Chinese Cities Research Articles

Hindrance or facilitator? The economic consequences of national demonstration eco-industrial parks in China.

Many countries attach great importance to the green, low-carbon, and circular development of industrial parks. China is one of them and has entered an exploration journey of national demonstration eco-industrial parks (NDEIPs). However, the impact of the transformation of industrial parks into NDEIPs on local economic development still remains a mystery. To address this issue, we develop an empirical study using a combination of the multi-period difference-in-differences method and the propensity score matching method based on the panel data for 266 cities in China from 2001 to 2021. The results show that industrial parks becoming NDEIPs promotes cities' economic development. This conclusion still holds after a series of robustness tests, such as the reverse causality test and the placebo test. Moreover, the park heterogeneity tests show that the economic consequences vary according to differences in levels, industry types, life cycle phases, and the degree of foreign firm agglomeration. The city heterogeneity tests show that the economic consequences differ based on administrative levels, innovation capabilities, technology industrialization, and environmental friendliness. The spatial heterogeneity tests show that the economic consequences differ according to geographical location and whether situated in the Yangtze River Economic Belt. The policy upgrading heterogeneity tests show that the economic consequences differ during the process of policy upgrading and transformation. In addition, the mechanism tests reveal that green innovation, human capital level, and firm attractiveness mediate the relationship between industrial parks becoming NDEIPs and cities' economic development. This study provides a new perspective for understanding the economic effects of the transformation of industrial parks into NDEIPs, and provides a reference for the government on how to maximize these economic effects.

Digital memory construction in Lijiang

Purpose The ancient town of Lijiang is a representative place of ethnic minorities in China’s southwest border area jointly built by many ethnic groups. Its rich and diversified history, culture and architecture as well as its artistic and spiritual values need to be better retained and explored.Design/methodology/approach The protection and inheritance of Lijiang’s cultural heritage will be improved through the construction of digital memory resources. To guide Lijiang’s digital memory construction, this study explores strategies of digital memory construction by analyzing four case studies of well-known memory projects from China and America.Findings From the case studies analysis, factors of digital memory construction were identified and compared. Factors led to the discussion of strategies for constructing the digital memory of Lijiang within its design, construction and service phases.Originality/value The ancient town of Lijiang is a famous historical and cultural city in China, and it is also a representative place of ethnic minorities in the border area jointly built by many ethnic groups. The rich culture should be preserved and digitalized to offer better use for the whole nation.

Impacts of Low-Carbon City Pilot Policy on Urban Land Green Use Efficiency: Evidence from 283 Cities in China

Impacts of Low-Carbon City Pilot Policy on Urban Land Green Use Efficiency: Evidence from 283 Cities in China

Pathways to mitigate household carbon emissions in Chinese cities: Intentions, actions, and environments

Cities represent primary origins of carbon emissions and key spaces to cope with climate change. Low-carbon city pilots (LCP) have carried out three groups to mitigate household carbon emissions in China. There are many difficulties in identifying possible sources and factors of household carbon emissions. This study attempted to construct the analytical framework to examine potential mitigation pathways, which would influence household carbon emissions. Collecting data from urban energy consumption, the difference-in-differences model, a widely utilized quantitative method, is employed to assess the policy effect of LCP on mitigating household carbon emissions in China. Results indicated that: (1) LCP could mitigate household carbon emissions (−7.6%) and per capita household carbon emissions (−8.8%), which passed serious robustness tests. (2) Potential mechanisms, through which LCP mitigate household carbon emissions, were recognized, in terms of subjective intentions, objective actions, and external environments. (3) Policy effects in eastern and central cities were significantly negative.The improvement of energy consumption for winter heating in northern cities could mitigate more household carbon emissions.

