Intra-regional Differences Research Articles

Spatial and temporal analysis of China's healthcare resource allocation measurements based on provincial data: 2010-2021.

With the development of society, industrialization, urbanization, aging, lifestyle and social transformation, environmental degradation, global warming and other factors have had a great impact on the health of the population, and there is an urgent need to take a series of practical actions to promote the improvement of national health. Among them, healthcare resource allocation plays a key role in advancing the level of national health, treatment of chronic diseases, and leisure and healthcare. This article collected panel data on healthcare resource allocation in all provinces of China from 2010 to 2021, and comprehensively applied Analytic Hierarchy Process, comprehensive scoring method, regional difference analysis and spatial autocorrelation analysis to reveal regional differences, spatial-temporal patterns and development characteristics of healthcare resource allocation in China. In terms of regional differences, intra-regional differences in healthcare resource allocation tend to narrow and inter-regional differences tend to widen. In terms of spatial pattern, the western provinces on the left side of the Hu Huanyong line generally have higher scores, while the central and eastern provinces on the right side of the Hu Huanyong line have lower scores, and healthcare resource allocation in the provinces on the left side of the Hu Huanyong line, such as Tibet, Xinjiang, Qinghai, Ningxia, Gansu, Inner Mongolia, Sichuan, have the spatial characteristics of HH clusters in terms of geographic location, while the southeast coastal provinces, such as Zhejiang, Fujian, Guangdong, Hainan, have the spatial characteristics of LL clusters in terms of geographic location. From the quadrant analysis, the 2010-2021 healthcare resource allocation in the first quadrant concentrates most of the provinces in the western and northeastern regions, while the third quadrant concentrates most of the provinces in the eastern region. The allocation of healthcare resources in China's four major zones has undergone a process of change from "unbalanced quantity to relatively balanced quantity," but high-quality healthcare resources are highly concentrated in the eastern part of the country, and the problem of contradiction between people and doctors is prominent. It is recommended that Internet plus healthcare technology be used to reshape the regional allocation of high-quality healthcare resources.

Main results of permafrost monitoring in the French Alps through the PermaFrance network over the period 2010–2022

AbstractThis study presents data from the first years of permafrost monitoring in boreholes in the French Alps that started at the end of 2009 in the framework of the PermaFrance network. Nine boreholes are instrumented, among which six monitored permafrost temperature and active layer thickness (ALT) over >10 years. Ice‐poor and cold permafrost in high‐elevation north‐facing rock walls has warmed by up to >1°C at 10 m depth over the reference decade (2011–2020), whereas ice‐rich permafrost (rock glacier) temperatures remained stable. ALT has increased at four of the five boreholes for which decadal data are available. Summer 2015 marks a turning point in ALT regime and greatest ALT values were observed in 2022 (available for six boreholes), but thawing intensity did not show an obvious change. At one site with a layer of coarse blocks about 2 m thick, ALT was stable over 2018–2022 and response to the hottest years was dampened. Linear trends suggest an ALT increase of 2 m per decade for some ice‐poor rock walls, independently of their thermal state. The data reveal a variety of permafrost patterns and evolution with significant intraregional and local differences. Snow modulates the response to air temperature signal in various ways, with an important effect on near‐surface temperature trends and ALT: early snow melting in spring favors an ALT increase in rock walls. Maintaining these monitoring systems and understanding the physical processes controlling heterogeneous responses to climate signals is crucial to better assess permafrost dynamics and to adapt to its consequences.

Spatial differentiation of carbon emissions reduction potential for construction and demolition waste recycling.

Identifying the regional differences and drivers for carbon reduction of construction and demolition waste (C&DW) recycling is essential to combat climate change. This study aims to calculate the carbon reduction potential for C&DW recycling from 2006 to 2021 in China and investigates the spatial differences and driving factors of carbon reduction potential for C&DW waste by combining the Theil index, Gini coefficient, and geographic detector methods. The carbon reduction potential for C&DW recycling in China was "high in the east and low in the west" overall level, with an average annual growth rate of 6.27%. The overall differences in carbon reduction potential for C&DW recycling are decreasing, mainly due to intraregional differences and inter-provincial differences in Northeast China. The population size, urbanization rate, and technological effect are the key factors influencing carbon reduction potential for C&DW recycling. There are two types of interactions between influencing factor pairs: nonlinear enhancement and two-factor enhancement. This study's results can guide policymakers to devise relevant, regionally specific policies.

