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Green development is main direction of high-quality economic development in China. Urbanisation and human capital (HC) are important factors affecting green development. This study examines effects of urbanisation and HC on green total factor productivity (GTFP) using least squares dummy variable model, based on provincial data in China from 2001 to 2019. This study then explored impact of urbanisation on GTFP through HC (educated HC, healthy HC, and HC structure), adopting mediating effect and threshold effect model. The results showed that urbanisation and three types of HC promote GTFP in China and coastal region. In inland region, urbanisation has insignificant impact on GTFP, while educated HC and HC structure improve it. The mediating analysis revealed that educated and healthy HC in China and coastal region enhance promotion effect of urbanisation on GTFP, whereas HC structure hinders it. In inland region, only healthy HC stimulates promotion effect of urbanisation on GTFP. Considering threshold effect of educated and healthy HC, promotion effect of urbanisation on GTFP is weaker than threshold value; but effect is stronger above threshold value. The promotion effect of urbanisation on GTFP is stronger when value of HC structure is below the threshold, while effect is weakened as value exceeds threshold value. Policy implications are documented to promote urbanisation in a differentiated manner, increase investment in HC, and strengthen coordination between urbanisation and HC., (© 2024 John Wiley & Sons Ltd.)

This study aims to investigate the impact of foreign direct investment (FDI) inflow, financial development, economic growth, globalization, innovation, and urbanization on the carbon dioxide emissions in China by using long-ran time series dataset from 1970 to 2021 which for the first time used the newly developed dynamic autoregressive distributed lags (ARDL) simulation model for results analysis. Dynamic ARDL simulation model removes the shortcomings of the traditional ARDL models by predicting the actual change (positive and negative shocks) in the independent variables and its impact on the main dependent variables by 5000 simulations through graphical representation. The findings of the long-run dynamic ARDL simulations indicate that FDI inflow, globalization, and innovation negatively and significantly impact the environmental degradation while financial development, economic growth, and urbanization cause to increase the environmental degradation in China. Recommendations are suggested based on the findings of this study., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

In low- and middle-income countries, urbanization has spurred the expansion of peri-urban communities, or urban communities of formerly rural residents with low socioeconomic status. The growth of these communities offers researchers an opportunity to measure the associations between the level of urbanization and the home language environment (HLE) among otherwise similar populations. Data were collected in 2019 using Language Environment Analysis observational assessment technology from 158 peri-urban and rural households with Han Chinese children (92 males, 66 females) aged 18-24 months in China. Peri-urban children scored lower than rural children in measures of the HLE and language development. In both samples, child age, gender, maternal employment, and sibling number were positively correlated with the HLE, which was in turn correlated with language development., (© 2023 The Authors. Child Development © 2023 Society for Research in Child Development.)

This paper explores the impact of population agglomeration on urban economic development quality in various cities of China. The results show that population agglomeration significantly contributes to the improvement of urban green total factor productivity by increasing population diversification, promoting knowledge spillovers, and reducing pollution emission intensity. Moreover, we find that population agglomeration in type II big cities and type I large cities significantly improves green total factor productivity, while the impact of population agglomeration in metropolises and mega-cities on green total factor productivity is not significant. On the one hand, type II big cities and type I large cities are in the period of rising economic development, the population has not yet reached saturation, and there is still a large demographic dividend space. On the other hand, excessive population agglomeration also brings about "urban diseases" such as population congestion and traffic congestion, especially in the metropolises and mega-cities. Finally, using data on producer services and its sub-sectors, we identify a more significant driving effect of high-end talent agglomeration on green total factor productivity., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Abstract: Recent years have seen increasing demand for wider application of strategic environmental assessment (SEA), especially SEA of major policies, as a powerful instrument to safeguard the environment during the rapid industrialization and urbanization in China. Debates on SEA are concentrated on its feasibility and effective implementation in practice. This study applies Emergy analysis within the framework of social–economic–natural complex eco-system theory to overcome the limitations of methods used for assessing regional sustainability so far. This established model is tested in the case of Chinese paper industry to assess the sustainability of 5 policy scenarios. The results show that Emergy-based Indices (EbI) are more effective to measure the sustainability of industry complex ecosystem, thus EbI approach is very useful in SEAs on policy scenarios of a given complex ecosystem. [Copyright &y& Elsevier]

Although studies on the influencing factors of electricity consumption are rich, the focus on the relationship between financial development and electricity consumption is scarce due to the characteristics of financial sector. In fact, the financial development cannot only increase electricity consumption, but also have the spatial spillover effects. Based on the global spatial modeling techniques, the long-term and short-term relationship between financial development and electricity consumption is examined, and the intermediary effect of financial development on electricity consumption through economic growth, urbanization, and industrial structure optimization is also verified. Results show that there is a global co-integration relationship between financial development, economic growth, urbanization, industrial structure optimization, and China's electricity consumption, rather than a local co-integration relationship. When the short-term change of electricity consumption deviates from the equilibrium state, the global error correction mechanism can promote the unbalanced system to return to equilibrium from time and spatial dimension. This study confirms not only the spatial spillover effects, but also heterogeneous influences of financial development on electricity consumption, which provides new evidence to make relevant policies., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

This paper aims to examine the nexus among carbon dioxide (CO 2 ) emissions, urbanization level and industrial structure in North China over the period 2004-2019, according to an expanded Cobb-Douglas production function. The panel econometric techniques are employed to complete the empirical analysis, including cross-sectional correlation test, panel unit root test, panel co-integration test, and panel Granger causality test. The empirical results support the long-term equilibrium relationship among CO 2 emissions, urbanization level and industrial structure in North China, and the urbanization level contributes most to CO 2 emissions, followed by fossil energy consumption. Furthermore, the bidirectional causality between CO 2 emissions and urbanization level and unidirectional causality from industrial structure to CO 2 emissions are found in North China, indicating that urbanization level and industrial structure have significant impacts on CO 2 emissions. Finally, according to the empirical findings, several policy suggestions are proposed for the purpose of reducing CO 2 emissions in North China., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Regional density is a useful tool for analyzing regional spatial structure as well as a good starting point for analyzing regional CO2 emissions per capita. This paper empirically analyzes the relationship between regional density and per capita CO 2 emissions in China's prefecture-level administrative regions. We improve the CO 2 emission measurement method for prefecture-level administrative regions and estimate the per capita CO 2 emissions of 252 prefectural-level cities in China from 2003 to 2013. Using panel fixed effect model regression, and taking the terrain roughness index as an instrumental variable to solve endogeneity, we find that the relationship between regional density and per capita CO 2 emissions presents in an inverted U-shape, per capita CO 2 emissions first increase with the increase of regional density, and after reaching the turning point, it decreases with regional density. In a mechanism test, analyzing the interaction terms between regional density and industrial structure, and regional density and urbanization level respectively. We found that industrial structure and urbanization are important mechanisms for regional density to affect CO 2 emissions. In order to reduce per capita CO 2 emissions, we propose corresponding policy implications for the regions in different positions of the "U" curve., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Water, energy, and food security are global concerning issues especially in China. To promote regional environmental management cooperation as well as find resource security influencing factor differences among regions, this paper calculates the water-energy-food (W-E-F) pressure, find W-E-F pressure's regional differences, and the influencing factors by Dagum Gini coefficient decomposition and geographically and temporally weighted regression model for panel data (PGTWR). First, the temporal trend of W-E-F pressure is decreasing and then increasing during 2003-2019; pressure in the eastern provinces is significantly higher than in other provinces and structurally energy pressure is the dominant resource pressure in W-E-F in most provinces. Besides, inter-regional differences are the main source of regional differences in China's W-E-F pressure, particularly for the inter-regional differences between eastern regions and other regions. In addition, there are obvious spatio-temporal heterogeneity effects of population density, per capita GDP, urbanization, energy intensity, effective irrigated area, and forest cover on W-E-F pressure. Balancing regional development gaps and developing differentiated resource pressure mitigation strategies based on the characteristics of different regional drivers are of great importance., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