Performance Evaluation of Carbon-Neutral Cities Based on Fuzzy AHP and HFS-VIKOR

Climate change threatens human survival and development. Cities, as the main gathering places for human production and life, serve as the focal points for the implementation of the policies related to energy efficiency, energy transition, and environmental protection. This study constructs an index system for the evaluation of carbon-neutral cities from the perspectives of carbon sources and carbon sinks. The system includes thirteen indicators under six dimensions. It combines objective and subjective data (i.e., statistical data and expert evaluations) by integrating two approaches: the fuzzy analytic hierarchy process (fuzzy AHP) and vise kriterijumska optimizacija i kompromisno resenje with hesitant fuzzy sets (HFS-VIKOR). We verify the efficacy of the proposed approach through a case study of thirteen low-carbon pilot cities in China. The results indicate that among these cities, Shenzhen performs the best, followed by Guangzhou and Hangzhou, while Kunming, Baoding, and Tianjin show poor performance in terms of carbon neutrality. Kunming and Baoding exhibit shortcomings mainly in carbon sources, while Tianjin faces deficiencies in both carbon sources and carbon sinks. Sensitivity analysis and comparative analysis show the availability and effectiveness of the proposed method. The proposed radar chart further highlights the improvement directions for each city to achieve carbon neutrality.

Trending Time-Varying Coefficient Spatial Panel Data Models

This article 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 to 2021.

Recycled Excavation Soils as Sustainable Supplementary Cementitious Materials: Kaolinite Content and Performance Implications

In response to the environmental implications of the massive quantities of excavation soil generated by global urbanization and infrastructure development, recent research efforts have explored the repurposing of calcined excavation soils as sustainable supplementary cementitious materials (SCMs). As it is still at an early stage, current research lacks systematic analysis across diverse soil deposits regarding their reactivity and mechanical properties within cementitious binders, despite recognized geographical variability in kaolinite content. Through comprehensive experimentation with soils sourced from four major southern Chinese cities, this study presents a pioneering assessment of the compressive strength, pozzolanic reactivity (X-ray diffraction, Fourier-transform infrared spectroscopy, solid-state nuclear magnetic resonance), and microstructural development (mercury intrusion porosimetry, scanning electron microscopy) of mortars modified by various calcined excavation soils (up to 28 days curing). The experimental data suggest that soils with a kaolinite content above 53.39% produce mortars of equal or superior quality to plain cement mixes, primarily due to their refined pore structures, microstructural densification, and enhanced hydration reactions. The findings highlight kaolinite—specifically, aluminum content—as the principal indicator of excavation soil viability for SCM application, suggesting a promising avenue for sustainable construction practices.

Assessing Traffic Noise and Its Impact on High-Rise Apartment Buildings Adjacent to an Urban Expressway: A Case Study in Chengdu, China

With rapid urbanization, traffic growth has accelerated in some cities in China. Due to strict urban construction land utilization policies, many high-rise apartment buildings have been constructed adjacent to expressways. To better understand the impact of urban traffic noise on the residents of high residential buildings adjacent to expressways and the differences in noise impacts on different floors, on-site noise monitoring and questionnaires for building residents have been conducted. The characteristics of traffic noise were analyzed based on the measured data, and factors, including time periods and building floors, were considered. According to the results of the questionnaire survey, 56.06% of the male respondents and 54.55% of the female respondents think that the impact of traffic noise on high-rise buildings is “high” or “very high”; 50.53% of the respondents who were in “good” or “very good” condition thought that the traffic noise has a “significant impact” or “very significant impact” on their sleep and daily life. In addition, 25% of respondents living on floors 4–10 and 62.5% of respondents living on floors 11–20 considered the traffic noise to have a “significant impact” or “very significant impact” on their sleep and daily life. The on-site noise monitoring results show that the noise levels (LAeq) outside the windows of the studied buildings remain significantly elevated, with daytime noise on working days ranging from 56 to 70 dB(A), and on weekends ranging from 50 to 65 dB(A). During the four time periods on weekdays from 7 a.m. to 9 a.m., 11 a.m. to 1 p.m., 5 p.m. to 7 p.m., and 10 p.m. to 12 a.m., the average LAeq levels on floors 11–20 are higher than those on floors 4–10 by 4.04 dB(A), 4.92 dB(A), 4.06 dB(A), and 2.67 dB(A), respectively. Similarly, during these time periods on weekends, the levels on floors 11–20 are higher than those on floors 4–10 by 4.96 dB(A), 6.32 dB(A), 5.28 dB(A), and 5.24 dB(A), respectively. This indicates that floors 4–10 of the building experience relatively lower noise levels, while floors 11–20 are subjected to comparatively higher levels of noise disturbance.

