Level Of Agglomeration Research Articles

Digital finance, capital-biased and labor-biased technical progress: Important grips for mitigating carbon emission inequality

As an innovative financial model in the era of the digital economy, digital finance, with its inclusive characteristics, provides effective financial support for the realization of the carbon peak and carbon neutrality. To realize the “double carbon” goal, it is necessary not only to control the total amount and intensity of carbon emissions but also to consider the coordination and fairness of carbon emission reduction between regions. The existing literature has discussed the carbon reduction effect of digital finance, but few studies have focused on the impact and mechanism of digital finance on regional carbon emission inequality. On the basis of data from 287 prefecture-level cities in China from 2011 to 2021, this paper empirically examines the effect of digital finance on carbon emission inequality via a fixed effects model and convergence model. Digital finance not only reduces the Theil index of carbon emissions but also promotes the convergence of carbon emissions, which mitigates regional carbon emission inequality. The mechanism test shows that digital finance reduces the level of regional carbon emission inequality by promoting capital- and labor-biased technical progress in high-carbon emission regions. Heterogeneity analysis proves that digital finance can better exert its inhibitory effect on carbon emission inequality in regions with low financial agglomeration levels, weak industrial bases and small digital business scales. Further analysis indicates that digital finance can effectively reduce carbon emission inequality between regions, but the effect on carbon emission inequality within regions is not significant. The above findings provide a realistic reference for the formulation of differentiated digital finance policies to support carbon emission reduction.

Quantitative attribution of industrial agglomeration patterns in Africa: global, local drivers and indirect effects

ABSTRACT Finding appropriate measures to drive industrial agglomeration is particularly urgent for Africa, which has been facing a decline in industrial production activities. Therefore, this study contributed by developing a multi-level spatial analysis framework that explored the global driving mechanisms and local heterogeneity of industrial agglomeration in Africa through various critical factors. The findings are as follows: (1) From 2009 to 2019, the industry in Africa has always been highly concentrated in a few countries, but the degree of agglomeration has been declining, with some countries in the East and West African regions showing a significant increase in the level of industrial agglomeration and a high potential for development. (2) Industrial agglomeration in African countries was driven by several factors, of which GDP per capita, highway network density, and electricity supply were the strongest and most consistent drivers. The impact strength of factors varied considerably across regions. (3) The drivers didn’t act independently and directly on the dependent variable, but were the product of synergy after the interaction between the two factors. Synergies between access to electricity and GDP per capita and other factors dominated the pattern of industrial agglomeration in Africa.

Digital industry agglomeration and urban innovation: Evidence from China

This study explores the relationship between digital economy and urban innovation from the perspective of economic agglomeration. Based on a panel data set of 285 Chinese cities from 2009 to 2019 and the classification of the digital industry by the National Bureau of Statistics, this study shows that an increased level of digital industry agglomeration significantly contributes to urban innovation, with more pronounced effects observed in larger cities and those in eastern and western regions. Further analysis of industry heterogeneity reveals that digital industry agglomeration not only boosts innovation within the digital industry but also enhances it in non-digital industries. Additionally, digital industry agglomeration appears more conducive to promoting innovation in green technology industries than in non-green technology industries. The mechanism analysis reveals the mediating effect of data capital accumulation, market size expansion, and digital technology spillover on urban innovation. The Sobel test reveals that data capital accumulation has the largest mediating effect on total patents, while digital technology spillover has the strongest mediating effect on invention patents. This study enriches the existing understanding of the agglomeration effect of the digital industry on urban innovation and sheds light on the mechanisms driving urban innovation in emerging economies.