Can grain production be synergistic with socioeconomic development?—Empirical evidence from the agro-pastoral ecotone in North China

PurposeGrain production is an important foundation for economic development and social stability. Studying the interaction characteristics and influence mechanism between grain production and socioeconomic development is beneficial for promoting economic development and improving people’s well-being. MethodsBased on the water and carbon footprint perspective, this study first uses the Super-SBM model to measure the green production efficiency of grain in the agro-pastoral transition zone in North China from 2000 to 2020. Second, the theoretical logic of the synergy between grain production and socioeconomic development is established and the PVAR model is applied to verify the interaction. Third, the synergistic level is measured using the coupling coordination model. Finally, its dynamic evolution, regional differences and influencing factors are analysed by using kernel density estimation, the Dagum coefficient decomposition and the GTWR model. ResultsThe results show that ① The green production efficiency of grain first decreases and then increases, and the value is generally stable at approximately 1. ② The coupling coordination level shows an upwards trend of fluctuation; it moves from the mildly dissonant to the barely coordination stage, and many regions belong to the rich grain and poor area. ③ The regional differences show an overall decreasing trend, and the main source is intraregional differences. Environmental regulation has the greatest negative influence on the spatial and temporal divergence of coupling coordination, followed by the positive influence of urbanization.

The methods used to identify urban, rural, and intermediate territories at European level: A comparison of the methods developed in the framework of TERCET and ESPON

This paper examines the methods developed within the ESPON projects for identifying urban, rural, and intermediate territories, and compares the resulting territorial representations with those resulting from the implementation of the TERCET methods.In recent years, there has been an undeniable need for a harmonised delineation of territories that is both locally relevant and internationally comparable. On the one hand, locally relevant methods reflect the different perspectives that characterize territories and their diversity at the local level. On the other hand, methods that are internationally comparable harmonise comparisons between territories without taking into account intraregional differences and are mainly used for statistical analyses.This comparative analysis of the two types of methods uses documentary evidence and focuses on some key features (such as the preferred variables and statistical techniques, the spatial units, and the identified territorial classes) and some revealing indices of local relevance (such as the number of territorial classes) and international comparability (including use over time). The results demonstrate that the ESPON methods overcome the traditional dichotomous approach between urban and rural areas and provide solid evidence of territorial differences and progress in territorial policies and planning. Since these methods are often by-products, they strictly depend on the individual project's objectives and are rarely adopted in other studies or useful for reliable statistical comparisons. The comparison with TERCET typologies, which are the most commonly used for comparable statistical information at the European level due to their reliability and timeliness, reveals differences in all key characteristics and suggests that the choice of method to be used depends on the objectives of the scholar or policymaker.

Spatiotemporal dynamics and influencing factors of carbon productivity in counties of Shandong Province, China.

In the context of the increasing global greenhouse effect, the Chinese government has proposed a "dual carbon" target. As a major carbon-emitting province in China, Shandong Province needs to improve its carbon productivity to coordinate carbon emission reductions and sustainable economic growth. This study analyzes the spatial and temporal evolution of carbon productivity at the county scale and the factors influencing it in Shandong Province from 2000 to 2017. The study uses the Dagum Gini coefficient, kernel density analysis, spatial autocorrelation model, and geographically and temporally weighted regression model. The results indicate that the carbon productivity in Shandong Province nearly doubled during the study period, revealing a spatial distribution characteristic of "high in the east and low in the west," together with a significant positive spatial autocorrelation. Intra-regional differences, the most important source of development differences among the three economic circles, rose to 32.11% during the study period, whereas inter-regional differences declined to 26.6%. Gross domestic product per capita and population density play a significant positive role in the development of carbon productivity. The balance of deposits in financial institutions at the end of the year has a weak positive effect, and the local average public finance expenditure and secondary industry structure on carbon productivity are negative in general. Shandong Province should identify specific regions with weak carbon productivity levels and understand the key factors to improve carbon productivity to promote the achievement of the "dual carbon" goal.