Pre-treatment assessment of chemotherapy for cancer patients: a multi-site evidence implementation project of 74 hospitals in China

BackgroundChemotherapy, whilst treating tumours, can also lead to numerous adverse reactions such as nausea and vomiting, fatigue and kidney toxicity, threatening the physical and mental health of patients. Simultaneously, misuse of chemotherapeutic drugs can seriously endanger patients' lives. Therefore, to maintain the safety of chemotherapy for cancer patients and to reduce the incidence of adverse reactions to chemotherapy, many guidelines state that a comprehensive assessment of the cancer patient should be conducted and documented before chemotherapy. This recommended procedure, however, has yet to be extensively embraced in Chinese hospitals. As such, this study aimed to standardise the content of pre-chemotherapy assessment for cancer patients in hospitals and to improve nurses' adherence to pre-chemotherapy assessment of cancer patients by conducting a national multi-site evidence implementation in China, hence protecting the safety of cancer patients undergoing chemotherapy and reducing the incidence of adverse reactions to chemotherapy in patients.MethodsThe national multi-site evidence implementation project was launched by a JBI Centre of Excellence in China and conducted using the JBI approach to evidence implementation. A pre- and post-audit approach was used to evaluate the effectiveness of the project. This project had seven phases: training, planning, baseline audit, evidence implementation, two rounds of follow-up audits (3 and 9 months after evidence implementation, respectively) and sustainability assessment. A live online broadcast allowed all participating hospitals to come together to provide a summary and feedback on the implementation of the project.ResultsSeventy-four hospitals from 32 cities in China participated in the project, four withdrew during the project's implementation, and 70 hospitals completed the project. The pre-and post-audit showed a significant improvement in the compliance rate of nurses performing pre-chemotherapy assessments for cancer patients. Patient satisfaction and chemotherapy safety were also improved through the project's implementation, and the participating nurses' enthusiasm and belief in implementing evidence into practice was increased.ConclusionThe study demonstrated the feasibility of academic centres working with hospitals to promote the dissemination of evidence in clinical practice to accelerate knowledge translation. Further research is needed on the effectiveness of cross-regional and cross-organisational collaborations to facilitate evidence dissemination.

Mapping urban green space of the 36 major cities in China using ZY-3 satellite images based on a feature robust to low-brightness pixels

Abstract. Urban green spaces (UGS), integral to modern urban life, play a pivotal role in shaping ecological, low-carbon, resilient, and livable cities. Understanding the microstructure and macro patterns of UGS is necessary but limited. In this context, we investigated the spatial patterns in the 36 major cities in China using Ziyuan-3 remote sensing images. We used a method for extracting UGS suitable for complex urban environments, and then selected 5 landscape pattern indices such as percent of landscape and patch density to analyse the spatial pattern of UGS in the 36 cities. The results show that: (1) The overall accuracy, recall, F1 value, and intersection over union of the extraction results of UGS were 94.62%, 94.11%, 94.36%, and 89.33% respectively; (2) Overall, the green space rate of the 36 cities exhibited a spatial distribution pattern of “high in the east and low in the west, low in the north and high in the south”; (3) Variations among cities were weak in terms of patch shape, but significant in patch density. The findings of this study cater to the escalating demands of urban planning and management.