Policy, innovation, market or behavior driven effects: energy green transition and environmental management in Chinese heterogeneous cities

Energy green transition (EGT) is currently one of the main measures for countries around the world to address the contradiction between economic growth and increasingly deteriorating environmental and climate issues. Cities are the center of energy consumption. The key to EGT lies in urban energy green transition. Therefore, the focus of this study is on the driving mechanism of urban EGT. Firstly, the spatial-temporal characteristic of EGT in Chinese heterogeneous cities is analyzed by using methods such as gravity model. Secondly, the possible paths includes policy driven, innovation driven, market driven, and behavior driven for urban EGT are discussed through theoretical analysis. Finally, combined with panel data of 236 Chinese cities in 2007-2022, this study empirically analyzes the complex driving mechanism of urban EGT. Results show that: (1) The EGT in Chinese cities is continuing. From the perspective of urban heterogeneous, EGT in 1-tier and 2-tier cities is significantly faster than that in 3-, 4-, and 5-tier cities. The EGT speed in eastern cities is the fastest, while that in northeastern cities is the slowest. The difficulty of EGT in energy resource-based cities is actually the greatest. From the perspective of spatial features, the spatial center of EGT in Chinese cities generally shows a changing trend from northwest to southeast. (2) Policy driven, innovation driven, market driven, and behavior driven constitute the complex driving mechanism of urban EGT, and policy driven is the primary driving force for this round of EGT. (3) Positive effect of economic development level and education level improvement on EGT in Chinese cities is significant while resource endowment and population agglomeration level exhibit significant inhibitory effects. (4) There are significant differences in the core driving force for EGT in heterogeneous cities. Both policy driven effect and market driven effect have the highest impact in 1- and 2-tier cities. Innovation driven effect, market driven effect, and behavior driven effect are only significant in eastern and central cities. In energy resource-based cities, innovation driven effect of green innovation is not significant. This study can assist government departments better in formulating relevant policies to support energy transition, promote technological innovation, design market mechanisms, and guide energy consumption behavior.

High-resolution modeling and projection of heat-related mortality in Germany under climate change

Abstract Heat is a leading cause of premature deaths during summer months. Understanding the relationship between high temperatures and excess mortality is crucial for designing effective prevention and adaptation plans. Traditional statistical methods have been repeatedly applied to analyze heat-related mortality. However, spatially and temporally high-resolution analyses are challenging due to fragmented data archives across different agglomeration levels, especially for mortality data. We propose a neural network-based model to estimate heat-related mortality. This approach allows for high temporal and spatial resolution estimations, such as regional heat risk during specific heatwaves. Using Germany as a case study, we calculated heat-related excess mortality rates at the district level and visualized the dynamics of local health risks within a heatwave. Overall, we estimated a total of 48,000 heat-related deaths in Germany over the last decade (2014-2023), with most occurring during specific heatwave events. For example, in 2023, the heatwave from July 7-14 contributed approximately 28% (1100 deaths) to the total of about 3,900 heat-related deaths for the entire year. This estimation is consistent with previously published reports from the Robert Koch Institute (RKI), considering the resolution differences in the input data. In addition, we combined our model with shared socio-economic pathways (SSPs) of future climate change, assuming a static population and baseline mortality rate. The results suggest that heat-related risk in Germany could further increase by a factor of 2.5 (SSP245) to 9 (SSP370) without adaptation to extreme heat. Our approach is a valuable tool for the monitoring of regional heat-related risks as well as scenario-based risks projections for the future. The results of the model can help develop climate-driven public health strategies, aiding in the identification of local risks during heatwaves and in long-term resilience planning. Key messages • High-resolution modeling of heat-related mortality helps us to develop targeted adaptation and prevention plans. • The majority of heat-related mortality occurs during heatwaves in summer.

High-resolution modeling and projection of heat-related mortality in Germany under climate change.

Heat has become a leading cause of preventable deaths during summer. Understanding the link between high temperatures and excess mortality is crucial for designing effective prevention and adaptation plans. Yet, data analyses are challenging due to often fragmented data archives over different agglomeration levels. Using Germany as a case study, we develop a multi-scale machine learning model to estimate heat-related mortality with variable temporal and spatial resolution. This approach allows us to estimate heat-related mortality at different scales, such as regional heat risk during a specific heatwave, annual and nationwide heat risk, or future heat risk under climate changescenarios. We estimate a total of 48,000 heat-related deaths in Germany during the last decade (2014-2023), and the majority of heat-related deaths occur during specific heatwave events. Aggregating our results over larger regions, we reach good agreement with previously published reports from Robert Koch Institute (RKI). In 2023, the heatwave of July 7-14 contributes approximately 1100 cases (28%) to a total of approximately 3900 heat-related deaths for the whole year. Combining our model with shared socio-economic pathways (SSPs) of future climate change provides evidence that heat-related mortality in Germany could further increase by a factor of 2.5 (SSP245) to 9 (SSP370) without adaptation to extreme heat under static sociodemographic developments assumptions. Our approach is a valuable tool for climate-driven public health strategies, aiding in the identification of local risks during heatwaves and long-term resilience planning.

