) During the study period, the comprehensive evaluation index of new-type urbanization in the Ningxia urban agglomeration along the Yellow River showed a steady upward trend overall, while the comprehensive evaluation index of low-carbon development showed a fluctuating upward trend overall, with differences in new-type urbanization and low-carbon development levels among different cities.

2) The coupling coordination interval between new-type urbanization and low-carbon development in the urban agglomeration evolved from "transitional development" to "coordinated development," showing a slight upward trend. The spatial pattern of coupling coordination evolved from "high in the north, low in the south" to "one pole with multiple nuclei." Most cities experienced new-type urbanization lagging behind low-carbon development.

3) New-type urbanization and low-carbon development have a long-term equilibrium relationship, with mutual promotion in the early stage but low benign interaction, gradually stabilizing thereafter. Variance decomposition results show that the development of both systems mainly relies on their own inertia, with new-type urbanization having a more significant promoting effect on low-carbon development.

4) Economic development level, urbanization level, city size, and environmental governance all help promote the coupling and coordinated development of new-type urbanization and low-carbon development in the Ningxia urban agglomeration along the Yellow River, while industrialization level is a key factor hindering their benign coordinated development.

This study provides references for the Ningxia urban agglomeration along the Yellow River to achieve low-carbon urbanization transformation and "dual carbon" goals, as well as for differentiated development and policy implementation within the region. However, limitations exist: considering that different urban agglomerations have different economic structures and resource endowments, research conclusions may vary due to regional characteristics. Future research could expand perspectives to conduct comparative studies on urban agglomerations with different development models and resource endowments to deeply reveal regional differences and influencing mechanisms of low-carbon urbanization.

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