This study investigates the heterogeneous causal linkages between urbanization, the intensity of electric power consumption, water-based pollutant emissions, and GRP in regional China by developing an urbanization-augmented "Stochastic Impacts by Regression on Population, Affluence, and Technology" (STIRPAT) model. A whole country panel of 29 provinces as well as region sub-panels of China, for the period 1999 to 2018, are estimated employing common correlated effects mean group approach (CCEMGA), which offers robustness against heterogeneous characteristics and cross-sectionally dependent series. From the theoretic modeling aspect, the intensity of electric power consumption and urbanization have been introduced as the determinants of water-based pollutant emissions in the STIRPAT modeling framework. Based on empirical results, first, GRP growth has shown appealing behavior in the form of its heterogeneous impacts on water-based pollutant emissions growth in the case of different regions. For instance, its impact is noted to be positive and statistically significant for the western region, which turned positive but statistically insignificant for the intermediate region. And it further turned significantly negative in the case of the eastern region. We call this phenomenon as "development level-based emission mitigation effect." Second, in terms of the impact of GRP growth on urbanization, the "development-based urbanization ladder effect" has been found. Based on heterogeneous causal links, firstly, the existence of a positive bilateral causal link between the intensity of electric power consumption and GRP growth and urbanization and GRP growth has been validated. Secondly, a positive unidirectional causal link emerged from urbanization to the intensity of electric power consumption and water-based pollutant emissions growth. Thirdly, the causal connection between GRP growth and water-based pollutant emissions growth remained very interesting and of mixed nature. Based on empirical findings, useful policies are extended. Graphical abstract.

Compared with other transportation facilities, high-speed rail (HSR) may be more beneficial to "green development." Based on a sample of 276 cities in China over 2005-2019, this study calculates the actual and change values of green total factor productivity (GTFP) with the stochastic frontier approach (SFA) and investigates the effect of HSR on GTFP using the time-varying difference-in-difference model and propensity score matching analysis. Our research results show a significantly positive effect of HSR on GTFP through reducing energy consumption and environmental pollution, as well as improving technological innovation. HSR-connected cities are found to have outperformed non-HSR-connected cities by 12.8% regarding GTFP in the sample period, and the effect is stronger for the eastern region and/or the central cities compared with the rest of the country. The research findings of this paper have important policy implications regarding China's HSR development and its impact on economic growth as well as the natural environment., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The coordination relationship between new-type urbanization and urban low-carbon development under the goal of carbon neutrality has become a hot issue that needs to be focused on when formulating policies. Based on the estimation of urban CO 2 emissions by night light data, this study used spatial autocorrelation, spatial Markov chain and geographically weighted regression model to measure the spatial correlation and spillover effects of the coupling coordination degree of two systems in the Yangtze River Delta urban agglomeration from 2005 to 2018 and analyzed the influencing factors. The results showed that (1) the coupling coordination degree showed an increasing trend, but the club effect was quite obvious, and the regional pattern was higher in southeast and lower in northwest; (2) the spatial spillover effect of coupling coordination degree is significant, which aggravates the long-term persistence of the imbalance pattern; (3) regional economic level, government fiscal regulation, and industrial upgrading are the main driving forces for the increase of coupling coordination degree, while over-concentration of population and low energy efficiency are the main obstacles. Finally, on the basis of these conclusions, we provide targeted policy planning suggestions for policy makers., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The increasing drift of urbanization and its impact on urban human settlements are of major concern for China cities. Therefore, demystifying the spatial-temporal patterns, regional types, and affecting factors of urban livability in China is beneficial to urban planning and policy making regarding the construction of livable cities. In accordance with its connotation and denotation, this study develops a systematic evaluation and analysis framework for urban livability. Drawing on the panel data of 40 major cities in China from 2005 to 2019, an empirical research was further conducted. The results show that urban livability in China has exhibited a rising trend during the period, but this differs across dimensions. The levels of urban security and environmental health are lower than those of the three other dimensions. Spatially, cities with higher livability are mainly distributed in the first quadrant divided by the Hu Line and Bole-Taipei Line. Cities in the third quadrant are equipped with the lowest livability. In addition, the 40 major cities can be divided into five categories, and obvious differences exist in terms of the geographical distribution, overall livability level, and sub-dimensional characteristics of the different types. Furthermore, the results of the System GMM estimator indicate that the overall economic development exerts an inhibiting effect on the improvement of urban livability in present-day China, but this logical effect exhibits obvious heterogeneity in different time periods and diverse city scales. Finally, there are also differences in the influencing direction and degree of specific economic determinants., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

China's expansion in higher education has also given rise to developing university towns in sub-cities to deal with increasing enrollments and contribute to broader socio-economic development. Taking Xiasha University Town in Hangzhou as a case study, this paper adopts a tripartite framework of teaching, research, and service to investigate the role of university towns in human capital and skills development, regional innovation, and social and community services. This paper is the first to systematically evaluate Hangzhou's largest university town after more than two decades since its development; it also provides a more nuanced and contextual approach to university town developments similar to others in China or broader learning region integrations globally. Documentary research and interviews from relevant stakeholders were utilized to collect data. This study presents the three dimensions contextualized within Xiasha and points to issues that can further improve such through a more efficient resource-sharing scheme, a focused discipline orientation, more significant investments in research and development, and a more active role in community engagement.

China has witnessed significant growth in trade through vide range trade liberalization strategies and urbanization has also been entered in advanced stage. Based on these dynamics, how much energy consumption of both renewable and none renewable account for energy consumption in whole system is a point of higher attention for the researchers. To understand this salient emerging debatable concern, we investigate the impact of trade openness and urbanization effect on renewable and non-renewable energy consumption in China for the period 1990-2018. We apply the quantile regression technique for the analysis; our results show that trade significantly increases the non-renewable energy consumption in all quintiles while partially increasing renewable energy consumption. This shows that trade activities in production and export commodities heavily rely on non-renewable energy inputs instead of renewable energy inputs. Urbanization affects non-renewable energy consumption only in three quintiles, while its effect is insignificant in most of the quintiles. Similarly, urbanization does not affect renewable energy consumption as in almost all quantiles the coefficients are statistically insignificant. This implies that urbanization is one of the determinants of energy consumption in China. The empirical findings of this study suggest some policy recommendations; first, the government needs to implement certain regulations while expanding trade to minimize the negative effect of non-renewable energy consumption; besides government should provide incentives to industrial units and traders for using renewable energy which may help to attain long term sustainable development goals. The government should also put certain limitations on population moving from rural to urban destinations., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The main purpose of this article is to link the environment, economy, electricity, and society and put forward a new point of view. The current research mainly explores the relationship between the environment, economy, and society and lacks a discussion on electricity. Using a new research framework, this article examines the relationship between energy intensity, energy consumption structure, population density, urbanization rate, and carbon intensity based on relevant data from 2000 to 2017 in China. In the empirical research, according to the cluster analysis, China's 30 provinces are divided into three regions according to the electrification rate standard. The cross-sectional dependence test method is used to verify the cross-sectional dependence of the data, and the second-generation panel unit root test method is used. Exploring the relationship between the variables, this article finally uses the convergence analysis method to explore the degree of influence of each variable on the carbon intensity. The empirical results show that there are both short-term effects and long-term relationships in various regions, and the influencing factors of each region are different. It further shows that the carbon intensity of the four panels shows convergence, β absolute convergence, and β conditional convergence, but the main influencing factors in different regions are different. Finally, based on the results of empirical research, policy recommendations for reducing carbon intensity in different regions are put forward., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