Integrating Resilience Theory Into a Cultivated Land System: Empirical Insights From China's Key Grain‐Producing Regions

ABSTRACTExploring cultivated land use and conservation from a resilience perspective is crucial to address regional food security concerns. This article first examines the theoretical applicability of resilience in the context of cultivated land use systems and subsequently introduces a specific concept of cultivated land system resilience (CLSR). Focusing on the middle reaches of the Yangtze River, a major grain‐producing area in China, the study constructs a measurement system that encompasses five dimensions: endowment of production, socioeconomic factors, scale structure, ecological pressure, and food security. This system is used to evaluate the spatio‐temporal evolution and influencing mechanisms of CLSR in the region from 2001 to 2020. The results indicate that the level of CLSR increased by 7.2% overall and exhibits a distinct spatial pattern, with high‐value areas expanding from the center to the surrounding regions. Furthermore, CLSR shows a positive spatial correlation with rising levels of agglomeration. The spatial heterogeneity of CLSR is influenced by the interaction of various factors, resulting in a partially nonlinear two‐factor enhancement. The influence of each factor varies between different time periods, shifting from ecological pressure to scale structure, ultimately affecting food security. Thus, the resilience perspective offers greater explanatory power to identify key vulnerabilities in the regional cropland system. This approach can improve the efficient allocation of cropland resources and promote sustainable and healthy development at the regional level.

Electrospun polyvinyl alcohol nanofiber scaffolds incorporated strontium-substituted hydroxyapatite from sand lobster shells: synthesis, characterization, and in vitro biological properties

The paper describes the synthesis of hydroxyapatite (HAp) and strontium-substituted hydroxyapatite (SrHAp) from sand lobster shells by a hydrothermal method. The HAp and SrHAp were incorporated into the polyvinyl alcohol (PVA) nanofiber scaffold through the eletrospinning method. The scaffolds were incorporated with 5wt% of hydroxyapatite (HAp), 5wt%, 10wt%, and 15% of SrHAp. The physicochemical, mechanical, and in vitro biological properties of the scaffold were evaluated. The incorporation of HAp or SrHAp was evidenced by the diffraction patterns and the phosphate functional groups related to HAp. The morphological results showed the decrement of fiber diameter in line with the increased SrHAp concentration. A tensile test was conducted to investigate the mechanical properties of the scaffolds, and the results showed that the scaffolds perform poorly at a higher SrHAp concentration because of exceeding agglomeration levels. The PVA/SrHAp15 performed the best antibacterial activity against E. coli and S. aureus with an inhibition zone of (15.2 ± 0.2) and (14.5 ± 0.8), respectively. The apatite formation was more abundant in PVA/SrHAp10 after immersion in a simulated body fluid (SBF). Cell viability results showed that the scaffold enabled the osteoblast cells to grow and proliferate. The biocompatibility of HAp and SrHAp resulted in the enhancement of cell adhesion. Based on all tests, the PVA/SrHAp 10 scaffold shows a strong candidate for further in vivo studies.

