Cities In Urban Agglomeration Research Articles

Assessment of network structure characteristics and factors of corporate flows in Guangdong Province.

With the rapid development of the world city network, the traditional location theory has gradually been disproven, and the advantages of the flow space over the traditional vertical organizational structure are gradually being revealed. Therefore, from corporate branch networks and corporate investment networks, 21 cities in urban agglomerations of Guangdong are taken as case studies for this paper. Furthermore, in this paper, 5 representative types of corporate contact data (catering service, financial service, life service, sports and leisure and accommodation service) are selected, the social network analysis (SNA) method is used to quantitatively analyze the network structure characteristics of urban agglomerations, and a spatial interaction model is constructed to explore the factors influencing. The results indicate that secondary networks have developed in Guangdong. The financial service network is the most complex, followed by the life services, sports and leisure and catering networks. The accommodation service network structure is the simplest. Among all kinds of networks, Guangzhou and Shenzhen have the highest status. The catering and accommodation corporations in Yangjiang in the west have a relatively major external development. Shantou in the east has many branches of various types, while most of the capital exchange in the region is concentrated in Heyuan and Qingyuan in the north. The coefficients of geographical proximity and the urban development level play a significant role in promoting the development of networks. However, administrative capacity limits the attractiveness of origin cities to a certain extent.

Study on the Coupling Coordination Development between the Digital Economy and Innovation Efficiency: Evidence from the Urban Agglomeration in the Middle Reaches of the Yangtze River

The urban agglomeration in the middle reaches of the Yangtze River holds a crucial strategic position in China’s economic and social development landscape. Exploring the coordinated development effects within the digital economy and innovation in this area is conducive to promoting the development of the central region of China and the Yangtze River Economic Belt. This paper uses the 28 sample cities in urban agglomeration in the middle reaches of the Yangtze River as the study sample, and constructs a digital economy indicator system and an urban innovation efficiency indicator system. Based on the coupling coordination degree model, we use kernel density estimation, the Markov chain algorithm, and the Dagum Gini coefficient decomposition method to empirically investigate the dynamic trends in coupling coordination development between the digital economy and urban innovation efficiency from 2012 to 2021. The research results reveal an overall upward trend in the digital economy, innovation efficiency, and coupling coordination development stages. However, the upward trend is accompanied by the risk of recession. Moreover, there are significant differences between cities, as highlighted by the differences between Wuhan and other cities. In the light of the findings, it is recommended that government departments take measures, including being alert to the risk of regressive development, developing cities in a realistic manner, and drawing on the experiences of outstanding cities in development. This research can provide new insights and empirical references for government entities to take measures for a more coordinated development of the digital economy and innovation efficiency in the urban agglomeration in the middle reaches of the Yangtze River.

A multi-scale unified model of human mobility in urban agglomerations

Understanding human mobility patterns is vital for the coordinated development of cities in urban agglomerations. Existing mobility models can capture single-scale travel behavior within or between cities, but the unified modeling of multi-scale human mobility in urban agglomerations is still analytically and computationally intractable. In this study, by simulating people's mental representations of physical space, we decompose and model the human travel choice process as a cascaded multi-class classification problem. Our multi-scale unified model, built upon cascaded deep neural networks, can predict human mobility in world-class urban agglomerations with thousands of regions. By incorporating individual memory features and population attractiveness features extracted by a graph generative adversarial network, our model can simultaneously predict multi-scale individual and population mobility patterns within urban agglomerations. Our model serves as an exemplar framework for reproducing universal-scale laws of human mobility across various spatial scales, providing vital decision support for urban settings of urban agglomerations.

Can new-type urbanization realize low-carbon development? A spatiotemporal heterogeneous analysis in 288 cities and 18 urban agglomerations in China

Cities and urban agglomerations are carriers of greenhouse gas emissions and show significant heterogeneity. China has entered a transitional period of new-type urbanization, which emphasizes high-quality and coordinated regional development. However, evidence of the spatiotemporal heterogenous effects of new-type urbanization on carbon emissions in cities, and especially in urban agglomerations are still lacking. This study estimated the new-type urbanization level and investigated its spatiotemporal heterogenous impacts on carbon dioxide emissions (CO₂) in 288 Chinese cities and 18 urban agglomerations. The results show that for each 1% increase in new-type urbanization level, the median estimation of CO₂ emissions per capita can decrease by 171.0% (46.8%,338.4%) at city-level. The inverted “U-shaped” relationships between new-type urbanization and CO₂ emissions per capita were observed in more than 60% of the cities. The average impacts of new-type urbanization and its square term of the cities which are located in urban agglomerations are estimated to be approximately 0.8 and 1.7 times of cities that are not, which indicates that cities in urban agglomerations are peaking their CO₂ emissions per capita with a higher enhancement of new-type urbanization. The results add new insights for formulating dynamic phase-to-phase carbon reduction policies and urban planning in cities and urban agglomerations.

