Chinese Cities Research Articles

The role of geographic distances in green industrial pilot policies evaluation: A sustainability transition perspective.

Green industrial policies (GIPs) aim to promote the adoption ofgreen technology within a sustainability framework. While previous evaluations of GIP have focused more on the policy itself and the impacts within the policy boundaries, this paper further introduces the geographical factor to analyze the impact of different spatial geographic distances on implementing GIP. By integrating geographic distances into a spatial difference-in-differences analysis to assess the effects of municipal green industry policies (referred to as green industry pilot policies in this paper) enacted in 11 cities in China from 2006 to 2010, we find that these policies not only improve environmental and economic outcomes in targeted regions but also have spillover effects that may affect neighboring areas negatively, highlighting the importance of geographic considerations. The effectiveness of green industrial policies varies across cities, influenced by local socio-technical systems and regional characteristics such as infrastructure and information technology. These findings suggest that policy impacts are complex and multifaceted, requiring a comprehensive understanding of geographic interdependencies. By incorporating geographic factors, this research contributes to sustainability transition theory by offering insights into the spatial and temporal dynamics of socio-technical systems. The results underscore the need for policymakers to consider spatial-temporal aspects and potential secondary effects on adjacent regions when designing and implementing green industrial policies.

A machine learning algorithm to explore the drivers of carbon emissions in Chinese cities

As the world’s largest energy consumer and carbon emitter, the task of carbon emission reduction is imminent. In order to realize the dual-carbon goal at an early date, it is necessary to study the key factors affecting China’s carbon emissions and their non-linear relationships. This paper compares the performance of six machine learning algorithms to that of traditional econometric models in predicting carbon emissions in China from 2011 to 2020 using panel data from 254 cities in China. Specifically, it analyzes the comparative importance of domestic economic, external economic, and policy uncertainty factors as well as the nonparametric relationship between these factors and carbon emissions based on the Extra-trees model. Results show that energy consumption (ENC) remains the root cause of increased carbon emissions among domestic economic factors, although government intervention (GOV) and digital finance (DIG) can significantly reduce it. Next, among the external economic and policy uncertainty factors, foreign direct investment (FDI) and economic policy uncertainty (EPU) are important factors influencing carbon emissions, and the partial dependence plots (PDPs) confirm the pollution haven hypothesis and also reveal the role of EPU in reducing carbon emissions. The heterogeneity of factors affecting carbon emissions is also analyzed under different city sizes, and it is found that ENC is a common driving factor in cities of different sizes, but there are some differences. Finally, appropriate policy recommendations are proposed by us to help China move rapidly towards a green and sustainable development path.

Resources coupled with executive authority: Implications of relocating government administrative headquarters for local economic development

Despite more than three decades of market-oriented reforms, the Chinese government’s administrative capacity remains potent, exerting a substantial influence on economic development. This study delved into the economic ramifications of relocating government administrative headquarters to recipient counties, employing data from Chinese prefecture-level cities spanning from 2005 to 2019. We utilized event study analysis and the difference-in-difference method to conduct our analysis. Our results unveiled a significantly positive impact of administrative headquarters relocation on economic growth in the recipient counties. This was substantiated by an average increase of 2.236 in the nighttime light index, constituting 8.5 % of the sample mean for these counties. Notably, we found that the departure of administrative headquarters had no significant effect on the economic growth of the original counties. Therefore, the overall effect of administrative headquarters relocation was positive.

