Yangtze River Delta City Research Articles

Enhancing urban flood resilience: A coupling coordinated evaluation and geographical factor analysis under SES-PSR framework

Urban flooding has emerged as a significant urban issue in cities worldwide, with China being particularly affected. To effectively manage and mitigate urban floods, a holistic examination of the interaction between urban subsystems is required to improve urban flood resilience. However, the interactions and mechanisms between urban subsystems under flood disaster haven't been addressed adequately in previous studies. Therefore, this paper established a conceptual framework for illustrating the interactions between urban natural-ecological and social-economic subsystem considering urban pressure, state, and response within flood cycle. The objective is to investigate the coupling coordination degree (CCD) between these subsystems and identify the driving factors with a geographical detector model, and the cities in Yangtze River Delta are selected as an empirical example. The findings reveal an overall upward trend towards coordination for the whole area with notable variability among the cities. The resilience of the state dimension emerges as a crucial aspect in determining the CCD of the urban flood resilience of the area. Key driving factors for the coordinated development of urban flood resilience are identified as air pollution, global warming, technological innovation, governance power, financial strength, and urbanization. Based on the findings and the interactions among the driving factors, this paper presents potential implications that can serve as effective guidance and offer insights for policymakers, planners, and researchers in their efforts to enhance urban flood resilience for sustainable development in the future.

Design and Evaluation of Ecological Index for Small and Medium-sized Cities in Yangtze River Delta

Design and Evaluation of Ecological Index for Small and Medium-sized Cities in Yangtze River Delta

Health Benefit Impact Relationship and its Health Benefit Assessment of Greenspace in Yangtze River Delta Cities

Health Benefit Impact Relationship and its Health Benefit Assessment of Greenspace in Yangtze River Delta Cities

A study of the economic growth effects of market integration: An examination of 27 cities in the Yangtze River Delta city cluster.

The city cluster of the Yangtze River Delta is a highly dynamic and competitive economic region in China. The integration of the market across the 27 cities is crucial in driving economic growth in the area. This paper aims to provide policymakers with recommendations on promoting regional integration, enhancing the structure, and improving overall performance. By utilizing the benefits and resources of each community more effectively, greater economic gains can be achieved. The findings of this study can also be applied to other Chinese towns or business areas. Market integration is a necessary foundation for regional integration, as it enables the seamless movement of goods and factors throughout the region while simultaneously reducing entry barriers and supporting the creation of a unified market. Unfortunately, the "vassal economy" model has impeded the region's economic growth. The integration of regional markets is crucial for economic growth. However, it is equally important to create industrial clusters with central towns as their hubs. The Yangtze River Delta urban agglomeration is a prime example of one of six world-class city clusters demonstrating how market integration can result in high-quality economic progress. The paper's primary discoveries are threefold: firstly, there has been a progressive elevation in the level of market integration among the 27 cities within the Yangtze River Delta city cluster, characterized by increasingly intimate connections concerning trade, investment, and population mobility. Secondly, this heightened market integration exerts a catalytic impact on the real economic growth of the Yangtze River Delta city cluster, particularly concerning regional industrial restructuring, transformation, and upgrading. Finally, market integration is poised to expedite the industrial division of labor and synergistic development between the cities, thus promoting a concentration of advanced manufacturing and new industries in the central cities and furthering the development of profitable industries in the central individual cities.

The Impact of Green Innovation Capacity on Urban Economic Resilience: Evidence from China’s Yangtze River Delta Region