Smart Energy Urban Agglomerations in China: The Driving Mechanism, Basic Concepts, and Indicator Evaluation

The development of urban agglomerations and smart energy systems in China are tightly connected. However, basic concepts of this interdisciplinary connection are still lacking. To fill this gap, this paper proposed an item of “Smart Energy Urban Agglomeration” (SEUA), and studied its driving mechanism, basic concepts in China, and indicator evaluation of typical urban agglomerations. Firstly, by a theorical analysis, the driving mechanism of SEUA was concluded as of “internal and external driven by two axes”, whereas national policies and cities’ spontaneity are external and internal driving forces, and two axes are urban planning and energy system integration. Secondly, using system approaches, its concept connotation, development barriers, and action suggestions were proposed based on China’s conditions. Thirdly, an indicator evaluation based on the driving mechanism was carried out to reveal the differences of four urban agglomerations, with relevant explanations. The results indicated that the Yangtze River Delta had the highest level of SEUA development because of its good performance in both axes. Meanwhile, the cities’ spontaneity had a stronger driving force than national policies. Therefore, it is urgent for China’s government to integrate the urban and energy planning among cities in urban agglomerations.

Carbon emissions accounting and prediction in urban agglomerations from multiple perspectives of production, consumption and income

Urban agglomerations (UAs) play a momentous role in carbon reduction. The prerequisites for achieving carbon reduction goals in UAs are accounting and predicting their carbon emissions. When considering carbon reduction goals in China, it is crucial to pay attention to the joint influence of carbon emissions and economic benefits. Hence, in this study, an improved multi-regional input–output (MRIO) approach was established to quantify and predict carbon emissions for the UA, incorporating a biproportional scaling method (RAS) and Latin hypercube sampling (LHS). Specifically, a) the carbon emissions of UAs were quantified using the MRIO model from the perspectives of production, consumption and income; b) the carbon flows between cities in UAs were identified based on final demand and primary inputs, and c) the features of UAs’ carbon emissions in the future were predicted using RAS and LHS. To verify the effectiveness of the approach, a case study of a typical UA region in China [i.e., the Pearl River Delta (PRD)] was proposed. The results showed that the contribution of sectors to carbon emissions could be identified from multiple perspectives, and carbon flows can help regions coordinate emissions reductions. The majority of future carbon emissions would be generated from the areas of population and economic agglomeration (i.e., Guangzhou and Shenzhen), although the growth trend of carbon emissions of those would keep lower. The policy of carbon reduction should be urgently carried out in locations with high carbon emissions growth rates (e.g., Zhaoqing and Zhuhai). To improve the ability for carbon reduction in the PRD, cooperation in multiple cities to promote energy efficiency is advocated. The government should also increase technical support for carbon reduction and consider the balanced development of the economy, population, and resources in the PRD.

Whether polycentric spatial structure is conducive to regional coordinated development: A study on urban agglomerations in China

AbstractWith the aggravation of congestion, pollution, and other negative externalities generated by continued urbanization, polycentric strategies have gradually become one of the main urban and regional spatial strategies. It remains unclear, however, whether the polycentric structure is conducive to regional coordinated development. This study examines these issues using China's urban agglomerations (UAs) as a sample. The Prolonged Artificial Nighttime‐light Dataset of China (PANDA) was used to measure the polycentric structure. The results of the nonparametric identification of sub‐centers show that almost all of China's UAs exhibit multiple (sub)centers, and the number of (sub)centers in most UAs has increased from 1992 to 2020. Empirical analysis shows that a polycentric structure is beneficial for narrowing regional disparities within the UA, and the narrowing effect of the polycentric structure on regional disparities increases as the distance between centers increases. Furthermore, a polycentric spatial structure is more conducive to the economic growth of small cities in UA, thereby promoting the coordinated development of regions within UA.

