Chinese Cities Research Articles

Measurement and Influencing Factors of Regional Economic Resilience in China

The COVID-19 outbreak in 2020 has underscored the paramount importance of regional economies’ capacities to withstand and adapt to external shocks. Enhancing regional economic resilience and mitigating the adverse impacts on both the economy and society have emerged as critical imperatives for ensuring the sustainable development and transformation of the national economy. This paper employs an improved counterfactual method to measure the economic resilience index across 31 Chinese provinces and cities from 2001 to 2021, coupled with empirical analysis using a dynamic panel model to identify the influencing factors of regional economic resilience. Building upon this foundation, the study delves into the heterogeneous effects of various factors and different degrees of marketization on economic resilience across different regions. Research Findings: (1) There has been a significant improvement in the economic resilience levels of China’s 31 provinces, with differences in economic resilience between regions far exceeding those in economic development levels, indicating substantial internal regional disparities. (2) Factors such as the marketization index, industrial structure, level of informatization, labor force size, labor quality, innovation capacity, and degree of government intervention all impact regional economic resilience and exhibit regional heterogeneity. Policy Recommendations: (1) It is crucial to address regional disparities while formulating regional development strategies and enhancing regional economic resilience. (2) Regions should accelerate market-oriented reforms, promote rational labor mobility, strengthen investment in human capital, foster innovation, and adjust the degree of intervention.

Factor Analysis of EV Purchase Behavior in Medium-sized Cities in China:

Factor Analysis of EV Purchase Behavior in Medium-sized Cities in China:

Acceptance and willingness to pay for DTaP-HBV-IPV-Hib hexavalent vaccine among parents: A cross-sectional survey in China

ABSTRACT DTaP-HBV-IPV-Hib hexavalent vaccine has been used in high-income countries for many years to prevent diphtheria, tetanus, pertussis, hepatitis B, poliomyelitis, and invasive Haemophilus influenzae type b disease. Currently, no hexavalent vaccines have been approved for use in China. Evidence of parental acceptance and interest in hexavalent vaccines can help policy makers and manufacturers make decisions about entering the vaccine market and the immunization program in China. We measured parental acceptance and willingness-to-pay (WTP) for a hexavalent vaccine to provide such evidence. We conducted a cross-sectional survey of children’s caregivers in 16 vaccination clinics in seven cities in China and obtained information on socio-demographics, knowledge of disease, confidence in vaccines, previous vaccination experience, and acceptance of and WTP for hexavalent vaccine. Multivariate logistic regression was used to determine factors influencing acceptance, and multivariate tobit regression was used to identify factors impacting WTP. Between April 28 and June 30, 2023, a total of 581 parents of children aged 0–6 years participated in the survey; 435 (74.87%, 95% CI:71.3%−78.4%) parents indicated acceptance of hexavalent vaccine. Residence location, parents’ education level, experience paying for vaccination, and disease knowledge scores were key factors affecting parents’ choices for vaccination. Mean (SD) and median (IQR) willingness to pay for full 4-dose course vaccination were 2266.66 (1177.1) CNY and 2400 (1600–2800) CNY. Children’s age (p < .001), parents’ education level (p = .024), and perceived price barriers (p < .001) were significantly associated with WTP. Parents have high acceptance and willingness to pay for hexavalent vaccine. The less money parents have to pay out of pocket, the more willing they can be to accept the vaccine. Therefore, acceptance may increase even further if the vaccine is covered by medical insurance, provided free of charge by the government, or if its price is reduced. Our results provide reference for optimizing and adjusting immunization strategies in China.

Pollutant removal in an experimental bioretention cell situated in a northern Chinese sponge City

Abstract To assess the viability and effectiveness of bioretention cell in enhancing rainwater resource utilization within sponge cities, this study employs field monitoring, laboratory testing, and statistical analysis to evaluate the water purification capabilities of bioretention cell. Findings indicate a marked purification impact on surface runoff, with removal efficiencies of 59.81% for Suspended Solids (SS), 39.01% for Chemical Oxygen Demand (COD), 37.53% for Ammonia Nitrogen (NH3-N), and 30.49% for Total Phosphorus (TP). The treated water largely complies with rainwater reuse guidelines and tertiary sewage discharge standards. Notably, while previous research in China has emphasized water volume control in sponge city infrastructures, less attention has been given to the qualitative aspects and field-based evaluations. This research not only fills that gap but also offers valuable insights and practical implications for bioretention cell integration into sponge city development. Moreover, the methodology and outcomes of this study serve as a benchmark for future sponge city project assessments, offering guidance to relevant authorities.