The impact of green low-carbon development on public health: a quasi-natural experimental study of low-carbon pilot cities in China

BackgroundIn recent years, climate change and environmental pollution have posed significant threats to public health. As environmental policies such as low-carbon city initiatives are progressively implemented, their role in enhancing public health has become a topic of growing interest. This study aimed to investigate the relationship between green low-carbon development and public health and to analyze the underlying mechanisms.MethodsWe utilized data from 271 prefecture-level cities in China spanning from 2007 to 2020, focusing on green low-carbon development, climate change, environmental pollution, and public health. Employing the quasi-natural experimental framework of China’s low-carbon city pilot projects, we constructed a multi-site difference-in-differences (DID) model for empirical analysis. Various robustness checks, including parallel trend tests, placebo tests, sample selection bias checks, and adjustments to the temporal and spatial scope of the samples, were conducted to ensure the reliability of the results. Additionally, we explored the positive effects of green low-carbon development on public health through dual mediation pathways involving climate change mitigation and pollution reduction. Finally, we examined the heterogeneity of the results across different city tiers, economic growth rates, levels of technological investment, and green finance development.ResultsThe findings indicate that green low-carbon development significantly enhances public health, a conclusion supported by robustness tests. Mechanism analysis reveals that the benefits of green low-carbon development on public health are realized through mitigating climate change and reducing environmental pollution. Further analysis reveals that the positive impact on public health is more pronounced in first-and second-tier cities, as well as in cities with faster economic growth, greater technological investment, and more developed green finance sectors.DiscussionThis study highlights the crucial role of urban green low-carbon development in improving environmental quality and public health. In addition to providing empirical evidence that supports the promotion of green low-carbon development in cities, the results point to policy recommendations for enhancing public health. Moreover, the findings contribute to the development of environmental policies and the implementation of the “Healthy China” strategy.

The Impact of Smart City Policies on City Resilience: An Evaluation of 282 Chinese Cities

This study uses four dimensions, namely social resilience, economic resilience, infrastructure resilience, and ecological resilience, to construct an index system for urban resilience. The subject data came from the panel data of 282 prefecture-level cities in China from 2006 to 2020. We selected a multiperiod double-difference model to study the effects of smart city pilot policies on macro-urban resilience. By conducting parallel-trend tests and selecting appropriate robustness tests, this study drew the following relevant conclusion: smart city pilot policies can have a positive effect on the urban resilience level. These policies exert their influence by facilitating industrial structure upgrading, which plays a partial mediating role. Considering different city area distributions and city scales, smart city pilot policies can have significant heterogeneity in their enhancement of urban resilience. The effect is pronounced in the “east > central > west” states and is more likely to have a significant impact on small- and medium-sized cities. Therefore, promoting the scope of smart city pilots, strengthening the intermediary role of industrial structure upgrading, and implementing differentiated policies for different regions and city sizes are important for sustainable urban development.

Clustering of Basic Educational Resources and Urban Resilience Development in the Central Region of China—An Empirical Study Based on POI Data

This paper presents an urban resilience evaluation index system and evaluation on the clustering of educational resources based on the data of 80 prefecture-level cities in China’s central region in 2012, 2016, and 2020. The results reveal a rising trend of urban resilience in the central region of China, with the provincial capital cities exhibiting the highest levels of resilience. Educational resources are clustered in urban areas of provincial capital cities and other prefectural-level cities. Furthermore, clustering of educational resources has a significant impact on urban resilience. Policy factors play a significant role in moderating the relationship between educational resource clustering and urban resilience in large cities; however, this moderating role is not significant in small cities. These findings have significant implications for the optimal allocation of educational resources, promotion of urban resilience, and advancement of social equity.

Impact of dual pilot policies for low-carbon and innovative cities on the high-quality development of urban economies

<p style="margin-top:16px; text-align:justify"><span lang="EN-US" style="font-size:12.0pt"><span style="font-family:"Times New Roman",serif">Based on the panel data of 276 cities in China from 2005 to 2021, the article used a multi-period double-difference model to explore the impact of the dual-pilot policy of low-carbon cities and innovative cities on the high-quality development of urban economy. The study found that (1) the implementation of the dual-pilot policy significantly had significantly promoted the economic high-quality development of the pilot cities, and the dual-pilot policy had a more significant effect on the enhancement of urban economic high-quality development compared with the single-pilot. (2) The mechanism analysis showed that green technology innovation, industrial structure adjustment and entrepreneurial activity played a mediator role in the impact of the dual-pilot on the high-quality development of the urban economy. (3) The spatial effect showed that the dual-pilot policy not only promoted the high-quality economic development of the region, but also had a positive spillover effect on the high-quality economic development of the neighbouring regions. (4) The heterogeneity analysis showed that the dual-pilot policy promoted the high-quality economic development of the eastern cities, large-scale cities, and non-resource-based cities more strongly.This study enriches the research on the impact of policy synergy on high-quality economic development, and provides references and insights for the effective implementation of dual-pilot policies and the promotion of high-quality urban economic development.</span></span></p>

Can the digital economy contribute to rural revitalization? A case of from China?