Issues of Agglomeration Identity Policy in Statements of Russian Regional Politicians: Discourse Analysis of the Social Network “Vkontakte” Materials

The article examines how issues of identity construction in Russian urban agglomerations are reflected in the Russian regional politicians’ discourse in mass media. The study concerns theoretical problems of identity construction and the role of regional government bodies in shaping the territorial identity of the population. The specificity of the Russian situation is the absence of governing bodies related to the agglomeration level in most urban agglomerations. The empirical basis of the study is the texts of subnational politicians posted on the official websites of regional government bodies: websites of governors and regional governments, official pages in the mass media. The empirical information on identity policy were collected from the Internet sources (official portals of regional executive authorities, media reports). Discourse analysis was carried out after monitoring social media materials (VKontakte web-pages of regional leaders). The article reflects five cases out of sixteen Russian ones related to the Ural and Siberian agglomerations with a megalopolis core. The empirical data cover the period from December 2022 to the end of 2023. The choice of the time period for analysis is determined by the fact that by this period the most significant factors influencing the policy of our state at present (the pandemic and the Special military operation) have already manifested themselves in full. It has been confirmed that the problems of agglomeration development in the public official subfederal discourse in most cases are reduced to economic problems; first of all, it concerns the development of industry, science (high technology), transport, and waste disposal. In all analyzed cases, insufficient attention was found out, paid to the role of the implemented socio-cultural projects of subfederal identity policy, and also distancing from the discussion of the problems of integration of labor migrants in the public space. Insignificant number of messages from representatives of the regional political and administrative elite about the socio-cultural meanings of the formed agglomerations can become a significant limitation of information support for the agglomeration development of modern contemporary Russia.

Investigating the determinants of marine environmental degradation in Africa: What roles can economy, population, capture and energy play?

This study firstly examines the quality of marine eco-environment in Africa using Tapio decoupling model, and analyzes the sustainability level of the development of “population agglomeration - marine environment - economic growth”. Secondly, a series of econometric tools, such as ARDL, FMOLS, AMG model and DH panel causality test, are used to investigate the long- and short-term impacts of economic growth, population agglomeration, marine capture and energy consumption on the African marine eco-environment, and to analyze the differences between the sub-regions in Africa. The results indicate that: Adebayo and Kirikkaleli (2021) (Adebayo and Kirikkaleli, 2021) the decoupling state of “population-environment” has shifted from expansive negative decoupling to more optimized strong decoupling, and “economy-environment” has gradually changed from strong negative decoupling and expansive negative decoupling to strong decoupling. Ali et al. (2017) (Ali et al., 2017) There existed a bi-directional causal relationship between the degree of marine environment degradation and economic growth, population agglomeration, marine capture and energy consumption. Al-Mulali and Sab (2012) (Al-Mulali and Sab, 2012) In the short term, the economic EKC hypothesis does not hold in North and West Africa, while Central, East and Southern Africa are consistent with the EKC hypothesis. In the long term, the EKC hypothesis is valid in Central, East and Southern Africa, while is not valid in North and West Africa. Overall, reducing population agglomeration levels, marine fishing and energy consumption might mitigate marine environmental degradation in Africa.

Nonlinear impact of automobile industry agglomeration on CO2 emission: Incorporating urban characteristics in China

Despite the increasing economic benefits generated by the cluster effect of the automotive industry, CO2 emissions have become a serious challenge in the “3060” dual-carbon context. There are significant uncertainties regarding the impact of automotive industry agglomeration on urban CO2 emissions, including quantifying impact thresholds and understanding the sensitivity of different agglomeration patterns. This study explores how automotive industry agglomeration impacts CO2 emissions across 278 Chinese cities, and uncover the impact patterns based on varying city characteristics. The results show that the technology agglomeration of the automobile industry exhibits a nonlinear “U-shaped” impact on CO2 emissions with a threshold value of 0.4267, while the scale agglomeration shows a nonlinear inverted “U-shaped” impact with a threshold value of 0.1206. In low-carbon demonstration cities, technology agglomeration has the most significant impact, with fluctuations ranging from −14.65% to 16.12%. In contrast, transitional cities are most affected by scale agglomeration, with a fluctuation range of −18.1%–11.19%. Besides, the results indicate that China's automobile industry development programs tend to relocate economic activities from highly agglomerated low-carbon demonstration cities to potential development cities with lower levels of agglomeration and other transitioning cities. Lastly, the results reconfirm that developing automotive industry development models based on cities' characteristics can enhance the environmental benefits of industrial agglomeration.