Analysis on the structure and economic resilience capacity of China’s regional economic network

ABSTRACT This paper analyzes the heterogeneous influence of economic networks on urban economic resilience capacity from different network characteristics, providing an innovative research perspective and theoretical framework for the economic resilience capacity of urban clusters. The urban economic elasticity is measured by multiple indicators and constructed economic network using night light data, the complex network approach was combined with spatial econometrics to analyse the contribution of economic network linkages and economic network locations to regional economic resilience capacity. The results show that: urban economic network linkage has a significant positive impact on urban economic resilience capacity, and the polycentric pattern of urban clusters has a driving effect on this impact; in contrast, the influence of urban network location on economic resilience capacity has an inverted u-shaped curve. Compared with non-smart cities, regions in smart cities are better able to promote urban economic resilience capacity through economic networks, and the impact of economic networks on regional economic resilience capacity has network external spillover effects beyond geographical distance, The results of the study infer that cities in urban agglomeration should rationalize network locations, and build a coordinated urban agglomeration network structure to enhance economic resilience capacity of the regional economy.

Urban Agglomeration High-Speed Railway Backbone Network Planning: A Case Study of Beijing-Tianjin-Hebei Region, China

In order to optimize the network layout of urban agglomerations, improve the comprehensive benefits of transportation networks and promote the sustainable development of urban agglomerations, this paper studies the main trunk line selection model of the Beijing–Tianjin–Hebei high-speed railway (HSR). Firstly, the characteristics of cities in urban agglomeration are analyzed, and the economic capacity, transportation capacity, passenger turnover and network characteristics of urban nodes are selected as evaluation indexes. A node importance model and a line urgency model were established to obtain the value of the importance of urban nodes and the urgency of each line in the urban agglomeration. Secondly, the DBSCAN is used to cluster the city nodes, and the city nodes are divided into four grades. With the goal of maximizing the urgency of the lines and considering the constraints of the urban node level, the optimization model of the Beijing–Tianjin–Hebei backbone network selection is constructed. The backbone lines of the Beijing–Tianjin–Hebei urban agglomeration are obtained, and the selection results of backbone lines are analyzed, which lays a foundation for the design and optimization of the HSR operation scheme in urban agglomeration. The planned backbone network can basically realize the commuting between the important urban nodes in the Beijing–Tianjin–Hebei urban agglomeration to achieve the goal of driving and alleviating the operation of the branch line. It can accelerate the development of the internal traffic of the urban agglomeration. In addition, it has certain practical significance and practical value.

Linking supply-demand balance of ecosystem services to identify ecological security patterns in urban agglomerations

Ecological security patterns (ESP) is an effective approach to identify the priority conservation areas and maintain regional ecological security. The previous ESP studies only focused on the supply of ecosystem services (ESs), but ignored the supply-demand interaction of ESs. In this study, a novel large-scale ESP framework was proposed by introducing the supply-demand scarcity of ESs to revise identification of ecological sources. According to the scarcity theory “the severer ESs imbalance, the higher priority of protection”, the ESs scarcity supply capacity (ESSSC) was reconstructed by combining ESs supply with two adjust factors of the urgency of regional eco-protection (UEP) and the priority of ESs type (PET). Finally, ecological sources integrating ESSSC and ecological sensitivity, ecological corridors, and ecological nodes were identified to establish a cross-regional ESP. The results show: (1) the reconstructed ESSSC approach significantly increased ecological sources areas of developed cities in urban agglomerations with the severer overall and structural imbalance, and effect of PET exceeds UEP; (2) appropriate allocation of key protection areas in regions with low supply but high demand and the priority protection of the severely imbalanced ESs types can alleviate environmental injustice; and 3) the extracted 160 ecological corridors and 16 ecological nodes effectively enhanced connectivity among ecological sources (36.2% of the study area), and formed a complete and connected ESP. The scarcity idea for regional coordination can guide the trans-administrative ecological decision making.

Regional characteristics and spatial correlation of haze pollution: Interpretative system analysis in cities of Fenwei Plain in China

Urban agglomeration is an important model for promoting global economic development and has made important contributions to global economic integration. However, as the core area of urbanization and industrialization, urban agglomerations also contribute to air pollutant emissions primarily due to the agglomeration of population and industry. The mutual influence of air pollution between different cities in urban agglomerations has brought significant challenges to global environmental governance. The Fenwei Plain is one of the most severely polluted areas in China. We collected daily average PM2.5 concentration data of 11 cities in the Fenwei Plain, China in 2019. We then developed an interpretive structural model to statistically analyze the spatial correlation and hierarchical transmission of haze pollution between the 11 cities. The results showed that haze pollution has a strong systematic correlation between the 11 cities, and a regional haze pollution community has formed throughout the region. Haze pollution also exhibits evident transmission and spatial correlations between the cities. The transmission starts from Baoji and ends at Sanmenxia, with mutual interactions between the cities of Xi'an, Xianyang, Weinan, Tongchuan, Jinzhong, Lvliang, Linfen, Yuncheng, and Luoyang. Thus, air pollution prevention and control in the Fenwei Plain should consider the spatial correlation of haze pollution between different cities, especially in autumn and winter, and should rationally be implemented in key urban cluster areas. We recommend building a coordinated governance between cities to improve the overall air quality. Our findings shed a light for coordinated pollution management in urban agglomerations worldwide.