This study establishes a multi-dimensional evaluation index system for measuring digital economy and rural revitalization. It explores the impact of digital economy on China's rural revitalization and its mechanism using dynamic balanced panel data of 30 provinces and cities in China from 2012 to 2020 and adopting two-way fixed effect and mediated effect models. The results reveal that digital economy promotes rural revitalization in China; however, differences exist in its impact on industrial prosperity, ecological livability, civilized rural customs, effective governance, and affluent living under rural revitalization. Heterogeneity analysis shows that the impact of digital economy on rural revitalization is more pronounced in eastern China, with high levels of new urbanization and areas for big-data experimentation. In addition, this thesis verifies that technological innovation and human capital are two important transmission paths through which digital economy affects rural revitalization in China. The conclusions provide theoretical guidance and practical support for China and other developing countries to vigorously develop their digital economies and comprehensively revitalize the countryside.

Analysis of the spatiotemporal coupling coordination relationship between industrial development and water resource security in China

ABSTRACT Industrial development is an important part of economic and social development, and a stable pattern of water resource security can meet the needs of economic and social development. Therefore, correctly handling the relationship between industrial development and water resource security in China is the key to achieving high-quality development. This paper takes 287 prefecture-level cities in China from 2010 to 2019 as the research object, establishes the evaluation index system of industrial development and water resource security, calculates the comprehensive index of industrial development and water resource security by the entropy weight method, and analyzes the spatiotemporal evolution trend of the two by using the coupling coordination degree model. The results show that the degree of coupling coordination between industrial development and water resource security in China shows an overall upward trend from 2010 to 2019. Optimizing the industrial structure and promoting industrial transformation and upgrading can effectively improve the coupling coordination level between industrial development and water resource security, and the degree of industrial development threatening water resource security is stronger than the degree of water resource security restricting industrial development. The research conclusion has important practical significance for optimizing industrial structure and implementing regional differentiation policy.

Does the Digital Economy Promote Tourism Eco-Efficiency? – An Empirical Study Based on Chinese Cities

Does the Digital Economy Promote Tourism Eco-Efficiency? – An Empirical Study Based on Chinese Cities

Urban Rail Transit, Industrial Structure Advancement, and Green Economic Growth – Evidence from Chinese Metro-Opening Cities

Urban Rail Transit, Industrial Structure Advancement, and Green Economic Growth – Evidence from Chinese Metro-Opening Cities

How can local government capacity lift the ‘resource curse’? A study from the perspective of industrial structure transformation

Industrial transformation is crucial for sustainable urban development and economic security. Although more studies have analyzed the relationship between resource endowment and urban industrial transformation, they have failed to include the key factor of local government capacity in the analysis. Based on the panel data from 267 cities in China from 2003 to 2018, the study examines the impact of resource endowment on industrial transformation and the role of local government capacity in it by using linear models and panel threshold models. This study finds that resource endowment promotes the development of the secondary industry in urban, but hinders the development of the tertiary industry. There is a moderating effect of local government capacity that mitigates the lock-in effect of resource endowment on industrial transformation. This moderating effect demonstrates heterogeneity among cities with different levels of resource endowment and geographic locations, and the results are robust. Furthermore, this study concludes that under different local government capacity, the moderating effect of local government capacity on the relationship between resource endowment and industrial transformation is nonlinear, and it also finds that the stronger local government capacity is not the better.