Re-Examination of the Relationship between Industrial Agglomeration and Haze Pollution: From the Perspective of the Spatial Moderating Effect of Environmental Regulation

This paper uses panel data from 284 Chinese cities from 2004 to 2020 and employs a dynamic spatial panel Durbin model to re-examine the relationship between industrial agglomeration, environmental regulation, and haze pollution. It further adopts a dynamic spatial moderation effect model to explore the spatial regulatory mechanism of environmental regulation. The results show that both local and neighboring industrial agglomeration have a significant “inverted U-shaped” relationship with local haze pollution, and the scale cumulative optimization effect can only be effectively played after the industrial agglomeration level of the locality and neighboring areas exceeds the inflection point. Local environmental regulation significantly inhibits haze pollution, while neighboring environmental regulation plays a promoting role. The moderating effect of environmental regulation on the relationship between industrial agglomeration and haze pollution shows spatial heterogeneity in the local and neighboring areas. Local environmental regulation has a “U-shaped” non-linear moderating effect while neighboring environmental regulation has a positive linear moderating effect. Therefore, the government should pay attention to the joint effort and coordinated advancement of industrial agglomeration and environmental regulation to further reduce urban haze pollution and enhance urban air quality.

Spatiotemporal evolution and influencing factors of urban resilience in the Yellow River Basin, China

The Yellow River Basin of China is a key region that contains myriad interactions between human activities and natural environment. Industrialization and urbanization promote social-economic development, but they also have generated a series of environmental and ecological issues in this basin. Previous researches have evaluated urban resilience at the national, regional, urban agglomeration, city, and prefecture levels, but not at the watershed level. To address this research gap and elevate the Yellow River Basin’s urban resilience level, we constructed an urban resilience evaluation index system from five dimensions: industrial resilience, social resilience, environmental resilience, technological resilience, and organizational resilience. The entropy weight method was used to comprehensively evaluate urban resilience in the Yellow River Basin. The exploratory spatial data analysis method was employed to study the spatiotemporal differences in urban resilience in the Yellow River Basin in 2010, 2015, and 2020. Furthermore, the grey correlation analysis method was utilized to explore the influencing factors of these differences. The results of this study are as follows: (1) the overall level of urban resilience in the Yellow River Basin was relatively low but showed an increasing trend during 2010–2015, and significant spatial distribution differences were observed, with a higher resilience level in the eastern region and a low-medium resilience level in the western region; (2) the differences in urban resilience were noticeable, with industrial resilience and social resilience being relatively highly developed, whereas organizational resilience and environmental resilience were relatively weak; and (3) the correlation ranking of resilience influencing factors was as follows: science and technology level>administrative power>openness>market forces. This research can provide a basis for improving the resilience level of cities in the Yellow River Basin and contribute to the high-quality development of the region.

New urbanization construction and city economic resilience-based on multi-period DID tests for 278 cities

As a key measure to realize Chinese-style modernization, the construction of new urbanization injects new vitality into China ‘s urban economic growth by building a modern industrial system, and it is also of great significance to improve urban economic resilience. This study examines data from 278 Chinese cities spanning the period 2006–2022, utilizing a multi-period Difference-in-Differences model and a moderating effect model to investigate the impact of new urbanization on cities' economic resilience. The findings indicate that the adoption of modern urbanization significantly enhances cities' economic resilience. Notably, when examined from the perspectives of geographical location, urban scale, urban agglomeration, and urban economic development level, the impact of new urbanization is particularly pronounced in the eastern region, small cities, non-urban agglomeration cities, and cities with lower levels of economic development. The mechanism test demonstrates that new urbanization affects cities’ economic resilience by fostering technological innovation and upgrading the industrial structure. Essentially, technological innovation and industrial restructuring serve as intermediaries in fortifying economic resilience through the implementation of new urbanization. As a result, recommendations are formulated to bolster the resilience of urban economies.