Analysis of Measurement, Regional Differences, Convergence and Dynamic Evolutionary Trends of the Green Production Level in Chinese Agriculture

The development of green agriculture is conducive to accelerating the agricultural modernization process, making a significance for the sustainable development of agriculture and the environment in China. This paper constructs a comprehensive evaluation model by selecting 17 representative indicators from the perspective of sustainability. Then, this paper uses the entropy value method to measure the level of green agricultural production in 31 provinces from 2011 to 2021. We use Dagum’s Gini coefficient and decomposition method, the kernel density estimation method and spatial Markov chain analysis method to explore the main sources of spatial differences and dynamic evolution trends. The results show that: (1) The overall level of green production in Chinese agriculture is low, and the level in the central region is higher than that in eastern and western regions; (2) There are significant regional differences in the level of green production in China’s agriculture, and this is likely to widen. The interaction of inter- and intra-regional differences is the main reason for overall differences; (3) The trend of polarization in the level of green agricultural production is more obvious in the eastern part of China, while it is weaker in central and western regions; (4) There is a spatial spillover effect in the dynamic evolution of China’s agricultural green production level. And the longer the overall time, the more obvious the spillover effect is. This paper analyzes the past development of green agriculture in China, makes predictions and provides constructive suggestions for the improvement and development of green agricultural production in China in the future.

Advanced digital skills of the Spanish population from 2015 to 2021. Socioeconomic and geographical factors according to an ordered probit model

The increasing digitalisation of the economy, especially after the COVID-19 pandemic, requires the population to have advanced digital skills. In a decentralised country such as Spain, it is necessary to identify the population’s model of digital skills acquisition by taking geographical variables into account. To this end, the aim of this research is to analyse the impact of socioeconomic and geographical variables on the level of advanced digital skills of the Spanish population including two spatial levels: regional (Autonomous Communities) and local (provinces) from 2015 to 2021. An ordered probit model is used with microdata provided by the Spanish National Statistics Institute’s Survey on Equipment and Use of Information and Communication Technologies in Households (ICT_H) for 2015, 2019 and 2021. The results of this study show that socioeconomic factors have a greater influence than geographical factors on the digital skills acquisition model. The model has undergone changes with the emergence of the COVID-19 pandemic, with an increase of advanced digital skills among the employed and the unemployed compared to inactive persons. Moreover, the importance of educational level is corroborated and the importance of daily Internet use increased during the pandemic. There was also less regional than provincial dispersion in the probability of converging in digital skills with the region and province of Madrid. This study contributes the evolution over time of the model of digital skills acquisition with socioeconomic and geographical variables, identifying intra-regional differences and indicating whether there is spatial dependence between regional and local levels in Spain, with a view to reducing them in terms of sustainability.

Spatiotemporal differentiation and convergence characteristics of green economic efficiency in China: from the perspective of pollution and carbon emission reduction.

Accurate quantification of pollution and carbon emission reduction policies, as well as analysis of green economic efficiency (GEE), are of great significance to accelerating green economic development in China and contributing to pollution prevention and carbon peaking. Using data from 2006 to 2022, this study incorporates pollution and carbon emission reduction policies into the evaluation system, and uses a model with slacks-based measures and a directional distance function (SBM-DDF) to calculate the GEE of 30 provinces. The Dagum Gini coefficient, kernel density estimation, and spatiotemporal convergence analysis are used to analyze the spatiotemporal differentiation and convergence characteristics of GEE. The findings show that the strengths of the pollution and carbon emission reduction policies are increasing but vary greatly among the provinces. China's overall GEE has a time trend with the characteristics of "decline-fluctuation-stable." The Dagum Gini coefficient reveals the relative differences between the major regions. Both the intra-regional and inter-regional differences tend to widen over time and the latter explains most of the sources of the overall differences. Kernel density estimation shows that the absolute differences between the provinces are generally widening, whereas the absolute differences between the provinces in the central and western regions are smaller than those in the eastern region. No obvious σ convergence characteristics exist in the country overall and the three major regions, but β convergence characteristics are present in each region. The factors affecting changes in the GEE of each region are not the same. The study suggests that the China should further improve the implementation of pollution and carbon emission reduction policies, pay attention to the regional differences and convergence issues of GEE, and promote the coordinated development of green economy in different regions. This study innovatively quantifies the policies related to pollution and carbon emission reduction, providing empirical evidence for understanding the performance of pollution and carbon emission reduction policies in various regions. Furthermore, this study incorporates policies as inputs into the GEE evaluation system, reveals the spatiotemporal differentiation of GEE, thereby providing reference for green economic transformation and sustainable development.