Urban green innovation plays a crucial role in achieving sustainable urban economic development, and urban economic resilience is an important manifestation of urban economic development. This prese nt study aims to investigate how green innovation contributes to urban economies’ resilience, which is essential for long-term urban agglomeration expansion and sustainable economic development. To decrease subjectivity and achieve comprehensive evaluation, this study first constructs an index system for evaluating green innovation capability on urban economic resilience, which contains 21 indicators in three areas, including innovation input, innovation output, and green innovation foundation, and the performs a scientific evaluation using the TOPSIS method. On this basis, using the Super-SBM model, the green innovation efficiency value of cities in the Yangtze River Delta (YRD) is calculated. Finally, ArcGIS 10.8 software is used to classify the economic resilience of the 26 cities in the YRD city cluster and analyze the spatial layout characteristics of urban economic resilience. The results show that: (1) the decision evaluation model used in this study is stable and effective, and it can effectively address the issues of subjective assessment processes and information redundancy; (2) green innovation capacity has a positive contribution to urban economic resilience, and its contribution is more significant for cities with strong economic strength; and (3) the green innovation capacity of the YRD city cluster is unevenly distributed, with Shanghai, Suzhou, Hangzhou, and Nanjing having high levels of green innovation capacity and strong urban economic resilience, thus forming the core area of cities radiating outward, showing a “core-edge” spatially. Finally, suggestions for improving the overall economic resilience of urban agglomerations are provided.

Retracted: Grey Correlation Analysis of Low-Carbon Governance in Yangtze River Delta Cities.

[This retracts the article DOI: 10.1155/2022/2029087.].

Large-Scale Surface Deformation Monitoring Using SBAS-InSAR and Intelligent Prediction in Typical Cities of Yangtze River Delta

Large-scale short-term monitoring and prediction of surface deformation are of great significance for the prevention and control of geohazards in rapidly urbanizing developing cities. Most studies focus on individual cities, but it would be more meaningful to address large urban agglomerations and consider the relevance of the regions within them. In addition, the commonly used linear fitting prediction methods cannot accurately capture the dynamic mechanisms of deformation. In this study, we proposed an automatic PS extraction method (named PS-SBAS-InSAR) that improves SBAS-InSAR to extract surface deformation and an Informer-based short-term surface deformation prediction method for case studies in 16 typical cities of the Yangtze River Delta (YRD). The results show that PS-SBAS-InSAR successfully extracted accurate surface deformation sequences of the YRD. During the period from January 2019 to January 2021, the YRD experienced a slight deformation with an average deformation rate within [−4, 4] mm/year. Geographically neighboring cities may have associated deformation distributions and similar deformation trends, as indicated by average deformation rate maps and landscape metrics. Both types of deformation (i.e., subsidence/uplift) tend to occur simultaneously, with specific areas of subsidence/uplift occurring in close proximity to areas of concentrated deformation. The Informer model effectively captured the time-series variation in surface deformation, suggesting a slowdown of deformation over the next two months (February 2021–March 2021). Our work contributes to a better understanding of changes and trends in large-scale surface deformation and provides useful methods for monitoring and predicting surface deformation in coastal areas.

Carbon emission reduction effects in Yangtze River Delta from the dual perspectives of forest resource endowment and low-carbon pilot policy in the digital age

Although Chinese society has transformed into the digital age, carbon peaking and neutrality are still important starting points for implementing the national strategy of green and low-carbon integrated growth in the Yangtze River Delta (YRD) of China. With data from 41 cities in YRD from 2005 to 2019, this paper empirically analyzes the carbon emission reduction effects from dual perspectives of forest resource endowment and low-carbon pilot policy in the digital age. The findings include: (1) Forest resources are indeed conducive to reducing carbon emissions. However, when considering the carbon sequestration effect of forests, a nonlinear U-shaped relationship exists between forest resource abundance and net carbon emissions per GDP. (2) Low-carbon city pilot policies are effective in reducing carbon emissions. (3) Low-carbon pilot policies perform better in smart cities, resource-based cities, and cities with abundant forest resources, showing significant heterogeneity. Forests can be relied on to assist in carbon emission reduction in the short term, but in the long term, a forest ecosystem with biodiversity is needed to achieve low-carbon sustainable development. This article provides some experience and references for building green and carbon-neutral cities for YRD in the digital age.