With the advancement of China's economic and social development and urbanization, the scale of out-of-town migrant workers has been expanding. Following this, migrant worker children's education problem has become increasingly prominent and has gradually become a focus of education research. This paper reviews recent studies on migrant worker children's acceptance of compulsory education, and summarizes its existing education problems, aiming to provide direction and support for further promoting education equity and sustainable development of urban and rural education.

The development of urbanization has brought new challenges to the ecological environment, and the promotion of green technology innovation and development is widely recognized as an essential method to achieve cities' economic benefits and environmental protection. This paper examines whether the new urbanization pilot policies (NUP) increase green technology innovation (GTI) from both theoretical and empirical perspectives. This paper examines the impact of new urbanization on GTI by analyzing data from 285 cities in China between 2010 and 2021, using the multi-period DID model with the implementation of NUP as an exogenous policy shock. The study results indicate that NUP significantly affects GTI, and the conclusion still holds after the parallel trend test, placebo test, and other robustness tests. Heterogeneity analysis shows that the NUP significantly enhances GTI in low environmental pollution, non-resource-based, Medium-sized, and Central Region cities. The test of moderating effect shows that NUP has a "linkage effect" with the government's environmental attention, financial investment in innovation, and regional talent pooling. The findings of this paper provide empirical evidence and decision-making reference for promoting NUP and sustainable development of cities. [ABSTRACT FROM AUTHOR]

This paper uses inter-provincial panel data from 2011 to 2017, a linear regression model, and a threshold model to conduct empirical analyses of the impact of the digital economy on China’s overall economic growth and the three main sectors of industry. The paper then investigates the impact and effects the digital economy has had on the economic growth of the three main sectors of industry in China’s eastern, central, and western regions. Finally, the paper investigates the most significant differences among the various regions and the threshold effects of urbanization levels on the relationship between the digital economy and economic growth. The findings indicate a significantly positive correlation between the digital economy and regional economic growth. Moreover, geographical factors notably influence this correlation. The digital economy exerts a positive effect on all sectors of industry. It may not substantially impact industrial development in regions with highly developed infrastructure. Regarding the other regions, the digital economy exhibits varying degrees of impact due to the differences in the specific indicators. The conclusion drawn by the threshold model is that the magnitude of the threshold effect correlates with geographic factors. No threshold effect was observed in the eastern region, while the threshold effect occurred in the central region when the urbanization levels for the provinces were below 0.6645. Similarly, the threshold effect was noted in the western region when the urbanization level was below 0.3931. Considering all of this, the study also offers policy recommendations that will help balance the regional development of digital economies, accelerate the digital transformation of traditional industries, enhance digital infrastructure construction, refine the formulation and implementation of data policy, and establish relevant incentive mechanisms. [ABSTRACT FROM AUTHOR]

The effects of urbanization on carbon emissions (EUCE) are complex, while rare work has comprehensively elaborated on how various aspects affect and develop. In this study, utilizing Citespace and VOSviewer software, a global scientometric visualization analysis was conducted to excavate various impacts and future trends of urbanization on carbon emissions. Based on publications from the year 1982 to 2018, the spatial-temporal distribution of publications, collaboration, current hotspots, and future trends of EUCE were carried out. The results indicated that between 1992 and 2018, there were accelerated increasing trends of EUCE researches world widely, among which China, the USA, and UK ranked the top 3. Relevant research firstly appeared in the USA, while grew most rapidly in China. Research subjects mainly concentrate on population migration, resource consumption, land use and land cover change (LULCC), energy conservation, non-carbon greenhouse gases like CH 4 and N 2 O. And attention on carbon footprint has become a hotspot for carbon mitigation. For research fronts, ecosystem service offered by urban green space has gradually evolved as a research focus. Besides, energy transformation technology is critical for mitigating carbon emissions and has become an important concern in the future development. Furthermore, the timeline visualization analysis indicates that all the research topics related to EUCE are cited and connected with each other, reflecting the necessity of interdisciplinary integration in scientific research. Overall, our study has provided a quantitative visualization on the current situation and future trends of EUCE subject, which will be helpful to subsequent research and policy guidance.

This study examines links between Morgan and Stanley capital Investment (MSCI), foreign direct investment (FDI), renewable energy, urbanization, and trade openness on environmental degradation in (Brazil, Russia, India, China, South Africa) BRICS countries. In this study, generalized method of moment (GMM) estimation is applied on a data set ranging from 1993 to 2018. Results illustrate that stock market index price (MSCI) has negative relationship on CO 2 emissions in India, China, Russia, and South Africa and has positive relationship in Brazil. One possible reason for this is strong environmental regulations and their enforcement by Brazilian government. The study also finds that trade openness, FDI, and urbanization have a significant positive relationship on environmental degradation. The impact of stock market development on environmental degradation varies among BRICS countries. Our outcomes have significant policy implications. For example, the policy makers have to initiate effective strategies to promote the renewable energy sources to meet the increasing demand for energy by replacing the use of conventional energy such as coal, gas, and oil. This will help to reduce the CO 2 emissions from fossil fuel and ensure sustainable stock market development in the BRICS nations. BRICS countries who have taken the initiative and formulated policies for businesses to conserve the environment play a positive role compared to those who do not.

The ability of fast restoration reflects power system resilience and safety. This paper proposes a partitioning decision-making method for parallel restoration based on the label propagation algorithm and the cooperative game theory. The topological and physical characteristics of blackout systems are considered as the edge weight and the node importance simultaneously for formulating the partitioning model. By the label propagation algorithm, various labels representing different subsystems mark all buses. To accelerate the speed of convergence and prevent the label oscillation, this paper proposes a game strategy of cooperation between buses and subsystems by evaluating the Shapley value of buses. The partitioning constraints are integrated into each label propagation process to assess the feasibility of the partitioning strategy. Finally, case studies on the IEEE 39- and 118-bus test systems and an actual urban power system in South China verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This research attempted to investigate the impact of urbanization and spatial agglomeration on carbon emissions. To achieve the goal, the dynamic panel data model was employed to explore the nonlinear relationship between urbanization and carbon emissions for 166 cities in China taking the period 2005-2015, and the Gini coefficient of urban population size distribution in 15 urban agglomerations were calculated to analyze whether the spatial agglomeration of cities contributed to environmental protection. The results show that there is an inverted U-shaped curve between urbanization and carbon emissions; high-level urbanization development helps reduce carbon emissions; the spatial agglomeration of cities can contribute to carbon reduction to a certain extent based on the empirical results of the spatial agglomeration promotes the early arrival of the inflection point in the inverted U-shaped relationship between urbanization and carbon emissions; and the improvement of urban agglomeration level can present an abatement effect on carbon emissions at a lower urbanization level, which enhances the positive environmental effect of urbanization development compared with the decentralized urban distribution model. Furthermore, there is a significant U-shaped relationship between spatial agglomeration and carbon emissions, which indicates that the scientific planning of urban clusters will achieve economies of scale and agglomeration effect, thereby reducing carbon emissions. These findings contribute to complement the existing literature as well as provide some implications related to sustainable urban development for policymakers.