Intraregional variability of exotic and native zooplankton in Basque coast estuaries (inner Bay of Biscay): effect of secondary dispersion, estuary features and regional environmental gradients

The zooplankton of five estuaries of the Basque coast (southeast Bay of Biscay) was surveyed in summer 2019 to check the intraregional spread of exotic species and analyse the cross-estuary differences in brackish and neritic communities related to the arrival of exotic species and the summertime geographic gradient of water temperature. Results revealed that all the studied estuaries have been colonized by Oithona davisae but not by Acartia tonsa and Pseudodiaptomus marinus. Environmental constraints due to estuarine hydrological features partly explained such differences, and the role of secondary spread opportunities remained less clear. Cross-estuary differences in the brackish community mainly reflected changes in the dominance of the native species Acartia bifilosa relative to different exotic copepod species. The neritic holoplankton differed in the contribution of thermophilic species in agreement with the thermal west–east increase of surface water temperature in the inner Bay of Biscay in summer. The detection of large numbers of larvae of the exotic crab Rhithropanopeus harrisii only in one of the estuaries highlighted the role of exotic benthic species in enhancing intraregional differences in estuarine meroplankton. Differences in the dominance of neritic or brackish species as a function of salinity and distance from coastline were also explored.

Analysis of spatial-temporal pattern, dynamic evolution and influencing factors of health tourism development in China

The evaluation index system is constructed based on the connotation and characteristics of health tourism. Using the entropy method, Thiel index, exploratory spatial data analysis method, spatial Markov chain and spatial econometric model, research is carried out around the development index, difference status, spatial-temporal pattern, dynamic evolution and influencing factors of health tourism. The following results were drawn: (1) The development index of health tourism in China is low, but the development speed is fast. The inter-regional development index shows an eastern China > central China > western China pattern, and the development speed exhibits a western China > central China > eastern China situation. (2) In the overall difference in China’s health tourism development, the intra-regional difference is consistently higher than the inter-regional difference. Among the three major regions, the overall difference between eastern China and western China is always higher than that of central China. (3) The development of health tourism in China is positively correlated in the global space, with some local spatial clustering. (4) The dynamic evolution of health tourism development in China shows part of the “Matthew effect” characteristics, with an obvious spatial spillover effect. (5) Various influencing factors produced widely varying direct, indirect and total effects on health tourism development in China, eastern China, central China and western China. Finally, based on the results of the above empirical analysis, policy recommendations to promote the development of health tourism in China are proposed.

Research on the dynamic evolution and convergence of collaborative capacity of pollution control and carbon reduction: from the perspective of whole-process governance.

Under the strategic goals of achieving peak carbon neutrality, deepening the battle against pollution, and building a beautiful China, improving the collaborative capacity of pollution control and carbon reduction is an important means to achieve comprehensive green and low-carbon transformation of the social economy. Starting from the essential requirements of improving the collaborative capacity of pollution control and carbon reduction, based on the whole-process governance perspective of "source-process-end-of-pipe," build an evaluation index system, measure the collaborative capacity, quantify the spatial differences, analyze the evolution characteristics, and explore the improvement path. The study found that China's collaborative capacity of pollution control and carbon reduction is characterized by homogeneous agglomeration and unbalanced regional development. Intra-regional differences are the main source of the differences, sorting by contribution is "Eastern > Western > Central > Northeast." After taking into account the factors of green transformation of industry, the input of scientific and technological elements, and opening to the outside world, the differences have gradually narrowed. Among them, the green transformation of industry is instrumentally in bridging the gap in eastern, central, and northeastern, the input of scientific and technological elements is instrumentally in bridging the gap between regions and the eastern and northeast, and opening to the outside world is instrumentally in bridging the gap between regions and the western. The scientific measurement and improvement of this capacity will provide the factual basis and path choice for achieving the task goal of "significantly improving China's collaborative capacity of pollution control and carbon reduction by 2030," which is of great practical significance for building a higher-quality, more sustainable, and greener pattern of the collaborative capacity of pollution control and carbon reduction.