Evaluation of urban resilience in the post-COVID-19 period: A case study of the Yangtze delta city group in China

The coronavirus disease 2019 outbreak poses a new test for improving the resilience of cities in the face of public health emergencies, and a scientific evaluation of urban resilience is a key step towards improving such resilience. This study uses the post-pandemic period as the research perspective to establish an evaluation index system comprising six dimensions, namely infrastructure, ecological, social, economic, information elements and technology environment. The study also uses a combination of weighting and grey correlation Technique for Order of Preference by Similarity to Ideal Solution comprehensive evaluation method to empirically analyse the urban resilience of 27 cities in the Yangtze River Delta city group. The study found that significant spatial distribution differences exist in urban resilience. Moreover, the higher-, high- and medium-resilient cities are mostly located on the eastern coast of the Yangtze River Delta in Jiangsu and Zhejiang Province, whereas the lower- and low-resilient cities are mainly located in the inland area of Anhui Province. In addition, different aspects of resilience exist, which are shortcomings for each city. The above results indicate that the model is valuable for evaluating urban resilience in the post-pandemic period, and thus, the model can help policymakers formulate proposals to effectively improve urban resilience.

Coupling and coordinated development of low-carbon economy and green finance: an empirical study of the Yangtze River Delta region in China.

The introduction of China's double carbon target has led to a new stage in the development of China's low-carbon economy, while the development of China's green finance is also facing new challenges. Based on the determining of the relationship between low-carbon economy and green finance, this study selected the Yangtze River Delta city cluster of China, an exemplary region for the development of low-carbon economy and green finance, constructed a multi-level comprehensive index system covering two systems of low-carbon economy and green finance and conducted a coupled and coordinated relationship analysis based on the panel data of green finance and low-carbon economy-related indicators from 2016 to 2020. The empirical results showed that the interaction between the low-carbon economy system and the green finance system in the Yangtze River Delta region gradually weakened during 2016-2020, and the mechanism of interaction between the two systems has not been fully developed and utilized. Overall, the development of green finance in all four provinces and cities has not gained sufficient momentum, which is a constraint to the coupled and coordinated development of low-carbon economy and green finance in the four provinces and cities in the Yangtze River Delta. Zhejiang Province and Jiangsu Province performed better in terms of the scale of green finance and the use of diversified instruments, while Shanghai City performed better in terms of low-carbon economy, whereas Anhui Province needs to improve in both low-carbon economy and green finance.

The intermediary effect of intelligent Amap-related traffic efficiency on haze pollution

To determine the effect of intelligent traffic system (ITS) Amap on environmental benefits, this research employs the innovative approaches including the entropy-weighted method, super-efficiency slacks-based measure and spatial intermediary model to measure the ITS Amap-related traffic efficiency and its intermediary effect on environmental benefits using data from 17 key Chinese cities. Overall, the research finds that traffic congestion in China has mitigated between 2014 and 2020 due to the ITS Amap system, transportation infrastructure and traffic regulation policies. However, the overall Amap-related traffic efficiency has increased but remains within the ineffective range. Furthermore, the ITS Amap-related traffic efficiency has significant intermediary role on haze pollution mitigation for all cities. And traffic efficiency has positive spatial spillover on haze pollution mitigation in its neighboring cities. Specifically, the ITS Amap-related traffic efficiency is higher and more stable in both the Yangtze River Delta and Beijing–Tianjin–Hebei cities. The greatest intermediary alleviation effect on haze pollution is observed in the Yangtze River Delta cities, while the weakest effect is observed in the Chengdu–Chongqing inland cities.