How Do Population Changes and Land Use Policies Affect the Relationship between the Urban Economy and Public Services?

In recent years, an increasing number of Chinese cities have experienced population decline, impacting the urban economy, public services, and paid use of state-owned land (PUL). This paper employs a coupled coordination degree model and the gray correlation coefficient method to examine the relationship between the rate of population change from 1990 to 2020, the rate of PUL change from 2000 to 2020, and the coupled coordination of economy and public services. The study arrives at several conclusions: (1) Cities with declining populations exhibit a lower PUL rate than those without population shrinkage, indicating reduced activity in the land market. (2) Population growth plays a significant role in the coordinated development of the urban economy and public services, fostering urbanization. (3) The economy and public services in shrinking cities rely heavily on revenue generated from the transfer of PUL rights to support their coordinated development. This research provides an insightful comparison between shrinking and non-shrinking cities by integrating the unique compensated land transfer system in China with the critical variable of population change.

Relationships between Resident Activities and Physical Space in Shrinking Cities in China—The Case of Chaoyang City

Shrinking cities suffer from a decreased level of resident activities. As a result, areas with low levels of resident activities may become breeding grounds for social issues. To ease and prevent social issues, it is important to deploy physical space optimisation strategies to effectively guide the distribution of resident activities in shrinking cities. To support the development of such spatial strategies, this paper introduces machine learning-based methods for analysing the nuanced non-linear relationship between resident activities and physical space in shrinking cities. Utilising dual-scale grids, this study calculates multi-source spatial elements, which are subsequently integrated with resident activity data to construct a gradient boosting decision tree model. It then analyses the weight of different spatial elements’ impacts on resident activities and their nonlinear relationships. The model proposed in this study demonstrates good precision in construing the relationship between resident activities and physical space. Based on the research findings, strategies for different types of spatial development in shrinking cities are drawn out. This paper advocates for the application of this analytical approach before conducting spatial planning in shrinking cities to maximise the effectiveness of spatial development in guiding resident activities.

Can an Energy Transition Strategy Induce Urban Green Innovation? Evidence from a Quasi-Natural Experiment in China

Green innovation is a new driving force to promote green and low-carbon development. Whether an energy transition strategy can induce green innovation is an important question that has not been clearly answered. With the help of panel data from 281 cities in China during 2007–2021, this study considers China’s new energy exemplary city policy as a quasi-natural experiment and conducts a difference-in-differences model to explore the effects and mechanisms of energy transition strategy on urban green innovation. The results show that a new energy exemplary city effectively induces urban green innovation, with mediating mechanisms of increasing government financial support, promoting human capital agglomeration, and improving energy efficiency. The moderating mechanisms test reveals that environmental regulation and intellectual property protection play a positive moderating role in the promotion of green innovation through the new energy exemplary city policy. Heterogeneity analysis suggests that the new energy exemplary city policy has a stronger effect on promoting green innovation in eastern regions and non-resource-based cities. Our findings not only enrich our understanding of the relationship between energy transition strategy and green innovation but also provide a reference for policymakers to promote energy transition and green innovation.

Urban Growth and Its Ecological Effects in China

As the largest developing nation, China is currently experiencing rapid urban growth. Conducting a thorough scientific assessment of this expansion and its ecological consequences is of paramount importance for advancing China’s ecological civilization and aligning with the United Nations’ Sustainable Development Goals. This study employs multi-source remote sensing data to investigate the spatiotemporal trends in Chinese urban development and explore its impact on the ecological environment. From 2013 to 2021, the findings indicate an increasing trend in China’s total nocturnal light, with the southern and central regions exhibiting higher growth rates. This suggests a decade-long expansion of Chinese cities, especially in the southern and central regions. However, the impact of urban expansion on ecological quality varies. Beijing, Shenyang, and Xi’an have witnessed improved environmental quality, while Kunming and Shenzhen have experienced minimal changes, and Hefei and Wuhan have encountered a decline. The observed spatial heterogeneity underscores the intricate relationship between urban expansion and ecological shifts. This study reveals the spatiotemporal dynamics of China’s urban expansion and its ecological impact, providing valuable insights and policy recommendations for fostering the harmonized development of urbanization and ecological preservation.