Industrialization and urbanization are significant facets of modernization. The asynchronous development of the two is closely related to the agglomeration of producer services. This paper constructed an asynchrony index to describe the development gap between industrialization and urbanization. Various spatial weight matrices were introduced to test the spatial autocorrelation of the asynchrony index. Applying spatial econometric models, we explored the impact of agglomeration of producer services on the asynchrony index from two aspects: diversified agglomeration (DA) and specialized agglomeration (SA). The following conclusions are drawn from the empirical findings, which are based on data from 31 Chinese provinces between 2008 and 2019: (1) the asynchrony of industrialization and urbanization exhibits the spatial autocorrelation increasing over time; (2) SA exacerbates the asynchrony, while DA alleviates the asynchrony; (3) SA exerts greater impacts in highly industrialized and urbanized regions, while DA exerts greater effects in lowly industrialized and urbanized regions; and (4) agricultural dependence and infrastructure level weaken the impacts of SA and strengthen the impacts of DA. Income level weakens the impacts of both SA and DA. The results of this study provide a reference for policymakers to adjust the industrial layout in a targeted manner to regulate the asynchronous nature of modernization development. Peace and development are the themes of the world today. Most developing countries are experiencing or about to experience industrialization and urbanization. The world reality indicates that the two are not always synchronized in countries due to resource and cultural differences. Producer services not only improve agricultural and industrial production efficiency but also bring population agglomeration effects like other industries. In the era of informatization, the producer services exert a profound impact on industrialization and urbanization through two agglomeration modes. This technical paper quantifies the asynchrony between industrialization and urbanization using data from 31 provinces in China and verifies the opposite effects of two agglomeration modes on asynchrony. In cities with different levels of industrialization and urbanization, cities with higher or lower agricultural dependence, and cities with higher or lower infrastructure levels, the impact direction of the two agglomeration modes shows stability, while the magnitude varies. Cities with higher per capita income tend to develop into consumer cities, where industrialization should lag behind urbanization. [ABSTRACT FROM AUTHOR]

This paper expounds the theoretical logic among digital inclusive finance, urbanization, and agricultural mechanization level, puts forward the research hypothesis, and then selects the county unbalanced panel data of 1309 counties in China from 2014 to 2020 based on the two-way fixed model with standard error clustering to county level and mediating effect model for empirical data regression analysis. Through baseline regression analysis, mediation effect analysis, and heterogeneity analysis, the findings of this paper are as follows. First, digital financial inclusion has a significant positive effect on the growth of agricultural mechanization. Second, digital inclusive finance at the county level can also indirectly affect the growth of agricultural mechanization through urbanization. That is, agricultural mechanization has an intermediary effect between the financial agglomeration at the county level and the growth of farmers' income. Third, the impact of county-level digital financial inclusion on the growth of agricultural mechanization level is significantly heterogeneous, and the promoting effect is significant in areas with balanced grain production, national-level poor county or contiguous areas of dire poverty, and areas with a good foundation for digital financial inclusion. By analyzing digital inclusive finance, urbanization, and agricultural mechanization, this paper proposes targeted policy recommendations. First, the government can promote agricultural mechanization by developing digital financial inclusion. Second, the government should guide and accelerate the process of digital financial inclusion, promoting urbanization thereby amplifying the positive impact of digital financial inclusion on agricultural mechanization. Third, given the heterogeneity of the impact of digital financial inclusion on agricultural mechanization, local development should focus on developing different dimensions of digital financial inclusion according to specific conditions. [ABSTRACT FROM AUTHOR]

The Ming Great Wall Military Defense System is the most complete ancient military cultural heritage in China, which is of great significance to the study of China's ancient military defense mechanism and pattern. Military settlement is an important carrier of this mechanism. The estimation and in-depth understanding of its value can further excavate the profound connotation of the military defense system and the Great Wall spatial pattern in the Ming Dynasty. This paper adopts the AHP-CRITIC weighting approach to determine the weights of the historical value, scientific value, social value, cultural value and artistic value of the settlement heritage, so as to construct the value evaluation model of military settlements, and takes 34 Ming Great Wall military settlements in the Liaoxi Corridor as an example for evaluation. The results of the evaluation identified the priority settlements for conservation and development, and also explored their relationship with historical status, urbanization processes and official policies. The evaluation model constructed in this paper has a certain universality, and can also be followed in the evaluation of other military settlements in the Ming Great Wall Defense System, so as to obtain the overall cognition of the settlement system. [ABSTRACT FROM AUTHOR]

Territorial spatial planning involves fixability and flexibility in different driving factors related to control and development orientation, and they play an important role in regional sustainable development, especially in developing countries such as China. With rapid urbanisation and industrialisation, China has been impacted by conflicts between development and protection in territorial space. To integrate the contradictions among different territorial spatial planning measures, planners and scholars have started to focus on studies regarding fixability–flexibility relationships and integration. However, the relationship between and integration of fixability and flexibility in territorial spatial planning have yet to be clearly summarised. This paper explores an innovative research direction for the fixability–flexibility relations in territorial spatial planning from a new perspective, the Food–Energy–Water Nexus, which is a dynamic and comprehensive framework for Sustainable Development Goals (SDGs) studies. This paper covers the existing research on fixability and flexibility in territorial spatial planning. Moreover, after summarising the conflicts of fixability and flexibility, the dialectical relationship between and the integration of fixability and flexibility are researched. [ABSTRACT FROM AUTHOR]

This article explores the concept of "immigrant consumption behavior (ICB)" in the context of its holistic surroundings. The study investigated the current dynamics and scientometrics of the research field regarding immigrant consumption behaviors. Using an integrative approach employing bibliometric and content analysis, it scrutinized a collection of 224 studies from the Web of Science and Scopus databases to detect the field evolution, disciplinary distribution thematic map, and emerging trends in the ICB literature, as well as to forecast research directions. The results showed that ICB is a multi- and inter-disciplinary research area that experienced three phases of growth between 1989 and 2023: initiation (1989–2006), development (2007–2012), and consolidation (2013–now). The thematic analysis revealed five current trends, i.e., (1) the immigrant consumption behavior domain, (2) the demographic sub-groups of immigrants and related consuming products, (3) country-, region-, and cultural-focused studies, (4) the effects of culture and the acculturation process, and (5) the impact of urbanization. Each theme contains a number of sub-themes. Based on the current thematic evolution and keyword burst analysis, this paper suggests a number of critical research directions, comprising (1) observatory studies including remittances, China, ethnic minorities, lifestyle, inequality, urbanization, and food consumption; (2) context-based studies focused on socioeconomic, cultural, legal, and environmental factors; (3) studies based on compensatory and compromissory consumption behavior; (4) studies focused on sustainable and green consumption behaviors; and (5) studies regarding the behavior of specific demographic co-ethnic communities. The results have great implications for developing interventions and programs that can support immigrant populations in making appropriate consumption patterns and adapting to new cultural environments. The paper pushes forward the ICB investigation from individual empirical studies to synthesis-based research, which (1) provides an ample overview of the ICB literature, (2) identifies research priorities, emerging trends, and gaps, (3) proposes new research avenues for investigation, and (4) outlines expected contributions. The research contributes to a variety of disciplines through the provision of new knowledge, since ICB studies are multidisciplinary in nature. It also has numerous implications for policymakers and practitioners. [ABSTRACT FROM AUTHOR]