The effects of low-carbon city pilot policy on urban land green use efficiency: evidence from 284 cities in China

The effects of low-carbon city pilot policy on urban land green use efficiency: evidence from 284 cities in China

Impact of Low-Carbon City Pilot Policies on Regional Green Total Factor Productivity: A Study

Based on data from 246 prefecture-level cities in China spanning the years 2006 to 2019, this paper employs a multi-temporal double-difference model to empirically examine the effects of low-carbon pilot policies implemented since 2010 on green total factor productivity. Furthermore, the paper conducts a mechanism analysis and heterogeneity analysis to explore the policys impact mechanisms and effects on different regions. The study reveals that low-carbon pilot policies have enhanced Chinas green total factor productivity. Results from the mechanism analysis indicate that these policies increase green total factor productivity by promoting the agglomeration of productive service industries and the innovation of green technologies, with the mechanism test for manufacturing industry agglomeration showing non-significant effects. Heterogeneity analysis results suggest that the impact of low-carbon pilot policies on the improvement of green total factor productivity is significant in Chinas eastern and western regions as well as in non-resource-based cities.

How does digital technology administrative penalty affect big data technology innovation: evidence from China

Administrative regulation is an essential institutional arrangement for governing innovation in big data technology. Administrative penalties are one of its main methods. It is worth investigating whether administrative penalties can serve as an institutional safeguard to promote technological innovation. This study collects data on digital technology administrative penalty (DTAP) and big data technology innovation (BDTI) from 2008 to 2020 in 281 cities in China and empirically evaluates the impact and mechanism of DTAP on BDTI. The findings suggest that the normative impact of the DTAP system can foster a conducive business ecosystem for big data innovation. The incentive mechanism motivates firms to increase their long-term investment in technological innovation, while the deterrence mechanism ensures the existence of a regulated competitive market. These mechanisms play a crucial role in facilitating BDTI. Mechanism tests show that the DTAP has the potential to promote novel business models in the digital economy and accelerate progress in industrial digitalisation, which in turn promotes innovation in big data technologies. The impact of the DTAP on promoting BDTI is diverse, with a significantly greater impact in the first-tier cities. DTAP plays a more important role in fostering BDTI in places where the digital factor-driven industry is still in its early stages of development.

Research of multimodal transport potential of major cities in China based on the satellite remote sensing

Abstract. By two or more modes of transportation to connect with each other and complete the transport process, multimodal transport could significantly improve transport efficiency, reduce costs, while promote energy conservation and emission reduction, compared with the traditional single mode of transport. Therefore, the multimodal transport development reflects the level of national or regional economic development to some extent. In this study, multimodal transport potential index was built to evaluate the possibility of multimodal transport. Remote sensing images from satellites were used to extract roads, railway stations and airports. A method was proposed to derive the road-rail transport potential index and road-air transport potential index, and then for the analysis of multimodal transport potential in 36 cities. Results show that there is a big gap among 36 cities on the development potential of road-rail and road-air transport. Compared with the road-rail transport potential index, the distribution of road-air transport potential index is more consistent among and within the seven regions. Index values of megacity and super cities are much higher than type I and II big cities. Moreover, in the 36 cities, there is a positive correlation between the multimodal transport potential index and GDP. The research results could be used to quantitatively evaluate the development of transport infrastructure, consequently provide more solid and reliable basic information for the planning, design and scheme adjustment of multimodal transport, thus comprehensively improve the efficiency and quality of multimodal transport, serve the territorial spatial planning.

Spatiotemporal dynamics of urban sprawl in China from 2000 to 2020

ABSTRACT Accurately and timely quantifying the dynamics of urban sprawl is essential for improving land use efficiency and land use planning. However, existing research mainly focused on the sprawl of a single city or urban agglomerations in China, while national scale studies mainly used short-term remote sensing data to quantify urban sprawl. Therefore, we still lack a long term and most up-to-date understanding of urban sprawl in China, especially in different regions, cities of different sizes. Here, we quantified the spatiotemporal dynamics of urban sprawl using urban sprawl index (USI) based on the latest population census, and analyzed its driving force in China during 2000 ~ 2020 using the optimal parameters-based geographical detector. The results showed that in the past two decades, Chinese cities were still experiencing urban sprawl, with an average USI of 3.04, indicating that the average annual growth rate of urban lands was 3.04% higher than that of the urban population. Overall, the sprawl showed a slowdown, with the USI dropping from 3.55 in 2000 ~ 2010 to 2.53 in 2010 ~ 2020. Among regions, urban sprawl was more severe in the western region, where the USI was 5.33 during 2000 ~ 2020 and 89.3% of the cities exceeded the national average sprawl speed. Recently, the driving force of transportation on urban sprawl substantially increased. In the future, the Territorial Spatial Planning should pay attention to confining excessive sprawl of small- and medium-sized cities in the western region of China.