Assessing the impact of urban form and urbanization process on tropospheric nitrogen dioxide pollution in the Yangtze River Delta, China

Optimizing urban form through urban planning and management policies can improve air quality and transition to demand-side control. Nitrogen dioxide (NO2) in the urban atmosphere, mainly emitted by anthropogenic sources such as industry and vehicles, is a key precursor of fine particles and ozone pollution. Both NO2 and its secondary pollutants pose health risks for humans. Here we assess the interactions between urban forms and airborne NO2 pollution in different cities with various stages of urbanization in the Yangtze River Delta (YRD) in China, by using the machine learning and geographical regression model. The results reveal a strong correlation between urban fragmentation and tropospheric NO2 vertical column density (TVCD) in YRD cities in 2020, particularly those with lower or higher levels of urbanization. The correlation coefficients (R2) between NO2 TVCD and the largest patch index (a metric of urban fragmentation) in different cities are greater than 0.8. For cities at other urbanization stages, population and road density are strongly correlated with NO2 TVCD, with an R2 larger than 0.61. This study highlights the interdependence among urbanization, urban forms, and air pollution, emphasizing the importance of customized urban landscape management strategies for mitigating urban air pollution.

Empirically investigating the organizational identity mechanism of empowering leadership affecting the innovation performance of knowledge workers

PurposeThe authors examined how the identification mechanism of the innovation performance of knowledge employees is affected by empowering leadership by influencing the organizational identification and the moderating effect of leaders on the role expectation of knowledge employees as an essential innovation subject.Design/methodology/approachThe authors employed a mixed-method research approach. The authors collected data from 378 knowledge employees and managers in 20 companies in China's Yangtze River Delta cities. The authors analyzed data using multiple regression analysis forecasting methods.FindingsThe authors found that there was an inverted U-shaped relationship between empowering leadership and the innovation performance of knowledge employees; organizational identity played a partial mediating role between empowering leadership and the innovation performance of knowledge employees; role expectation of leaders on the innovation behavior of employees regulated the relationship between the organizational identity and innovation performance of knowledge employees.Originality/valueThis study extends the literature on empowering leadership and innovation performance. This study empirically examines the mediating effect of organizational identity between empowering leadership and innovation performance. In addition, this study empirically examines how empowered leaders' expected innovation level moderates the association between organizational identity and innovation performance.

Analysis of spatial and temporal carbon emission efficiency in Yangtze River Delta city cluster — Based on nighttime lighting data and machine learning

Improving carbon emission efficiency(CEE) is crucial to reducing CO2 emissions. Most studies on CO2 emission are conducted at national and industrial scales, and city-scale studies still need to be included. In order to collect more consistent city- and county-scale CO2 emission data, the sparrow search neural network is trained to fit the energy consumption CO2 emissions with nighttime light in this study. Additionally, using the SBM-DEA model and spatial econometric techniques, the CEE values of 27 cities in the Yangtze River Delta region (YRDR) from 2000 to 2020 were examined from the perspective of total factor inputs. The findings demonstrate that CEE's general trend is erratic and uneven. The CEE value of the YRDR decreases from 0.720 in 2000 to 0.628 by 2020, which means that the YRDR has redundant capital and labour inputs and insufficient economic output. The low value carbon efficiency areas are mainly concentrated in the western part of the YRDR, i.e. the Anhui Province region. Shanghai, Wuxi and Suzhou have high carbon efficiency values of 1.21, 2.08 and 1.00 respectively, and are exemplary cities in terms of carbon efficiency, while the rest of the cities have varying degrees of efficiency loss. Taking Chizhou-Jiaxing as the middle line, the CEE pattern in the YRDR presents a state of “low in the middle and high at each end,” and center of gravity for CEE generally shifts southward. Additionally, the cold-spot areas of CEE are concentrated in the southern part of Anhui Province, and develop a low-efficiency zone with Chizhou, Anqing, and Xuancheng as clusters and spreading outwards. Overall, this paper significantly narrows the spatial scale of carbon accounting studies and the findings can be applied to the formulation of customized carbon reduction policies.