Purpose: This paper explores the relationship between state-led urbanization and primary industry development using the difference-in-differences (DiD) method. Design/methodology/approach: The study uses the DiD method. Findings: Exploiting county-city mergers during 2010–2018, the key strategy to expand the city outward and promote urbanization on the urban fringe by local government, the authors find that county-city mergers led to the growth of primary industry decline by 4.23%. The result can be explained by the loss of essential production factors, including land and labor used for farming. In addition, the negative effect is more pronounced for counties with more substantial manufacturing. The results indicate that urbanization in China relocates land and labor; however, it does not improve the efficiency of agricultural output. Originality/value: This paper contributes to the understanding of urbanization and rural development from the perspective of the primary industry by showing production factor redistribution. Second, this study complements the literature on local government mergers. [ABSTRACT FROM AUTHOR]

Labor mobility is an inherent component of economic development and labor market changes. With globalization and urbanization, labor mobility is on the rise in many developing countries, and it is of great significance to study the economic outcomes and poverty alleviation effects of this phenomenon. This paper explores the impact of labor mobility on the wages of rural migrants when they move out with their fellow townsmen (folks from the same county). The study uses the China Migrants Dynamic Survey (CMDS) data and applies the Propensity Score Matching (PSM) method for empirical analysis. Our results suggest that labor mobility with fellow townsmen significantly increases the wages of rural migrants. The paper shows two promotion mechanisms: mobility with fellow townsmen affects the wages of rural migrants by improving their ability to search for information and negotiate wages. Heterogeneity analysis indicates that mobility with fellow townsmen significantly increases the wages of rural migrants engaged in producer service, consumer service, blue-collar occupations, and working in state-owned and private enterprises. Furthermore, it has a more positive impact on the wages of older rural migrants from an intergenerational perspective. Interestingly, rural migrants may "give up" part of their wages to care for their families when they move with their spouses, parents, or children. Therefore, the government needs to take effective policy measures to promote the employment service system and improve the labor rights and interests protection mechanism for rural migrants. [ABSTRACT FROM AUTHOR]

With the development of the digital city, data and data analysis have become more and more important. The database is the foundation of data analysis. In this paper, the software system of the urban land planning database of Shanghai in China is developed based on MySQL. The conceptual model of the urban land planning database is proposed, and the entities, attributes and connections of this model are discussed. Then the E-R conceptual model is transformed into a logical structure, which is supported by the relational database management system (DBMS). Based on the conceptual and logical structures, by using SpringBoot as the back-end framework and using MySQL and Java API as the development tools, a platform with data management, information sharing, map assistance and other functions is established. The functional modules in this platform are designed. The results of JMeter test show that the DBMS can add, store and retrieve information data stably, and it has the advantages of fast response and low error rate. The software system of the urban land planning database developed in this paper can improve the efficiency of storing and managing land data, eliminating redundant data and sharing data. [ABSTRACT FROM AUTHOR]

This study explores the conservation of historic flyway corridors for egret in the Greater Bay Area (GBA), with a focus on habitat connectivity and dynamic corridors. To address the gaps in previous research, we used field observations, bio-climatic data and landcover information spanning three decades. Our approach involves MaxENT modeling and the Linkage Mapper method. The results showed that the MaxENT model effectively simulated the egret habitats at different levels, with coastlines and riverbanks emerging as primary habitat zones. Moreover, bio-climatic factors, particularly Bio 19 and Bio 8, played a dominant role, accounting for 90 % of the habitat suitability in 2020. Other factors contributed rather minimally. Through the utilization of resistance surface and corridor extraction methods, noteworthy alterations in the flyway networks emerged post-2000, followed by a gradual return to normal. Connectivity analyses highlighted a critical 30 km threshold for the egret preservation. Corridor widths should be determined based on cost-effective considerations. We conclude that combining MaxENT with the Linkage Mapper method, even with limited egret observations and integrating multi-source data, such as land cover, might simulate potential suitable habitats and flyway dynamics for waterbirds such as egrets. This study provides valuable insights for the egret conservation and the preservation of their habitats in the GBA, contributing to a global waterbird diversity and habitat quality., Competing Interests: Declaration of competing interest The authors declare they have no known competing financial interests or personal relationships that could have influenced the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Coastal cities, as hubs of social and economic activity, have witnessed rapid urbanization and population growth. This study explores the transformative changes in urban municipal wastewater treatment practices and their profound implications for greenhouse gas (GHG) emissions in Chinese coastal provinces. The approach employed in this study integrates comprehensive data analysis with statistical modeling to elucidate the complex interplay between urbanization, wastewater treatment practices, and GHG emissions. Results reveal a substantial surge in GHG emissions from coastal wastewater treatment, rising from 3367.1 Gg CO 2 e/yr in 1990-23644.8 Gg CO 2 e/yr in 2019. Spatially, the top 20 cities contribute 56.0% of emissions, with hotspots in the Bohai Sea Region, Yangtze River Delta, and Pearl River Delta. Initially dominated by emissions from untreated wastewater, post-2004, GHG emissions from treatment processes became the primary source, tied to electricity use. Growing population and urbanization rates escalated wastewater discharge, intensifying GHG emissions. From 1990 to 2019, average GHG intensity ranged between 320.5 and 676.6 g CO 2 e/m 3 wastewater, with an annual increase of 12.3 g CO 2 e/m 3 . GHG intensity variations relate to the wastewater treatment rate, impacting CH 4 , N 2 O, and CO 2 emissions, underscoring the need for targeted strategies to mitigate environmental impact., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