A Study of the Evolution of Haze Microblog Concerns Based on a Co-Word Network Analysis

Haze is a phenomenon caused by excessive PM2.5 (air-borne particulate matter having a diameter of fewer than 2.5 μm) and other pollutants and results from the interaction between specific climatic conditions and human activities. It significantly impacts human health, transportation, and the natural environment and has aroused widespread concern. However, the influence of haze on human mental health, being hidden and indirect, is often overlooked. When haze pollution occurs, people express their feelings and concerns about haze events on media such as Weibo. At present, few studies focus on haze public opinion, as well as the changing trends in people’s discussion of haze since its emergence, which is of great significance for haze response and resource management. Based on the perspective of topic analysis, this study explores the psychological impact of haze on people by exploring the feelings of netizens in haze public opinion and investigates the evolution of people’s concerns based on long-term public opinion data. In this study, seven typical provinces and cities in China with severe haze pollution were selected as the research area. Based on data on the “haze” theme from Weibo from 2013 to 2019, first, the microblog posts were preprocessed, and the keyword co-word network was constructed. Second, the Louvain algorithm was used to detect the topic community. Based on this, the cosine similarity was calculated to realize the temporal evolution analysis of topics. The results show that with the development and change in haze pollution, the content and intensity of the topics netizens pay attention to have changed, including five types: merger, split, survival, transformation, and rebirth/extinction. People’s attention to haze shows obvious spatial differences, and it is related to the degree of haze pollution, which is bipolar. Areas with severe haze tend to pay more attention to haze itself and its influence, while areas with light haze pay more attention to haze control. The research results can provide valuable insights for governments and relevant departments in guiding public opinion and resource allocation.

From policy to practice: Enhancing enterprise productivity through energy transition initiatives

This study investigates the impact of energy transition policies on enterprise Total Factor Productivity (TFP) in China, utilizing a quasi-natural experiment with New Energy Demonstration Cities (NEDC) and panel data from Chinese cities and manufacturing enterprises (2011–2021). Using the difference-in-difference method, the analysis reveals that energy transition policies positively affect enterprise TFP, especially in non-resource-based cities, less polluting industries, and enterprises with strong Environmental, Social, and Governance (ESG) performance. The research identifies two key mechanisms driving productivity gains: green innovation and reduced financing costs. Additionally, it examines the role of Environmental Regulation (ER), finding that formal ER can mitigate the positive impact of energy transition policies on enterprise TFP, while informal ER has a reinforcing effect. This study contributes to the broader understanding of the policy implications of energy transitions, highlighting the nuanced effects of different regulatory environments on enterprise development and providing evidence on sustainable growth in the context of climate imperatives. The findings offer insights into the complex dynamics between energy policy and industrial productivity, relevant to policymakers, industries, and stakeholders interested in the interplay between energy transition and economic sustainability.

Spatial-temporal dynamics and influencing factors of city level carbon emission of mainland China

Urban areas are major sources of carbon emissions, making it crucial to understand their emission characteristics for effective carbon reduction and sustainable development. Using carbon emission data from mainland China (2001–2021), we analyzed the spatio-temporal dynamics and future trends of city-level emissions and explored influencing factors using machine learning methods. Results indicate significant fluctuations in carbon emissions, with over 40 % of mainland Chinese cities experiencing a doubling in total emissions. Geospatially, cities in South Coast (SC), East Coast (EC), Northeast (NE), and NorthCoast (NC) show stronger intensity and increasing trends in carbon emissions compared to other regions, with over 80 % of cities in these regions experiencing high or higher increases. Additionally, a continued rise in carbon emissions was detected in most Chinese cities, with an average Hurst index of 0.64, indicating persistent trends. Using the XGBoost method, factors such as population density, built-up area, urban green coverage rate, and GDP were found to strongly correlate with urban carbon emissions, exhibiting significant spatial heterogeneity. This research uncovers the characteristics and influencing factors of urban-scale carbon emissions, offering valuable insights for policymakers to tailor carbon reduction strategies to the specific needs and conditions of various urban areas.