Optimizing Built Environment in Urban Negative Spaces Using Parametric Methods—Research on a High-Density City in China

In the early stage of architectural design, addressing the challenges posed by negative spaces in high-density urban environments is crucial for enhancing spatial efficiency and building sustainability. Multiple studies employed digital methods and tools to address these issues, such as parametric design, simulation, and genetic algorithms, to investigate architectural generation approaches for urban negative spaces. This article proposes an integrated design process that involves finding the location and form of negative spaces, generating solutions using slime mold and wasp algorithms, and optimizing and analyzing solutions using the Wallacei plugin in Grasshopper. This comprehensive approach underscores the potential of parametric design to yield a multitude of solutions while also acknowledging the convergence challenges encountered during simulations, particularly in optimizing for optimal sunlight exposure during the winter solstice and minimal solar radiation in the summer. Analyzing the optimization goals and parameter values of the 15th Pareto optimal solution in the 100th generation reveals: (1) a higher number of units leads to positive correlation growth in both objectives; (2) within a certain number of units, parametrically generated solutions facilitate the convergence of optimization goals, yielding optimal outcomes. Therefore, factors such as the range of unit quantities and proportions need consideration during early-stage parametric design and simulation. This study explores a design methodology for negative spaces in high-density urban cities, validating the feasibility of various mainstream generation methods and offering insights for future research.

Spatial Relationship of Inter-City Population Movement and Socio-Economic Determinants: A Case Study in China Using Multiscale Geographically Weighted Regression

In the current field of regional studies, there is a growing focus on regional spatial relationships from the perspective of functional linkages between cities. Inter-city population movement serves as an embodiment of the integrated functionality of cities within a region, and this is closely tied to the socio-economic development of urban areas. This study utilized Location-Based Services (LBSs) to collect the scale of inter-city population movement across 355 cities in China. Additionally, socio-economic data published by local governments were incorporated. By establishing a Multiscale Geographically Weighted Regression (MGWR) model, this research explores the spatial relationships between inter-city population movement and socio-economic influencing factors in China. This study aims to elucidate the spatial scales of the relationships between various variables. Our research findings indicate that the relationship between inter-city population movement and potential socio-economic determinants exhibits spatial non-stationarity. It is better to explore this spatial relationship through the MGWR model as there are different determinants operating on inter-city population movement at different spatial scales. The spatial distribution of the coefficient estimates shows significant regional differences and numerical variations. In China’s economically developed coastal regions, there is relatively balanced development among cities, with advanced manufacturing and producer service industries acting as significant drivers of mobility. In inland regions of China, city size is the most influential variable, directing a substantial flow of human and economic resources towards regional socio-economic hubs such as provincial capitals. The main contribution of this study is the re-examination of the relationship between inter-city population movement and socio-economic factors from the perspective of spatial scales. This approach will help China to consider the heterogeneity of different regions more extensively when formulating regional development policies, thereby facilitating the targeted promotion of regional element flow.

Littered cigarette butts in both coastal and inland cities of China: occurrence and environmental risk assessment

Cigarette butts (CBs) pollution is a critical global environmental issue, yet limited research exists on CBs pollution in both coastal and inland Chinese cities with varying development levels. This study investigated CBs occurrence, contamination, Cigarette Butts Pollution Index (CBPI), and heavy metal leakage in four cities. The results of CBs collected over multiple days revealed higher contamination levels in coastal city of Dalian (0.10 ± 0.03 CBs/m2), inland cities of Baoding (0.06 ± 0.02 CBs/m2) and Meizhou (0.07 ± 0.02 CBs/m2) compared to first-tier coastal city of Guangzhou (0.03 ± 0.02 CBs/m2). Patterns of CBs occurrence and CBPI varied across land usage and cities development level. SEM and EDS analysis identified microplastics and heavy metal particles released from CBs in water environments. ICP-MS detected a total of 629.7 μg/L of 14 heavy metals. Approximately 1.9 ± 0.9 g/km2 of heavy metals are leaked daily in Chinese cities due to CBs, posing a severe threat to soil and water safety given the indiscriminate disposal of CBs. This study offers scientific insights into CBs pollution and underscores the pressing need for effective measures to mitigate environmental hazards, particularly heavy metal and microplastics contamination released from CBs in China.