The rapid advancement of global economic integration and urbanization has severely damaged the stability of the ecological environment and hindered the ecological carbon sink capacity. In this study, we evaluated the spatiotemporal evolution pattern of landscape ecological risk (LER) in the Loess Plateau from 2010 to 2020. This was examined under the driving mechanism of human and natural dual factors. We combined the random forest algorithm with the Markov chain to jointly simulate and predict the development trend of LER in 2030. From 2010 to 2020, LER on the Loess Plateau showed a distribution pattern with higher values in the southeast and lower values in the northwest. Under the interaction of human and natural factors, annual precipitation exerted the strongest constraint on LER. The driving of land use and natural factors significantly influenced the spatial differentiation of the LER, with a q-value >0.30. In all three projected scenarios for 2030, there was an increase in construction land area and a significant reduction in cultivated land area. The urban development scenario showed the greatest expansion of high-risk areas, with a 5.29 % increase. Conversely, the ecological protection scenario showed a 1.53 % increase in high-risk areas. The findings have provided a reference for ecological risk prevention and control, and sustainable development of the ecological environment in arid regions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Extreme meteorological events and rapid urbanization have led to serious urban flooding problems. Characterizing spatial variations in flooding susceptibility and elucidating its driving factors are essential for preventing damages from urban pluvial flooding. However, conventional methods, limited by spatial heterogeneity and the intricate mechanisms of urban flooding, frequently demonstrated a deficiency in precision when assessing flooding susceptibility in dense urban areas. Therefore, this study proposed a novel framework for an integrated assessment of urban flood susceptibility, based on a comprehensive cascade modeling chain consisting of XGBoost, SHapley Additive exPlanations (SHAP), and Partial Dependence Plots (PDP) in combination with K-means. It aimed to recognize the specific influence of urban morphology and the spatial patterns of flooding risk agglomeration under different rainfall scenarios in high-density urban areas. The XGBoost model demonstrated enhanced accuracy and robustness relative to other three benchmark models: RF, SVR, and BPDNN. This superiority was effectively validated during both training and independent testing in Shenzhen. The results indicated that urban 3D morphology characteristics were the dominant factors for waterlogging magnitude, which occupied 46.02 % of relative contribution. Through PDP analysis, multi-staged trends highlighted critical thresholds and interactions between significant indicators like building congestion degree (BCD) and floor area ratio (FAR). Specifically, optimal intervals like BCD between 0 and 0.075 coupled with FAR values between 0.5 and 1 have the potential to substantially mitigate flooding risks. These findings emphasize the need for strategic building configuration within urban planning frameworks. In terms of the spatial-temporal assessment, a significant aggregation effect of high-risk areas that prone to prolonged duration or high-intensity rainfall scenarios emerged in the old urban districts. The approach in the present study provides quantitative insights into waterlogging adaptation strategies for sustainable urban planning and design., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

This study investigated dissolved PAHs and OCPs in Quanzhou Bay estuaries, assessed their ecological risk, and examined anthropogenic impacts on contaminant distribution. Results showed that dissolved ∑ 24 PAH concentrations ranged from 117 to 709 ng/L (mean: 358 ng/L), with dominance of 2-ring PAHs (Naphthalene, 1-Methylnaphthalene, and 2-Methylnaphthalene). Dissolved DDT levels ranged from 0.06 to 0.49 ng/L (mean: 0.28 ng/L), while HCBz concentrations varied from 0.02 to 0.44 ng/L (mean: 0.20 ng/L). PAHs were higher in the north due to urbanization and transport, while OCPs showed higher levels in the south due to historical agricultural use. Rural areas, water bodies, and wetlands significantly influenced the behavior of PAHs according to Spearman correlation and lasso regression analyses. Quanzhou Bay was categorized as a low to medium risk area based on dispersion simulation and ecological risk assessment, highlighting implications for future sustainable development and policy planning. CAPSULE: The coupled relationship between human activities and the distribution of dissolved PAHs and OCPs in urbanized estuaries was explored using statistical methods and GIS technology, providing valuable insights into environmental processes and pollutant control policies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Affected by human activities, the naturally occurring river network in the southeastern plain of Yinzhou has gradually evolved into a natural-artificial composite water system, and changes in river connectivity due to changes in river network systems have caused water security problems, including urban flooding. To clarify the river connectivity change and its relationship with the urbanization process, this paper discusses an evaluation method for river connectivity based on complex networks and cellular automata (CA) from the perspective of complex systems, quantitatively analyzes the spatial-temporal characteristics of the structural and functional river connectivity in the study area during the 1990s-2020s, and reveals the impact of river nodes and chains on the connectivity level under the disturbance of natural or human factors. The results contained the following revelations: ① River connectivity showed a decreasing trend in the initial and rapid development stages of urbanization from the 1990s to the 2010s and a limited increasing trend in the optimization and upgrading stages from the 2010s to the 2020s. ② River network degradation and ongoing connectivity decline are found in the northeastern part of the study area. The highest river connectivity exists in Dongqianhukaifaqu. ③ The number of river nodes and chains should be maintained at approximately 80% for normal river connectivity. The nodes of high degree in the inflow area are listed in the key protection areas. ④ Changes in river connectivity are significantly correlated with the urbanization process. Changes in the functional connectivity level affect the magnitude of a flood. This study provides a theoretical basis for river network connectivity improvement and flood prevention in plain areas., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

This paper systematically analyzes the spatiotemporal evolution trends and macroeconomic driving factors of farmland transfer at the provincial level in China since 2005, aiming to offer a new perspective for understanding the dynamic mechanisms of China's farmland transfer. Through the integrated use of kernel density estimation, the Markov model, and panel quantile regression methods, this study finds the following: (1) Farmland transfer rates across Chinese provinces show an overall upward trend, but regional differences exhibit a "U-shaped" evolution characterized by initially narrowing and then widening; (2) although provinces have relatively stable farmland transfer levels, there is potential for dynamic transitions; (3) factors such as per capita arable land, farmers' disposable income, the social security level, the urban‒rural income gap, the urbanization rate, government intervention, and the marketization level significantly promote farmland transfer, while inclusive finance inhibits transfer, and agricultural mechanization level and population aging have heterogeneous impacts. Therefore, to achieve convergence of low farmland transfer regions to medium levels while promoting medium-level regions to higher levels, it is recommended that the government increase support for agricultural mechanization, increase farmers' income and social security levels, and optimize marketization processes and government intervention strategies. The main contributions of this paper are (1) systematically revealing the spatiotemporal evolution patterns of China's farmland transfer and (2) employing panel quantile regression methods to explore the heterogeneous impacts of driving factors, providing more precise and detailed empirical support for the government's formulation of farmland transfer policies., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Chen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Rapid urbanization and industrialization have resulted in diverse anthropogenic activities and emissions between urban and non-urban regions, leading to varying levels of exposure to air pollutants and associated health risks. However, endeavors to mitigate air pollution and health benefits have displayed considerable heterogeneity across different regions. Therefore, comprehending the changes in air pollutant concentrations and health impacts within an urbanization context is imperative for promoting environmental equity. This paper uses gross domestic product (GDP)- and population-weighted methods to distinguish anthropogenic emissions from urban and non-urban areas in China and quantified their contributions to fine particulate matter (PM 2.5 ) using the Community Multiscale Air Quality (CMAQ) model in 2010 and 2019. Anthropogenic emissions from urban and non-urban (outside urban) regions decreased by 26 and 44% from 2010 to 2019, respectively, resulting in 31 and 28% reductions of PM 2.5 in China. PM 2.5 -related premature mortality attributed to non-urban and urban anthropogenic emission decreases by 8%. Non-urban anthropogenic activities are the main contributor to PM 2.5 (56% in 2010 and 2019) and its associated premature mortality (59%), which also predominantly affects non-urban premature mortality (37-42% in 2010-2019). Population changes increase the proportion of premature mortality in urban populations (7-19%) from 2010 to 2019. This study emphasizes the shift of affected populations due to urbanization and population changes.