Medium- and Long-Term Electric Vehicle Ownership Forecasting for Urban Residents

With the rapid development of electric vehicles (EVs) in Chinese cities, accurately forecasting the number of EVs used by urban residents in the next five years and more long term is beneficial for the government to adjust industrial policies of EVs, guide the rational planning of urban charging facilities and supporting distribution network, and achieve the rational and orderly development of the EV industry. The paper considers the advantages of using the grey GM(1,1) prediction model to predict the short-term ownership of EVs by urban residents. Then, by forecasting the number of EV users in a certain city in the future and predicting the number of private vehicles in the future, the boundary conditions for long-term year ownership of EVs by residents are determined. Combined with historical data and short-term forecast data generated by the grey prediction model, the model parameters that include the innovation coefficient and imitation coefficient of the Bass model are trained using a genetic algorithm. Finally, the Bass model is used for medium- to long-term ownership forecasting from 2023 to 2040. The prediction error for the target year is provided. The simulation results indicate that the ownership of resident EVs in this city will experience rapid growth in the next five years.

The influence of water safety knowledge on adolescents’ drowning risk behaviors: a framework of risk-protect integrated and KAP theory

IntroductionAlthough previous research has examined the risk factors for drowning behavior among adolescents, it is unclear whether this association is influenced by water safety knowledge. This study aimed to examine whether water safety knowledge is associated with adolescents’ drowning risk behaviors and whether drowning risk perceptions and attitudes could have a chain mediating role in the association between water safety knowledge and adolescents’ drowning risk behaviors.MethodsThis study included 7,485 adolescents from five Chinese provinces and cities. We used the Drowning Risk Behaviors Scales (DRBS) to evaluate the risk of drowning behaviors. The Water Safety Knowledge Scale (WSKS) was used to evaluate the competence level of water safety knowledge. The Drowning Risk Perceptions Scale (DRPS) was used to evaluate the risk level of perceptions, and the Drowning Risk Attitudes Scale (DRAS) was used to evaluate the risk level of attitudes.ResultsThe results of the mediating effect test showed that water safety knowledge (WSK) affected drowning risk behaviors (DRB) through three indirect paths. Drowning risk perceptions (DRP) and attitudes (DRA) have significantly mediated the association between WSK and DRB. In conclusion, DRP and DRA can act as mediators between WSK and DRB, not only individually, but also as chain mediators, where the direct effect is-0.301, the total indirect effect is-0.214, and the total mediated indirect effect is 41.5%.DiscussionWater safety knowledge negatively predicts adolescents’ drowning risk behaviors; water safety knowledge has an inhibitory effect on drowning risk perceptions. Water safety knowledge can directly influence adolescents’ drowning risk perceptions and indirectly affect drowning risk behaviors through the mediation of drowning risk perceptions and attitudes comprising three paths: (1) the drowning risk perceptions mediation path, (2) the drowning risk attitudes mediation path, and (3) the drowning risk perceptions and attitudes mediation paths.

Examining nonlinear effects of socioecological drivers on urban solar energy development in China using machine learning and high-dimensional data