Assessing the Development Level of Logistics for Sustainable Cities in Urban Agglomeration Based on a Multi-Layer Complex Network

Evaluating the development level of urban logistics can significantly inform policies for the sustainable development of each city in an urban agglomeration. This study analyzed the logistics development of 11 cities in the Guanzhong Plain urban agglomeration (GPUA) of China. Compared to traditional urban logistics evaluation methods considering individual attributes, this study constructed a multi-layer complex logistics network of urban agglomerations (MCLNUA) based on complex network theory, which takes into account the multiple connections between cities. The development levels of logistics in these cities were evaluated from a multi-dimensional perspective of “point–line–surface”, (the “point” represents the node characteristic index of the city, the “line” represents the strength and direction of urban logistics connections between cities, and the “surface” represents the cohesive subgroup of cities). An urban spatial hierarchy and corresponding spatial development plan for urban logistics were also developed. The results show that there are significant differences in logistics levels between different cities. The spatial structure of the overall network connections shows the pattern of being strong in the south and weak in the north, and strong in the east and weak in the west. There are differences in the strength of connections between cohesive subgroups. The research provides a reference for the sustainable development of regional logistics in other urban agglomerations.

Horizontal ecological compensation as a tool for sustainable development of urban agglomerations: Exploration of the realization mechanism of Guanzhong Plain urban agglomeration in China

Horizontal ecological compensation can promote the division of labour and collaboration among cities in urban agglomerations (UAs) and coordinate the relationship between socioeconomic development and ecological protection through payments from ecological beneficiary cities to contributor cities. However, it’s difficult to determine the compensation subjects and standard. This study uses ecological footprint (EF) and ecosystem service value (ESV) to calculate the horizontal ecological compensation standard. The ecological compensation weight is introduced to calculate the horizontal ecological compensation payment or acceptance values (HECVs) to determine the compensation subjects and objects. And we take China’s Guanzhong Plain urban agglomeration (GPUA) as an example for empirical analysis. The results show that the EF of the GPUA has the characteristics of nonequilibrium. Except for the only ecologically functional city, all other cities had ecological deficits (EDs), and the spatial distribution of the ESV in each city was significantly different, which shows that the GPUA has the conditions to establish a horizontal ecological compensation mechanism. Further research results show that higher GDP and lower ESV mean higher HECVs, key ecological function cities have the largest HECVs, and key economic development cities pay the most HECVs. This horizontal ecological compensation method regulates the relationship among stakeholders through the migration of ESV, and solves the actual problems of “who compensates whom” and “how much to compensate”. It provides strong technical support for the formulation of horizontal ecological compensation schemes for UAs in developing countries and is conducive to maintaining environmental justice and promoting the sustainable development of UAs.

Research on collaborative management and optimization of ecological risks in urban agglomeration

Collaborative governance is increasingly advocated to address the ecological risk management issues that occur during urban agglomeration developing. However, how to form strong and effective collaboration is still a great challenge among multiple cities in urban agglomeration. By analysing the multiple ecological risk transmission pathways of the case of Pearl River Delta Urban Agglomeration (PRD) in China, this paper aims at deconstructing the complex structure and connection types in urban agglomeration, as well as exploring the inherent mechanism of ecological risk governance to achieve collaboration. Thus, a new Bayesian network model of ecological risk transmission is developed to visualize the key connection notes of risk transmission process. Testing the impacts of (1) number of collaborative cities, (2) spatial distance factor and (3) risk transmission links, we can find the optimal cooperative risk management strategy by reducing the probability of occurrence of key nodes and intervening on the critical path of the risk transmission process. The results show that (1) The current collaborative governance plan in the PRD is mainly formulated by large cities driving small surrounding cities, which is not an optimal strategy. (2) The management effect of ecological risks in urban agglomerations is not necessarily positively correlated with the number of collaborative cities. There are multiple combinations methods under a certain number of collaborative cities and the effects of ecological risk collaborative governance are different. (3) Collaboration governance of urban agglomeration should be based on the overall planning of urban development, and comprehensively consider collaboration number, spatial distance and association between cities.