Coupling synergy level and interaction effect between the ecological environment and low-carbon development in the Yangtze River Delta urban agglomeration: Characteristics of spatial and temporal heterogeneity

Low-carbon development and the ecological environment are often assessed separately, but understanding their interaction effect and the coupled coordination development from a spatially heterogeneous perspective remains limited, particularly in the context of rapidly urbanizing urban agglomeration regions. To address this research gap, this study assessed the levels and variations in coupled coordinated development between low-carbon development and the ecological environment at the urban agglomeration level using a coupled coordination degree model. Key factors of the interaction effect for each system were initially identified by ordinary least squares, then a geographically and temporally weighted regression model was used to reveal the spatial and temporal heterogeneity of these factors. Our study showed that the comprehensive development level of low-carbon development system in all cities exceeded that of the ecological environment system from 2006 to 2021. However, the level of synergy between the two systems showed slight improvement, with most cities exhibiting a moderate balance from 2010 to 2020. Regional heterogeneity was apparent in the coordinated development types, with highly balanced cities located primarily in the west and north of the urban agglomeration. Furthermore, our findings illustrated the positive effect of the air and climate environment on low-carbon development, contrasted with the negative influence of the land environment. These results not only enrich our understanding of low-carbon development and ecological environment interrelations in the Yangtze River Delta urban agglomeration but also provide insights applicable to similar regions worldwide, thereby contributing to the global discourse on synergistic sustainable development of low-carbon and ecological environment.

Impact of Industrial Intelligence on China’s Urban Land Green Utilization Efficiency

Against the backdrop of the fourth technological revolution, industrial intelligence (INDI) represented by industrial robots has rapidly developed. This evolution provides favorable opportunities for precise decision-making in pollution control and achieving China’s “dual carbon” goals. Previous studies have mainly discussed the economic effects of INDI from the perspective of the labor market. This study shifts its focus to examining the impact of INDI on the land green utilization efficiency (LGUE) in cities. Using the panel data of Chinese cities spanning 2009–2021, this study empirically tests the effect and transmission mechanism of INDI on LGUE. We find that urban INDI significantly enhances LGUE. In terms of its transmission mechanism, INDI drives improvements in urban LGUE through technological progress, energy structure optimization, and industrial structure upgrading. Urban infrastructure construction and financial agglomeration level can further strengthen the positive impact of INDI on LGUE. In addition, the improvement in LGUE due to INDI is more significant in non-resource-based and large-sized cities than resource-based and small and medium-sized cities. Therefore, each region should enhance the integration of intelligent technology with traditional industrial manufacturing. Doing so is essential to establish comprehensive assessment indicators that balance environmental protection and economic growth, strengthen regional information infrastructure construction, ensure steady financial flow, and support green development initiatives across regions.

Investigation and Characterization of Interfacial Transport Phenomena in the Catalyst Layer Using Rheo-Impedance Measurement

Electrodes or catalyst layers (CLs) are the heart of fuel cell and electrolyzer cell devices. They are mainly heterogeneous porous electrodes composed of catalyst particles, ion-conducting polymer material, and void spaces that make up the triple-phase boundary (TPB). It is important to tailor the CL’s microstructure such that there are abundant TPBs where reactions take place to maximize catalyst utilization and improve cell performance. However, this is a critical challenge due to lack of fundamental understanding of the interfacial transport within the CL. Understanding how catalyst ink parameters affect ink properties and how ink components interact, and ultimately, their relationship with CL microstructure formation and cell performance, are essential to designing electrodes. Electrode morphology is important and is controlled by the ionomer/catalyst interactions formed in precursor inks that evolve during mixing and electrode fabrication.In this study, we probe interactions in catalyst inks with different formulations (ionomer-to-carbon ratio and IPA/water) using a new experimental method to unravel the complexities of ionomer/catalyst particle interactions. The new experimental method is a combination of rheological and electrical impedance spectroscopy measurements (rheo-EIS) that takes advantage of the dynamic nature of catalyst ink and the fact that the rheological and electrical behaviors of the ink are coupled to the microstructure of the material. Using rheo-EIS tool, in combination with zeta (ζ) potential and dynamic light scattering (DLS) measurements, we were able to systematically study how the level of agglomeration of the inks and microstructures evolve with respect to different I/C ratios, solvent formulation, and external shear forces. Results from the three-phase rebuilt test designed to simulate the ink coating condition with single-frequency EIS measurement give information on how the ionomer/catalyst particle interactions form and recover during the coating process. In addition, the full frequency range EIS measurements provide complementary data of the ionic and electrical resistance of the ink before and after high shear applications. Furthermore, the observations of the effect of I/C and IPA/water ratios from this study provide insights on how to better engineer suitable catalyst inks and how to control specific CL microstructure without the need for time-consuming optimization and empirical studies.