In the context of carbon neutrality target, renewable energy sources have been transforming from “supplementary energy” to “main energy”, which have promoted the green and low-carbon transition of global energy supply system. In-depth analyzing the spatial patterns and driving mechanisms of renewable energy expansion are of significance for optimizing the spatial layout of clean power, and avoiding the phenomenon of wind and solar power curtailment. In this paper, we proposed an ensemble learning model to examine the nonlinear effects of physical geography, resource endowment, and socio-economic factors on solar photovoltaic (PV) capacity at the prefecture-level city scale in China. Using the city-level multi-sources geospatial big data, we extensively collected a total of 175 related explanatory variables and cumulative installed capacity of solar PV power for 295 prefecture-level cities of China. The recursive feature elimination algorithm (SVM-REF) is firstly used to extract the optimal feature subset of urban PV capacity from multi-dimensional features variables. Furthermore, three advanced machine learning models (random forest, decision tree, extreme gradient boosting) are developed to identify the key influencing factors and nonlinear driving effect of urban solar PV power expansion in China. The results show that China's PV installation capacity is highly concentrated in Northern and Northwest parts of China, with the occupancy over 70% in 2019. Moreover, the XGBoost model has the best prediction accuracy (R2 = 0.97) among three methods. We also found that total amount of urban water resources, average solar radiation, and population density are the most important controlling factors for urban solar PV capacity expansion in China, with contribution of 35.6%, 17.7%, and 13.3%, respectively. We suggested that urban solar PV layout mode in China is recommended to gradually shift from resource orientation to the “resource-environment-demand” comprehensive orientation. The paper provides a replicable, scalable machine learning models for simulating solar PV power capacity at the prefecture-level city scale, and serves as a motivation for decision-making reference of the macro siting optimization and sustainable development of China's green power industry.

Can ecological compensation reduce air pollution? New evidence from resource-based cities in China

ABSTRACT China has made great efforts to establish an ecological compensation mechanism, but there lacks empirical evidence on whether this scheme effectively reduces air pollution. To test the effectiveness of air quality ecological compensation (AQEC) on air pollution control, this study considers 114 resource-based cities in China and uses a multi-period difference-in-difference (DID) model for empirical analysis. The finding shows that the AQEC policy significantly reduces the concentration of air pollutants by promoting air pollution prevention and local authority enthusiasm for pollution abatement, resulting in an average annual decrease in PM2.5 concentrations of approximately 3.9 µg/m3 in the pilot cities. The AQEC policy of resource-based cities in eastern and northern China, and those with less financial pressure have greater inhibitory effects on air pollution. The study recommends establishing long-term protection mechanisms and implementing differentiated policies focused on green technological innovation and financial autonomy.

Vitamin D levels and its influencing factors in pregnant women in mainland China: A systematic review and meta-analysis.

Maternal vitamin D deficiency is a prevalent public health issue worldwide. While isolated reports from certain cities in China have highlighted the existence of maternal vitamin D deficiency, no nationwide investigation has been conducted on this topic. Therefore, we conducted a meta-analysis and systematic review to examine the prevalence and associated influencing factors of maternal vitamin D deficiency in mainland China. This study aims to provide a theoretical foundation for future prevention and supplementation strategies for maternal vitamin D. We retrieved relevant Chinese and English literature on the status of maternal vitamin D deficiency in mainland China from databases such as CNKI, Wanfang Data, VIP, CBM, Web of Science, Google Scholar, and PubMed. The literature search and database construction were conducted until September 8, 2023. Data were extracted and synthesized following PRISMA guidelines.After literature screening and quality assessment, we performed meta-analysis, sensitivity analysis, and identified publication bias using RevMan 5.3 software. A total of 26 articles were reviewed, involving 128,820 pregnant women. Among them, 108,768 had vitamin D insufficiency or deficiency, resulting in a prevalence of 84% (95% CI: 81%~88%). Subgroup analysis revealed the highest prevalence of vitamin D deficiency or insufficiency among pregnant women in mainland China to be in the northwest region (94%, 95% CI: 94%~95%). Furthermore, the highest prevalence was observed during the winter and spring seasons (80%, 95% CI: 77%~83%) and in the early stages of pregnancy (93%, 95% CI: 90%~95%). Significant statistical differences (P<0.05) were found among these three subgroups. No publication bias was detected, and sensitivity analysis indicated the stability of the meta-analysis outcome. This study provides evidence of the prevalence of vitamin D deficiency or insufficiency among pregnant women in mainland China. To improve the overall health and well-being of the population, relevant health authorities should develop policies aimed at alleviating this phenomenon.