Changes in aerodynamic and thermal conditions caused by urbanization can impact regional meteorological conditions, subsequently affecting air quality. Updated Moderate-resolution Imaging Spectroradiometer (MODIS) land use data and coupled with the urban canopy models (UCMs) in the Weather Research and Forecasting (WRF) model. This enabled the impact of urban land expansion on meteorological conditions and ozone (O 3 ) concentrations to be evaluated. Urban expansion increased the temperature at 2 m (T 2 ) and the probability of precipitation in urban expansion areas, and enhanced the surface urban heat island at night. As the expansion areas became progressively larger, the increase in T 2 became more pronounced. The proportions of urban surfaces in June 2016, 2018, and 2020 compared to 2001 increased by 0.69%, 0.83%, and 1.04%, respectively, while T 2 increased by 0.12, 0.19, and 0.20 °C in urban areas, respectively. With urban expansion, the O 3 concentration increased by 1.12, 1.37, and 0.76 μg/m 3 (three-year averages) in urban, suburban, and rural areas, respectively. After coupling a multi-layer urban canopy model (building effect parameterization, BEP), or a multi-layer urban canopy model with a building energy model including anthropogenic heat due to air conditioning (BEP + BEM, abbreviated as BEM simulation), the O 3 concentration changed significantly in the urban expansion area, compared to the results of a single-layer urban canopy model (UCM). O 3 concentrations decreased most in the BEP simulation (-0.77 μg/m 3 ), while O 3 concentrations increased most in the BEM simulation (+1.85 μg/m 3 ). The average observed O 3 concentration was 108.35 μg/m 3 (three-year average), while the simulated value was 75.65-83.72 μg/m 3 (R = 0.69-0.77). The validation results in the BEM and Global Optimal Scenario (GOS) simulations were relatively good, with the GOS simulation producing slightly better results than the BEM. The simulation of O 3 in urban agglomerations could be improved by integrating the results of the UCMs., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Numerous studies have examined the impact of temperature on mortality, yet research on the combined effect of temperature and humidity on non-accidental deaths remains limited. This study investigates the synergistic impact of high temperature and humidity on non-accidental deaths in China, assessing the influence of urban development and urbanization level. Utilizing the distributed lag nonlinear model (DLNM) of quasi-Poisson regression, we analyzed the relationship between Wet Bulb Globe Temperature (WBGT) and non-accidental deaths in 30 Chinese cities from 2010 to 2016, including Guangzhou during 2012-2016. We stratified temperature and humidity across these cities to evaluate the influence of varying humidity levels on deaths under high temperatures. Then, we graded the duration of heat and humidity in these cities to assess the impact of deaths with different durations. Additionally, the cities were categorized based on gross domestic product (GDP), and a vulnerability index was calculated to examine the impact of urban development and urbanization level on non-accidental deaths. Our findings reveal a pronounced synergistic effect of high temperature and humidity on non-accidental deaths, particularly at elevated humidity levels. The synergies of high temperature and humidity are extremely complex. Moreover, the longer the duration of high temperature and humidity, the higher the risk of non-accidental death. Furthermore, areas with higher urbanization exhibited lower relative risks (RR) associated with the synergistic effects of heat and humidity. Consequently, it is imperative to focus on damp-heat related mortality among vulnerable populations in less developed regions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The main component of China's income gap is the urban-rural income gap, which is largely affected by urbanization. It is worth studying how new-type urbanization affects the income gap between urban and rural areas. Research mostly focuses on the urbanization rate as the core explanatory variable to explain the impact using one or two factors. This paper analyzes the mechanism of the effect using a comprehensive number of factors, with the quality of new-type urbanization development as the core explanatory variable. In terms of theoretical research, we believe that new-type urbanization affects the urban-rural income gap by promoting the transfer of labor, changing industrial structure, and policy tendency. Using both static and dynamic empirical analyses, we test the impact of new-type urbanization on the urban-rural income gap based on China's provincial data. We find that new-type urbanization is conducive to narrowing the income gap between urban and rural areas. The transfer of labor significantly reduces the urban-rural income gap. However, the upgrading of industrial structure will enlarge the gap. The impact of China's policy orientation is negligible. Policy should focus on promoting urbanization and improving the marginal rate of return of agriculture, improve the level of human capital, reverse the mismatch between employment structure and industrial structure, increase support for rural areas, and make substantial progress in promoting common prosperity., Competing Interests: NO authors have competing interests., (Copyright: © 2024 Na Zhao. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

During rapid urbanization in developing countries, changes in land use and land cover (LULC) can significantly alter urban land surface temperatures (LST), exacerbating the urban heat island (UHI) effect and degrading the outdoor environment. In this study, taking Guangzhou, China, as an example, we used Landsat series satellite data from 1992 to 2022, classified the LULC of the study area by the Support Vector Machine (SVM) method, estimated the LST of the area by the mono-window algorithm, and classified the LST of the study area into five UHI intensity classes based on the normalized values of the LST, and explored the influence of the LULC on the distribution of the UHI intensity. The CA-ANN (cellular automata-artificial neural network) model in QGIS software was employed to forecast the distribution of LULC and UHI intensity in Guangzhou for 2032. The findings reveal a strong correlation between UHI intensity and LULC, with water bodies and vegetation primarily exhibiting low and sub-low temperatures, while urban areas exhibit sub-high and high temperatures. The prediction results show that, according to the current development trend, compared with 1992, the water body and vegetation cover in 2032 will decrease by 46.97% and 34.24%, the building land will increase by 263.71%, and the sub-high and high temperature areas will increase by 127.76% and 375.92%. By analysing the spatial and temporal changes in LULC and its relationship with the distribution of UHI intensity during urbanization, this study assists government administrations and urban planners in devising sensible urban development strategies and implementing effective measures to plan LULC rationally. This approach aims to mitigate the impacts of the urban heat island and foster sustainable urbanization., Competing Interests: Declaration of competing interest To the best of our knowledge and belief, neither the entire paper nor any part of its content has been published or has been accepted elsewhere. It is not being submitted to any other journal. All authors have seen the manuscript and approved to submit to your journal. The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper, no conflict of interest exists in the submission of this manuscript. Thank you very much for your attention and consideration., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Promoting the formation of the green lifestyle (GL) is a crucial step in achieving comprehensive green transformation of urban economic and social development. The widespread adoption of GL is influenced by various environmental regulations. Previous research mainly focused on the impact of individual policies on GL from the single policy perspective. The mechanisms of the combined effects of policies have not been thoroughly explored, particularly the contributions of each policy during periods of overlap. This paper takes the dual-policy of the New-type Urbanization Policy (NUP) and Smart City Policy (SCP) in China as an example. It employs panel data collected from 271 cities in China during 2007-2019 and establishes a multi-period difference-in-difference model to identify the combined effects of the dual-policy on residents' GL. Additionally, the Shapley value decomposition method is utilized to identify the contribution magnitude of each policy when they act simultaneously. The following conclusions are yielded. Firstly, the combined effects of dual-policy are more effective than a single policy in influencing residents' GL. Secondly, the Shapley value decomposition method reveals that when both policies are simultaneously implemented, SCP contributes a greater weight compared to NUP. Thirdly, the dual-policy can promote residents' adoption of GL through mechanisms such as green technological innovation, public participation in environmental protection, and the agglomeration of tertiary industries. Fourthly, the impact of dual-policy on residents' GL varies across different types and sizes of cities. This study attempts to unseal the "black box" of how the dual-policy influences residents' GL during the green transformation of cities in China, providing theoretical references for relevant urban policies in other countries and contributing to Chinese solutions and experience to global urban green development., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Evaluating the sustainable development level and obstacle factors of small towns is an important guarantee for implementing China's new-type urbanization and rural revitalization strategies, and is also a key path to promoting the United Nations Sustainable Development Goal 11 (SDG11). Traditional evaluation methods (such as Analytic Hierarchy Process, AHP, and Technique for Order Preference by Similarity to Ideal Solution, TOPSIS) mainly calculate the comprehensive score of each indicator through weighting. These methods have limitations in handling multidimensional data and system nonlinearity, and they cannot fully reveal the complex relationships and interactions within the sustainability systems of small towns. In contrast, the evaluation model combining Principal Component Analysis (PCA) and Catastrophe Progression Method (CPM) used in this study can better handle multidimensional data and system nonlinear relationships, reducing subjectivity in evaluation and improving the accuracy and reliability of the assessment results. The specific research process is as follows: First, based on the United Nations SDG11 framework, using multi-source big data, a theoretical framework and evaluation index system for the sustainable development of small towns suitable for the Chinese context were established. The impact of county-level factors on the sustainable development of small towns was also considered, and an entropy weight-grey correlation model was used to measure these impacts, resulting in a town-level dataset incorporating county-level influences. Secondly, the sustainability levels of 782 top small towns in China were evaluated using the comprehensive evaluation model based on PCA-CPM Model. Finally, an improved diagnostic model was used to identify obstacles influencing the sustainable development of small towns. The main findings include: 52.69% of the small towns have a sustainable development score exceeding 0.7255, indicating that the overall performance of small towns is at a medium to high development level. The development of small towns exhibits significant differences across regions and types, which are closely linked to county-level effects. Economic and social factors are the main obstacles to the sustainable development of small towns, and the impact of these obstacles intensifies from the eastern to the central, western, and northeastern regions. This study provides valuable insights for policymakers and scholars, promoting a deeper understanding of the sustainable development of small towns., Competing Interests: Declaration of competing interest The authors declare that there is no conflict of interest regarding the publication of this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