Screening potential biomarkers for acute respiratory infectious diseases from antipyretics, antiviral, and antibiotics in wastewater

Since the onset of COVID-19, respiratory diseases have emerged as a focal concern within the field of public health. This study aims to reveal the prevalence of acute respiratory infectious diseases by screening antipyretic, antiviral, and antibiotic biomarkers through wastewater analysis. Samples were collected over a seven-day period each year in 2022, 2023, and 2024 from a northern city in China, assessing the concentrations of two antipyretics (paracetamol and ibuprofen), one antiviral drug (oseltamivir), eleven antibiotics, and three pathogens (influenza A, influenza B, and Mycoplasma pneumoniae). The usage of most antipyretics and antibiotics was higher in 2023 and 2024, primarily due to the outbreak of COVID-19 in 2023 and the prevalence of influenza A, influenza B, and Mycoplasma pneumoniae in 2024. The prevalence assessed using antipyretics (2.68 %) and pathogens (2.70 %) demonstrated a high degree of consistency, whereas the prevalence estimated using antibiotics and antiviral drugs was only 0.53 % and 0.36 %, respectively. Antibiotics are generally used to treat a broad spectrum of bacterial infections rather than targeting a specific pathogen, so their presence in wastewater may not directly reflect the prevalence of a particular disease. In contrast, antipyretics and specific pathogens exhibit a stronger correlation, suggesting that they may serve as more reliable biomarkers than antiviral and antibiotic drugs. The research findings offer alternative biomarkers, such as antipyretics, aside from pathogens, for the assessment of acute respiratory infectious diseases.

Multistage data center cooling system for temperature gradation and matching

A prototype of a multistage cooling system with a cooling capacity of 20 kW is assembled and studied. The traditional single-stage system is split into two sub-systems according to the temperature level, which reduces the temperature difference and irreversible heat transfer loss, and further improves the system's energy efficiency. The system mainly features three modes including free-air cooling, refrigeration-based cooling and waste heat recovery, which can achieve efficient cooling while capable of recovering the waste heat to the surrounding heat users. The efficiency of the proposed cooling and heat recovery system was assessed by measuring its energy reuse effectiveness (ERE). The energy savings and environmental benefits of the system were analyzed across five cities in China, each representing different climates. Results indicate that the system achieved an ERE of 0.91 in Beijing, 38.9 % lower than the national average of the city. Additionally, an economic analysis showed a payback period of less than two years for the proposed system across all climates considered, which is 30 % shorter than that of a single-stage cooling system.

Rethinking the Effects of Smart City Implementation on Industrial Structure Change

Understanding the relationship between smart city implementation (SCI) and industrial structure change is necessary for improving SCI and achieving high-quality development of the urban economy. This study aims to comprehensively investigate how the two core SCI investments—information and communication technology (ICT) infrastructure and human capital—influence industrial structure. To this end, both SCI investments are measured using composite indexes calculated by the vertical and horizontal scatter degree method, and spatial panel models are applied using data from 156 smart cities in China from 2013 to 2019, classified according to their economic development level and population density. The results show that industrial structure upgrading produces positive spatial spillover effects and that the impacts of SCI investments on industrial structure change vary in different city classifications. Overall, ICT infrastructure promotes the upgrading of industrial structure, while human capital hinders industrial development due to human capital mismatch. Mechanism analysis shows that SCI investments can influence industrial structure through technological innovation and consumption upgrading. Moreover, policy implications are proposed to promote industrial structure upgrading for effective future SCI.