The role of digital governance on carbon emission performance: evidence from the cities in yangtze river delta, China

Rapid industrialization and ambitious socio-economic targets have presented significant challenges to China’s carbon neutrality process. However, digital transformation offers new opportunities for sustainable development. This research examines the influence of digital governance (Digov) on carbon emission performance (Cep) and explores its underlying mechanisms. The study utilizes data from cities in China’s Yangtze River Delta from 2011 to 2019. The results show that digital governance has significantly improved carbon emission performance, a conclusion that remains robust even after conducting a series of rigorous tests and addressing endogeneity concerns. The main impact mechanisms of digital governance on carbon emission performance include energy intensity reduction, energy consumption scale reduction, industrial structure adjustment, and energy consumption structure optimization.Furthermore, the results indicate that the variation in carbon emission reduction due to digital governance can be attributed to differences in city administrative level, city size, and government capacity. In particular, digital governance plays a pivotal role in facilitating the sustainable transformation of resource-based cities.From the perspective of digital governance, this study provides effective recommendations and valuable insights for achieving low-carbon targets and promoting sustainable development of cities.

Identification and Measurement of Shrinking Cities Based on Integrated Time-Series Nighttime Light Data: An Example of the Yangtze River Economic Belt

Urban shrinkage has gradually become an issue of world-concerning social matter. As urbanization progresses, some Chinese cities are experiencing population loss and economic decline. Our study attempts to correct and integrate DMSP/OLS and NPP/VIIRS data to complete the identification and measurement of shrinking cities in China’s Yangtze River Economic Belt (YREB). We identified 36 shrinking cities and 644 shrinking counties on the municipal and county scales. Based on this approach, we established the average urban shrinkage intensity index and the urban shrinkage frequency index, attempting to find out the causes of shrinking cities for different shrinkage characteristics, city types and shrinkage frequencies. The results show that (1) the shrinking cities are mainly concentrated in the Yangtze River Delta city cluster, the midstream city cluster and the Chengdu–Chongqing economic circle. (2) Most shrinking cities have a moderate frequency of shrinking, dominated by low–low clusters. Resource-based, heavy industrial, small and medium-sized cities are more inclined to shrink. (3) The single economic structure, the difficulty of industrial transformation and the lack of linkage among county-level cities are possible reasons for the urban shrinkage in the YREB. Exploring the causes of urban shrinkage from a more micro perspective will be an inevitable task for sustainable development in YREB and even in China.

Current situation, bottlenecks, and path options for the development of capital flows and integration in the Yangtze River Delta region

IntroductionCapital plays a crucial role in the development of regional economies, especially in low-income regions where it acts as a primary driver of economic growth. Efficient capital flow is essential for optimizing resource allocation and facilitating the development of integrated capital markets. This passage introduces the topic of capital, capital flow, and capital market integration and highlights their significance in regional development.MethodsTo gain a comprehensive understanding of capital flow and integration in the Yangtze River Delta region, the researchers conducted a connotative analysis. They constructed indicators from various aspects, including social fixed asset investment, bank capital flow, government transfer payments, social financing structure, and foreign direct investment. By utilizing these indicators, the researchers aimed to assess the current situation and identify bottlenecks related to capital flow and integration. Additionally, they drew on experiences from foreign capital flow and integration development to enrich their analysis.ResultsThe analysis revealed several primary bottlenecks affecting capital flow and integration in the Yangtze River Delta region. These bottlenecks include an unsound banking management system, the presence of government competition and administrative barriers, and shortcomings within listed companies. The results highlight the specific challenges that hinder the smooth functioning and integration of capital in the region.DiscussionTo promote the development of capital flows and integration in the Yangtze River Delta region, the researchers propose various recommendations. These suggestions include promoting the development of listed companies, establishing a robust banking management model, improving relevant government policies, and optimizing the investment environment. These recommendations serve as important guidelines for policymakers to enhance capital flow and integration in the Yangtze River Delta city cluster. Furthermore, they emphasize the need to strengthen financial supervision and improve institutional mechanisms within the three provinces and one city comprising the region.