Does enterprises agglomeration lead to increased pollution emissions? Evidence from Chinese microdata

Enterprise agglomeration provides significant economic benefits but also carries substantial environmental impacts. Using the China Industrial Enterprise Database, this research develops novel metrics to comprehensively quantify specialization and diversity within enterprise agglomeration patterns in the Chinese industry from 1998 to 2012. Meanwhile, this study also theoretically links levels of enterprise agglomeration to pollution levels by extending established models and testing these relationships empirically with emissions data from the period. The study finds that enterprise agglomeration has a "U-shaped" relationship with environmental pollution that is modified by factors like fossil fuel intensity and strength of environmental regulations. The conclusions suggest priorities for sustainable development include optimizing degrees of enterprise agglomeration and promoting energy efficiency and stricter standards to support long-term compatibility between economic clustering through enterprise agglomeration and environmental performance goals.

Simulation and evaluation of ecosystem service value along the Yellow River in Henan Province, China

The unprecedented growth in population and swift industrial advancements exert considerable strains on the ecosystem, particularly within medium-sized and large urban landscapes. The critical investigation into the intricate links between current and prospective land utilization, as well as the ecosystem service value (ESV), holds considerable empirical relevance for the calibration of land usage frameworks, thereby contributing to the sustainable evolution of extensive urban zones. Utilizing GlobeLand 30 data, the present research probes into the pattern of land transformation and the spatial-temporal dispersal of ESV in Henan’s Yellow River vicinity over a span from 2000 to 2020. For the enhancement of land usage alignment, a Markov-PLUS fusion model was devised to gauge three disparate ESV transition scenarios slated for 2030, namely, natural development scenario (NDS), cropland protection scenario (CPS), and ecological protection scenario (EPS). The principal determinants of land transformation within the 2000–2020 period were recognized as elevation, populace concentration, and atmospheric temperature. Amid the rapid accretion of construction land engulfing substantial cropland and grassland areas, there was an ESV diminution to the tune of 1.432 billion RMB between 2000 and 2020. The ESV’s high-value regions were discerned within relatively undisturbed ecosystem zones, with the lower-value sections identified in cropland and constructed areas, where human interventions exerted pronounced effects on the ecosystem. In accordance with the 2030 land usage simulations and analyses, in contrast to alternative scenarios, the EPS exhibited the least fluctuation in land type alterations in 2030, demonstrated the most pronounced escalation in cold spot concentration, and reached a peak agglomeration level. This underscores that the EPS not only offers a refinement in land utilization configuration but also mediates the equilibrium between economic and ecological considerations. The insights derived from this investigation afford innovative evaluative methods for spatial planning, ecological recompense, and sustainable land exploitation within large- and medium-scale urban domains.

Talent agglomeration research within digital economy development: Trend analysis and research prospects

Talent is important for development and innovation across fields. Further, in this era of digital economy, primarily driven by modern information networks, how to attract talent and effectively leverage talent’s agglomeration effect is a crucial research topic. Thus, this paper reviewed studies from the China Knowledge Network in the Chinese Social Sciences Citation Index and from the Web of Science Core Collection. By combining cluster analysis based on keyword co-occurrence with a review of highly relevant literature, this paper determines and compares mainstream directions in both domestic Chinese and international studies on talent agglomeration effects and digital economy talent research, thereby constructing a two-dimensional analytical framework. This paper recommends four research paths for the effects of talent agglomeration, namely, talent management, enterprise–industry development, industry–regional development, and industry–regional level of talent agglomeration. Meanwhile, considering the digital economy’s key role in future national economic strategies, its human resources studies should be included in these same paths for studying talent aggregation effects. Introducing public sector strategic manement theories into research on digital-economic talent aggregation could prove an extremely valuable subject matter in the future.