Research on the Heterogeneity of Carbon Emissions under the Government’s Promotion of Urban Agglomeration Development: Empirical Evidence from County-to-District Reforms

County-to-district reform (CTDR) is an important policy path for the government to promote the cultivation and construction of urban agglomerations, and exploring its “carbon emission” effect is of great significance for the high-quality development of urban agglomerations and the realization of the “dual carbon” goal. Based on the panel data of 120 counties in the Yangtze River Delta urban agglomeration from 2000–2017, this paper empirically tests the effect of county-to-district reforms on per capita carbon emissions in the counties of the central and peripheral cities of the Yangtze River Delta urban agglomeration under the Kutznets curve (EKC) hypothesis and the integrated difference-in-difference (DID) model and STIRPAT model. The results show that: (1) The carbon emission effect of county-to-district reforms have significant regional heterogeneity. The reforms of the central city of the urban agglomeration significantly reduced the per capita carbon emission of the county by 4.27%, whereas the reforms of the periphery cities of the urban agglomeration significantly increased per capita carbon emission by 6.56%. (2) The impact of county-to-district reforms on county per capita carbon emissions began to appear in the fourth year of reform. (3) Mechanism analysis showed that county-to-district reforms promoted central cities population agglomeration and reduction of carbon emission intensity can help reduce the per capita carbon emission level in counties, whereas peripheral cities have a dual carbon-increasing effect of decreasing population density and increasing carbon emission intensity. Therefore, the approval of county-to-district reforms should be strictly controlled, and the reform of non-central cities would be especially prudent, so as to reduce the negative effect of reform on the high-quality development of cities.

Does Fiscal Stress Improve the Environmental Efficiency? Perspective Based on the Urban Horizontal Fiscal Imbalance

The resilience of the fiscal system has a driving effect on environmental governance, and it is always a challenge to solve the problem of matching fiscal power with administrative power. Based on the panel data of 193 cities in China from 2013 to 2018, the data envelopment analysis method was used to evaluate the comprehensive indicators of urban environmental efficiency. The impact of fiscal stress on environmental efficiency is examined from the perspective of urban horizontal imbalance. We find that the smaller the fiscal stress, the higher urban environmental efficiency. The endogeneity is mitigated by using instrumental variables and the generalized method of moments, and the results are still robust after considering the interference of sample selection bias and variable estimation bias. At the same time, the impact of fiscal stress on environmental efficiency varies with spatial location, ecological strategic planning, economic development, and other factors, especially in southern cities, cities in the Yangtze River Basin, and cities in urban agglomerations, where reducing fiscal stress promotes environmental efficiency. In addition, green production and public environmental services are important channels for its role, and the rational allocation of self-raised funds can effectively moderate the improvement of environmental efficiency.

Towards balanced development stage: Regulating the spatial pattern of agglomeration with collaborative optimal allocation of urban land

Urban agglomeration is an important carrier that promotes urbanization into an advanced stage, addressing its unbalanced development is an important task for the newly established territorial spatial planning in China. This research proposed a collaborative optimal allocation of urban land (COAUL) model which provides a simulation tool both for the quantity and spatial structure optimization of urban agglomeration. COAUL first optimizes the quantity structures of every city according to the current situation, potential development capacity and spatial policy. And then the optimized quantity structure is assigned into geo-space with land use spatial optimization model. COAUL has been applied to Guangdong-Hong Kong-Macao Greater Bay Area (GBA), a fast-developing urban agglomeration located in Southern China, and three main findings are obtained: (1) COAUL model can optimize the quantity and spatial structure of urban agglomeration for the goal of balanced development, which could provide scientific reference scenario for the delimitation of the urban agglomerations growth boundaries (UAGB). (2) As cities in urban agglomeration have strong connections with each other, collaborative optimal allocation of urban land could considerably relieve the pressures of developed central cities and also promote the growth of undeveloped edge cities. (3) COAUL can unlimitedly reduce the imbalanced development tendency of urban agglomeration, which is performance better than traditional land use planning models. This research demonstrated that delimiting the UAGB with COAUL model is an important government measure for promoting the balanced development of urban agglomeration areas.

Too Big or Too Small? The Threshold Effects of City Size on Regional Pollution in China.