Detecting causal relationships between fine particles and ozone based on observations in four typical cities of China

As the concentration of fine particles (PM2.5) is declining, ozone (O3) concentration has been increasing in China in recent years. To collaboratively control PM2.5 and O3, it is critical to understand the relationship between the two and identify major controlling factors. We use a convergent cross-mapping method to detect the causal relationship between daily PM2.5 and maximum daily 8 h average (MDA8) O3 concentrations in Beijing, Taizhou, Shenzhen and Chengdu, China, in the four seasons in 2015–2021. In addition, we also examined causal effects of atmospheric oxidation capacity, precursors and meteorological elements on PM2.5 and MDA8 O3 in the four cities. PM2.5 and MDA8 O3 are strongly positively correlated and show bidirectional causal relationships during the Beijing and Taizhou summer and in the four seasons in Shenzhen, due mainly to the strong photochemical reactions in the daytime. During the Beijing winter, PM2.5 and MDA8 O3 show bidirectional causal relationships, but the two are significantly negatively correlated, driven by NO2 and relative humidity. Weak bidirectional, unidirectional and no causal effects between PM2.5 and MDA8 O3 are detected in other seasons in the four cities. In these seasons and cities, the top three causal factors of PM2.5 differ from those of MDA8 O3. Season-, city- and pollutant-specific control measures of PM2.5 and MDA8 O3 are required.

How do industrial land transfer modes impact carbon emissions? An intermediation perspective based on industrial structure.

Industrial land is currently the main carrier and important source of global carbon emissions, and as the world's largest developing country, China's large-scale and diversified industrial land supply has made it the world's largest carbon emitter. Therefore, researching the impact of different supply methods of industrial land on carbon emissions and its impact paths in China can help provide a reference for other countries to reduce carbon emissions from the perspective of urban industrial land management, which is of great significance for effectively promoting global carbon reduction. Based on this, this paper analyses the impact of different supply methods of industrial land on carbon emissions and its urban heterogeneity using the SYS-GMM and chain-mediated effects models for 285 cities in China from 2008 to 2020. The study found that, in general, the impact of different industrial land transfer modes on carbon emission has hysteresis and persistence. Agreement and listing transfer with government intervention can significantly exacerbate carbon emissions, while more market-based bidding and auction transfer can dampen carbon emissions. In terms of intermediary effects, the transfer of industrial land by agreement and listing will inhibit the rationalization and advancement of industrial structure, thus aggravating carbon emissions. The transfer of industrial land by bidding and auction will create barriers to entry and a crowding-out effect, promote the rationalization of industrial structure and the transformation and upgrading of industrial structure and moderate carbon emissions. In terms of city heterogeneity, there is urban heterogeneity in the impact of industrial land transfer on carbon emissions in cities with different economic types. Bidding and auction transfer for industrial land in both economically developed and less developed cities can promote carbon pollution. While the more developed urban economy makes the intermediary effect of industrial structure not significant. In the future, it is necessary to strictly control the scale of industrial land supply; the whole process supervision mechanism of industrial land allocation and differentiated industrial land supply strategies will provide useful experience for many developing countries in allocating industrial land to mitigate carbon emissions, generating effective contributions to global carbon emission reduction.

Digital inclusive finance, green technological innovation, and carbon emissions from a spatial perspective

Based on the panel data of 276 prefecture-level cities in China from 2011 to 2020, this study explores the impact of digital inclusive finance (DIF) on carbon emissions and the intrinsic mechanism of green technological innovation from a spatial perspective by constructing a spatial econometric model, a mediating effect model, and a threshold model. The results show that DIF significantly inhibits carbon emissions, exhibiting a spatial spillover effect. The transmission mechanism from a spatial perspective shows that green technological innovation plays a partial mediating role between DIF and carbon emissions, with the mediating effect accounting for approximately 59.47%. The heterogeneity analysis suggests that the impact of DIF on the reduction of carbon emissions is more pronounced in large and medium-sized cities and eastern regions. Further discussion reveals that the carbon reduction effect of DIF is also influenced by green technological innovation and industrial structure upgrading, showing threshold effects with marginal decreases and gradual increases, respectively.

Forecast urban ecosystem services to track climate change: Combining machine learning and emergy spatial analysis

It is important to simulate urban ecosystem services and provide guidance for their conservation and management under complex scenarios. We developed software for the rapid computation of ecosystem services based on emergy spatial analysis, machine learning, and the DLUCP model to predict the precipitation based on climate change and land use changes in five Chinese cities. The LSTM model is used to predict monthly precipitation for the cities based on historical data of 720 months. We also utilized the land use change prediction model based on the idea of distribution to improve the accuracy of future land use changes in China. The results show that based on the predicted values in 2025, an increase in ES is observed for Beijing, Wuhan, and Chongqing in 2020–2025 under both SSP1-RCP2.6 and SSP5-RCP8.5 scenarios, while the ES in Guangzhou and Shenzhen decreased. Furthermore, among the three types of ecosystems, the woodland ecosystem contributed the most to the total ES. The change in the woodland area had the greatest impact. Therefore, it is recommended that ecosystem conservation and restoration should focus on woodland ecosystem, and proactively address climate change to help achieve carbon peak and neutrality goals. The accuracy and applicability of the software are also tested.