Air quality prediction by integrating mechanism model and machine learning model

AQP (Air Quality Prediction) is a very challenging project, and its core issue is how to solve the interaction and influence among meteorological, spatial and temporal factors. To address this central conundrum, we make full use of the characteristics of mechanism model and machine learning and propose a new AQP method based on DM_STGNN (Dynamic Multi-granularity Spatio-temporal Graph Neural Network). This method is the first time to use the air quality model HYSPLIT (Hybrid Single-Particle Lagrangian Integrated Trajectory Model) to assist in building a dynamic spatio-temporal graph structure to learn the spatiotemporal relationship of pollutants. DM_STGNN is based on an elaborate encoder-decoder architecture. At the encoder, in order to better mine the spatial dependency, we built a multi-granularity graph structure, used meteorological, time and geographical features to establish node attributes, used well-known HYSPLIT model to dynamically establish the edges among nodes, and used LSTM (Long Short Term Memory) to learn the time-series relationship of pollutant concentrations. At the decoder, in order to better mine the temporal dependency, we built an attention mechanism based LSTM for decoding and AQP. Additionally, in order to efficiently learn the temporal patterns from very long-term historical time series and generate rich contextual information, an unsupervised pre-training model is used to enhance DM_STGNN. The proposed model makes full use of and fully considers the influence of meteorological, spatial and temporal factors, and integrates the advantages of mechanism model and machine learning. On a project-based dataset, we validate the effectiveness of the proposed model and examine its abilities of capturing both fine-grained and long-term influences in AQP. We also compare the proposed model with the state-of-the-art AQP methods on the dataset of Yangtze River Delta city group, the experimental results show the appealing performance of our model over competitive baselines.

Abundance, characteristics, and removal of microplastics in different wastewater treatment plants in a Yangtze River Delta city of China

Microplastics (MPs) have become emerging environmental pollutants worldwide. Wastewater treatment plants (WWTPs) are considered to be the major source and sink of MPs in the terrestrial and aquatic environment. The present study has been carried out for Nanjing, a typical Yangtze River Delta city in China. In this work, the abundance and characteristics of MPs were investigated in the influent of four WWTPs, and the removal effect of different treatment processes was studied in the two advanced tertiary treatment WWTPs. In the influent, the abundance of MPs of industrial WWTPs (IWWTPs) was higher than that of municipal WWTPs (MWWTPs), with a dominant size of 38–63 μm. MP shapes were mainly distributed in fragments and fibers, with polymer species of polypropylene (PP) and polyethylene (PE). In the final effluent, MPs were removed by 93.81 % in IWWTPs versus 88.10 % in MWWTPs, which were mainly influenced by the tertiary treatment technology. The tertiary treatment showed significant differences with the removal efficiency of 61.58 % in IWWTPs, equipped with a high-density sediment tank, and 30.40 % in MWWTPs, equipped with a denitrification filter. This study provides comprehensive information about the MPs' characteristics and fate contained in different sewage of WWTPs and analyzes the tertiary treatment effect of MPs, expecting to provide constructive support for the improvement of management strategies in WWTPs technologies.

The opening of high-speed rail and environmental pollution of the Yangtze River Delta Region in China-based on SDID model test.

In recent years, environmental problems have attracted attention at home and abroad, so exploring the causes of environmental pollution has become a research content for scholars. The opening of high-speed railway has improved the economic development of China's Yangtze River Delta, and with the economic growth, the construction of high-speed railway has also led to environmental pollution in China's Yangtze River Delta. Therefore, using the data from 41 prefecture-level cities in China's Yangtze River Delta from 2003 to 2020, the SDID model was constructed, and the comprehensive index of environmental pollution was calculated by factor analysis to calculate the impact of high-speed railway construction on environmental pollution in China's Yangtze River Delta. The conclusions are as follows: The opening of high-speed railway significantly reduces the overall pollution level in China's Yangtze River Delta. The opening of high-speed rail has played a role in restraining the environmental pollution of the first and second tier cities and the third and fourth tier cities, but the pollution level of the third and fourth tier cities has decreased significantly.