Ambient Air Pollution and Hospitalizations for Schizophrenia in China

Schizophrenia episodes may be triggered by short-term environmental stimuli. Short-term increases in ambient air pollution levels may elevate the risk of schizophrenia episodes, yet few epidemiologic studies have examined this association. To investigate whether short-term increases in air pollution levels are associated with an additional risk of schizophrenia episodes, independent of absolute air pollution concentrations, and whether sustained increases in air pollution levels for several days are associated with more pronounced risks of schizophrenia episodes. This nationwide, population-based, time-stratified case-crossover study was performed based on hospitalization records for schizophrenia across 295 administrative divisions of prefecture-level or above cities in China. Records were extracted from 2 major health insurance systems from January 1, 2013, to December 31, 2017. Thirty-six cities with a small number of schizophrenia hospitalizations (n < 50) were excluded. Data analysis for this study was performed from January to March 2024. Daily absolute concentrations of fine particulate matter (PM2.5), inhalable particulate matter (PM10), nitrogen dioxide, sulfur dioxide, ozone, and carbon monoxide were collected. Air pollution increases between neighboring days (APINs) were generated as the differences in absolute air pollution concentrations on the current day minus that on the previous day. Sustained increases (APIN ≥5 μg/m3 for PM2.5 and PM10, APIN ≥1 μg/m3 for nitrogen dioxide and sulfur dioxide, and APIN ≥0.05 mg/m3 for carbon monoxide) lasting for 1 or more to 4 or more days were defined for different air pollutants. Patients with schizophrenia episodes were identified by principal discharge diagnoses of schizophrenia. A conditional logistic regression model was used to capture the associations of absolute concentrations, APINs, and sustained increase events for different air pollutants with risks of schizophrenia hospitalizations. The study included 817 296 hospitalization records for schizophrenia across 259 Chinese cities (30.6% aged 0-39 years, 56.4% aged 40-64 years, and 13.0% aged ≥65 years; 55.04% male). After adjusting for the absolute concentrations of respective air pollutants, per-IQR increases in 6-day moving average (lag0-5) APINs of PM2.5, PM10, nitrogen dioxide, sulfur dioxide, and carbon monoxide were associated with increases of 2.37% (95% CI, 0.88%-3.88%), 2.95% (95% CI, 1.46%-4.47%), 4.61% (95% CI, 2.93%-6.32%), 2.16% (95% CI, 0.59%-3.76%), and 2.02% (95% CI, 0.39%-3.68%) in schizophrenia hospitalizations, respectively. Greater risks of schizophrenia hospitalizations were associated with sustained increases in air pollutants lasting for longer durations up to 4 or more days. This case-crossover study of the association between ambient air pollution increases and schizophrenia hospitalizations provides novel evidence that short-term increases in ambient air pollution levels were positively associated with an elevated risk of schizophrenia episodes. Future schizophrenia prevention practices should pay additional attention to APINs, especially sustained increases in air pollution levels for longer durations, besides the absolute air pollution concentrations.

The effects of perceived corporate social responsibility and Confucian ethics on psychological meaningfulness and employee engagement: A moderated‐mediation study

AbstractThis study aimed to explore whether perceived corporate social responsibility (PCSR) and Confucian values impact employee engagement. Specifically, we investigated the relationships among PCSR, psychological meaningfulness, and employee engagement, as well as the moderating effects of Confucian Ren‐Yi ethics on these relationships by using the social identity theory, Job Demands‐Resources (JD‐R) model and the stimulus‐organism‐response(S‐O‐R) model. A valid survey was conducted among 664 full‐time employees of 228 companies in 72 different cities in China from all walks of life. The findings reveal that PCSR was positively associated with psychological meaningfulness and employee engagement. Confucian Ren‐Yi ethics was positively associated with employee engagement, and psychological meaningfulness mediated the effect of PCSR on employee engagement. Moreover, we found that the positive relationship between PCSR and employee engagement through psychological meaningfulness was stronger for high‐level Confucian Ren‐Yi ethics than for low‐level Confucian Ren‐Yi ethics (i.e., moderated mediation). By verifying the impact of Confucian Ren‐Yi ethics and PCSR on employees' work attitudes, this study makes up for the deficiency of existing literature on CSR and Confucian values and enriches the micro research on CSR. Based on our findings, companies should consider improving employee engagement by implementing social responsibility and aligning their policies with Confucian Ren‐Yi ethics.