Towards Carbon Neutrality in Agglomeration: Impact of Eco-Industry Development on Urban Carbon Emission Efficiency

Ecological industrial parks (EIPs) play a pivotal role as primary drivers of China’s industrial green transformation, facilitating the enhancement of urban carbon emission efficiency (UCEE) and the realization of green sustainable development. This study empirically investigates the effects of EIP policies on UCEE through quasi-natural experiments, utilizing data from 282 prefecture-level cities in China spanning from 2006 to 2021. Employing a multi-period difference-in-difference (DID) method, the findings are as follows: (1) The implementation of EIP policies leads to a 2.5% average increase in UCEE. (2) Event analysis reveals certain lagging characteristics in the promoting effect of EIP policies on the carbon emission efficiency of pilot cities. (3) EIP construction primarily enhances UCEE by reinforcing agglomeration effects and elevating innovation ability. (4) The promoting effect of EIP construction is more pronounced in the eastern and central regions, as well as in non-resource-based cities within different regions. Drawing from the empirical results, this study provides pertinent recommendations for EIP construction, offering theoretical guidance to policymakers and managers in crafting sustainable development strategies.

Language change and multilingualism in an ethnic city in China: a diachronic linguistic landscape perspective

ABSTRACT This study adopts an apparent-time diachronic linguistic landscape (LL) approach to investigate the vitality of an ethnic minority language in China, namely the Nuosu Yi (诺苏彝). Diachronic LL research is concerned with changes in language use on signage over time. It provides insights into phenomena such as language shift, which is challenging to be unveiled through synchronic research. This study collected a total of 1233 signboards, which were made from 2002 to 2021, and thirty follow-up interviews with store owners. By analysing the data statistically and qualitatively, this study demonstrates the changes in language use on private signs of Xichang (the capital city of Liangshan Yi Autonomous Prefecture). A significant finding was a trend for multilingualism, in which the status of Chinese has changed from a monolingual to multilingual dominance, and English has benefited the most from the trend. The use of Nuosu Yi has been high over the two decades, but some issues have arisen with its use on some of the recent-made signs. This study provides a new approach to apparent-time LL research and demonstrates its importance in understanding the dynamic nature of the vitality of ethnic minority languages.

Geographical indication, agricultural development and the alleviation of rural relative poverty

AbstractSustainable development is the power source to promote rural economic and social prosperity and the necessary guarantee for rural revitalization, while rural relative poverty alleviation is the inherent requirement for promoting sustainable development and realizing rural revitalization. The pro‐agricultural attribute of geographical indication determines that it can be an important tool to alleviate rural relative poverty. This study analyzes the relationship between geographical indication and rural relative poverty alleviation, as well as the mediating role of agricultural industry agglomeration and the moderating role of agricultural scale operation. We use global Moran's I and spatial Durbin models to achieve these objectives, using panel data from 218 cities in China spanning from 2008 to 2019. The results show that: (1) During the study period, relative poverty in China exhibits a distinct pattern of contiguous distribution, and there has been a significant reduction in the number of areas with high levels. Notable progress has been made in alleviating relative poverty in the central, northeastern, and southern regions of China. (2) Geographical indication can alleviate rural relative poverty not only within its region but also in neighboring regions. (3) Geographical indication can alleviate rural relative poverty through agricultural industry agglomeration, and agricultural scale operation can strengthen the relative poverty alleviation effect of geographical indication. This paper enriches the study of relative poverty alleviation mechanisms and reveals how geographical indications can help. The results can provide useful insights for poverty alleviation in poor areas through geographical indication and a new practice path for rural revitalization.

Strategic interactions for carbon emissions in Chinese cities are influenced by mayors

Strategic interactions for carbon emissions in Chinese cities are influenced by mayors

Trending time-varying coefficient spatial panel data models*†

This paper investigates the estimation and inference of spatial panel data models in which the regression coefficient vector is a trending function. We use time differences to eliminate the individual effects and employ various GMM estimations for regression coefficients with both linear and quadratic moments. Time trend estimator based on these GMM estimations is also proposed. Monte Carlo experiments show that the finite sample performance of the estimators is satisfactory. As an empirical illustration, we investigate the trending pattern of the spillover effect of air pollution among Chinese cities from 2015–2021.