The continuous expansion of modern cities not only leads to ecological degradation but also seriously threatens regional ecological security and sustainable development. The construction of ecological security patterns (ESPs) has emerged as a significant approach to alleviate or even solve the conflict between regional development and ecological protection. The Chengdu-Chongqing Economic Circle (CCEC) represents the core area of regional economic development strategy in western China, characterized by rapid economic growth from 2000 to 2020. This study integrates assessments of ecosystem services importance, eco-environmental sensitivity and landscape connectivity; uses circuit theory and hydrological analysis to establish a research framework for the spatiotemporal evolution of regional ESP; and develops an optimized ESP combined with the Major Function Oriented Zone. The results indicate that urban expansion significantly impacted the ESP of the CCEC between 2000 and 2020. The fragmentation and merging of ecological sources occurred simultaneously, the number of patches reduced by 28.13% from 64 to 46. The early ecological security network was compromised, leading to the disappearance or elongation of some ecological corridors. The number of ecological corridors decreased by 36.03% from 136 to 87; the total length was reduced by 29.92% from 7500.57 km to 5256.28 km. Urgent optimization of the ESP is needed, reducing the number of key ecological protection areas by 50% from 106 to 53 while increasing priority restoration areas by 13.51% from 37 to 42. The study also reveals the insufficiency of the current Major Function Oriented Zone in protecting linear corridors, necessitating focused attention on the protection and restoration of ecological sources and surrounding corridors in important development zones. Additionally, a spatial optimization strategy of "one shelter, two cores, and three regions" is proposed to enhance regional ecosystem stability and connectivity. The aim was to strike a balance between ecological protection and food security by recommending an ecological corridor width range of 30∼100 m. These research findings offer scientific guidance for ecological space protection and restoration in the CCEC, contributing to the enhancement of both scientific and rational ecological planning in rapidly urbanizing areas., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

China's new urbanization strategy serves as a key instrument for achieving sustainable development goals in urban areas. However, a consensus on how and whether new urbanization affects urban green total factor productivity (GTFP) has yet to be reached. This analysis targets 276 prefecture-level and above cities, using panel data from 2011 to 2019 to assess the impact of the new urbanization pilot policy (NUPP) on GTFP. The research findings demonstrate that implementing China's NUPP has significantly enhanced urban GTFP. Furthermore, the population-land-industry coupling coordination degree (PLICCD), as well as the industry-environment-economy coupling coordination degree (IEECCD), play crucial facilitating roles in the aforementioned enhancement effects. The results remain robust even after employing PSM-staggered difference-in-differences (DID) estimation and excluding other policy interferences. Furthermore, heterogeneity analysis, based on urban characteristics, reveals that the NUPP significantly enhances GTFP in resource-based, non-resource-based, industrial, non-intensive compactness, and non-expansionary urbanization cities. Finally, the paper offers three policy recommendations. First, new urbanization initiatives should be more actively promoted in China and other developing countries. Second, the construction of new urbanization plans should focus on the coordinated development of "population-land-industry" and "industry-environment-economy." Third, the government should implement new urbanization initiatives tailored to the specific characteristics of different cities. This study provides valuable insights for the general public, policymakers, and scholars to better understand the potential of coordinating the development of population, land, industry, the environment, and the economy to improve GTFP. Moreover, it offers a broad perspective for evaluating sustainable urban development., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Implementing a Carbon Peak Action Plan at the regional level requires comprehensive consideration of the developmental heterogeneity among different provinces, which is an effective pathway for China to realize the goal of carbon peak by 2030. However, there is currently no clear provincial roadmap for carbon peak, and existing studies on carbon peak pathways inadequately address provincial heterogeneity. Therefore, this paper employs the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model to decompose assess 8 factors influencing carbon emissions of 30 provinces. According to scenario analysis, the paper explores the differentiated pathways for provincial carbon peaks based on policy expectation indicators (including population, economy, and urbanization rate) and comprises policy control indicators (including the energy structure, energy efficiency, industrial structure, transportation structure, and innovation input). The results indicate that population, per capita GDP, urbanization rate, and innovation input are the primary factors for influencing (negatively) the growth of carbon emissions. In contrast, the optimization and upgrading of the industrial structure, energy intensity, energy structure, and transportation structure have mitigating effects on carbon emissions, especially for the first two factors. The forecasting results reveal that robust regulations of the energy and industry can effectively accelerate carbon peak at a reduced magnitude. If developed at BAU, China cannot achieve carbon peak by 2030, continuing an upward trend. However, by maximizing the adjustment strength of energy and industrial transformation within the scope of provincial capabilities, China could achieve carbon peak as early as 2025, with a peak of 12.069 billion tons. In this scenario, 24 provinces could achieve carbon peak before 2030. Overall, this study suggests the feasibility of differentiated pathway to achieve carbon peaks in China, exploring the carbon peak potential and paths of 30 provinces, and identifying provinces where carbon peak is more challenging. It also provides a reference for the design of carbon peak roadmaps at both provincial and national levels and offers targeted recommendations for the implementation of differentiated policy strategies for the government., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Based on the endogenous growth theory, this paper uses the Gini coefficient to measure educational inequality and studies the empirical relationship between educational inequality and income inequality through a simultaneous equation model. The results show that: (1) Income inequality leads to educational inequality while the reduction of educational equality does not contribute to the decrease of income inequality, and there is no simple casual effect between them. However education expansion is beneficial to reduce educational inequality and income inequality. (2) Education relates to income inequality through the human capital transmission mechanism, but this mechanism does not automatically translate into a virtuous cycle of "educational equality[double arrow]income equality". (3) In the long run, the reduction of educational inequality does not reduce income inequality, but income inequality has a negative instant-impact on educational equality. (4) At present, the level of educational investment and urbanization do not effectively promote educational equality. In addition, the robustness of the model used in this paper has been partly proved.