The relationship between urban agglomeration and environmental pollution was checked using the balanced panel data of 285 cities in China from 2003 to 2016 and applying the fixed-effect model and the threshold effect model. This showed that: (1) the relationship between urban agglomeration (represented by city size) and environmental pollution is not linear but an inverted U-shape. As long as the GDP is less than 800,370 million RMB, the expansion of city size is not conducive to reducing pollutant emissions. When GDP is less than 41,641 million RMB, the influence of city expansion on environmental pollution is relatively less. When GDP is higher than 800,370 million RMB, the city expansion may reduce pollutant emission. (2) The city size is not too big but is in fact too small. Only 18 cities experienced the inverted U-shape with the expansion of their city size, causing the gas and water pollutant emissions to decrease. (3) For cities in an urban agglomeration, environmental pollution can be reduced by expanding the city size through coordinated development of urban agglomeration. In conclusion, for most large cities in urban agglomerations in China, the city size is not too large but too small.

Pathways for sustainable municipal energy systems transition: A case study of Tangshan, a resource-based city in China

Cities consume most of the global energy and account for approximately 75% of global CO2 emissions. Moreover, resource-based cities tend to consume higher amounts of fossil fuel and produce higher carbon emissions than other cities, whereas there are still insufficiencies about energy carbon reduction in resource-based cities in developed urban agglomerations. Therefore, it is necessary to explore the energy planning of such cities to achieve carbon peaking and carbon neutrality, and this is crucial for achieving carbon neutrality in urban agglomerations. This study aims to apply a scenario-based analysis approach to a resource-based heavy industrial city in China, Tangshan, based on the Long-range Energy Alternative Planning model, to explore Tangshan's future energy consumption, generation, and associated carbon emissions from 2010 to 2050. The impacts of different energy policies are analyzed for the Tangshan energy system by considering four scenarios. Under each scenario, energy consumption increased steadily by 2050, but the growth rate is different. The business as usual scenario is the fastest, and the low-carbon scenario is the slowest. In the comprehensive and integrated low-carbon transition scenarios, CO2 is expected to peak at 298.34 million tons (Mt) in 2028. The main industrial sectors of Tangshan with high output value, high energy consumption, and high carbon emissions include smelting and pressing of ferrous metals, petroleum processing and coking, raw chemical materials and chemical products, etc. Combining Tangshan's coal resource endowment, the development of renewable energy, and introducing advanced technology can effectively reduce carbon emissions and increase the diversity of energy supply. We analyzed the cost-benefit of the energy system and found that the implementation of carbon capture and storage technology could effectively reduce carbon emissions by 219.62 Mt and increased costs by 563.12 billion yuan. The research could provide a scientific basis for the medium and long-term energy sustainable transformation of resource-based cities, especially for resource-based cities in urban agglomerations.

Analysis of socio-economic spatial structure of urban agglomeration in China based on spatial gradient and clustering

Research background: Previous studies on the economic and social development of urban agglomerations mostly focus on a single primacy comparative analysis and efficiency evaluation. Spatial structure differentiation is an important feature of urban agglomeration. The lack of economic and social analysis on the spatial structure makes it impossible to determine the development positioning of each city in the urban agglomeration, which affects the sustainable economic devel-opment ability of these areas.
 Purpose of the article: The objective of the article is to analyze the spatial development law and experience of urban agglomeration, this study explores the practice of economic and population spatial structure of city areas in China. For this purpose, CPUA and its central city Zhengzhou was taken as an example, the spatial gradient structure of example was analyzed.
 Methods: Using economic and population data of 32 cities in this region, growth pole theory, and pole-axis theory, the economic and population spatial structure of urban agglomeration, the spatial gradient structure of central cities in urban agglomerations were analyzed with the method of cluster about radiation index.
 Findings & value added: (1) In the process of the formation of CPUA, the geo-graphical spatial pattern plays a decisive role in economic and social development. This is an experience from developing countries. (2) CPUA presents a gradient development pattern with Zhengzhou as the center, and economic and social development gradually radiates to the metropolitan area, the core development area, and the character development demonstration area. (3) The economic and social gradients of Zhengzhou, the central city, present the hierarchy rules and characteristics which are driven by the Beijing-Guangzhou-Railway axis and the Longhai-Railway axis. (4) The central city of Zhengzhou still presents insufficient primacy in regional development, which shows that Zhengzhou accounts for 6% of the population of the Central Plains Economic Zone and 14% of GDP, and insufficient agglomeration. Different countries at different stages of economic development have different urban agglomeration development models. The conclusions from China provide new decision-making ideas and methods for spatial structure research and development strategy analysis of urban agglomerations.