Regional Differences, Distribution Dynamics, and Convergence of the Green Total Factor Productivity of China’s Cities under the Dual Carbon Targets

Economic development in China has been severely restricted by environmental problems such as carbon emissions. Improving green total factor productivity (GTFP) is an extremely important pathway to realizing carbon peak and carbon neutrality. Nevertheless, existing studies on China’s urban GTFP under the carbon emissions constraint are still insufficient. In this context, this study adopts the directional distance function (DDF), includes carbon emissions in the undesirable output, combines the global Malmquist–Luenberger (GML) productivity index, and calculates the GTFP of China’s cities. On this basis, the Dagum Gini coefficient, kernel density estimation, and convergence model are employed to explore the regional differences, distribution dynamics, and convergence in China and in three subdivision regions of east, center, and west. The core conclusions are as follows: (1) the average annual growth rate of GTFP in China’s cities is about 0.7064%, which is relatively low, but there is great room for improvement. The growth trend of GTFP in the three subdivision regions of east, center and west is obvious, presenting a spatial distribution characteristic of “high in the east and low in the west”; (2) the regional differences in GTFP of these cities are enlarging, with the largest gap in the eastern region and the smallest in the western region. Intraregional difference is the primary source of regional differences; (3) the imbalance in urban GTFP in China is prominent, with noticeable gradient differences, making it difficult to achieve hierarchical crossing. The central and western regions even have multilevel differentiation problems; (4) there is an absolute β convergence and conditional β convergence of China’s GTFP, but no σ convergence. As a result, it is necessary to comprehensively consider and actively implement the concept of shared development, enhance technological progress, focus on narrowing the differences in GTFP, and facilitate coordinated green development within the regions.

The study on the characteristics of carbon pressure agglomeration and the dynamic evolution of heterogeneity in China from a regional perspective.

Provinces (cities and districts) with identifiable boundaries are under intense pressure to reduce emissions as a fundamental unit and research object of carbon peaking and carbon-neutrality goals. Due to the significant variability of regional development, achieving equilibrium between carbon emissions and carbon absorption is challenging, contributing to the difficulty of developing carbon emission reduction and relevant green strategic initiatives in China. Therefore, this paper explored the spatial effect of carbon balance with carbon pressure as the starting point. First, this paper defined the "carbon pressure index" (CPI) of 30 provinces (cities and districts) in China from 2000 to 2019. Second, this paper validated the CPI agglomeration evolutionary characteristics in global and local aspects based on the Moran's index. Third, this paper identified and decomposed the spatial heterogeneity of CPI using the kernel density estimation method and the Theil index, then extracted typical cities to analyze the specific causes. Finally, this paper classified the seven regions in China into four types according to a comprehensive analysis of CPI. The results indicated that China's ecological carbon cycle system was in a serious "carbon overload" state. Thirty provinces (cities and districts) showed significant spatial agglomeration characteristics. The spatial gap of CPI was gradually decreasing nationwide, and the intra-regional differences were the leading cause of CPI levels in China. This can provide policy basis for the improvement of China's balanced development system of regional carbon emission reduction.

Evaluation of Supply and Demand Balance and Spatial Spillover Effect of Age-Friendly Environment

Given the rapid development of population aging, regions face significant challenges in providing diverse public service resources for the elderly. Constructing an age-friendly environment actively addresses population aging and ensures the well-being of the elderly. This study employed panel data from 31 provinces (municipalities) in China spanning the years 2014 to 2020. The research utilized a coupling coordination degree model, Theil index, Moran index method, and spatial econometric model to empirically examine the level of coupling coordination development, regional differences, and spatial spillover effects of age-friendly environments. The findings indicate the following: (1) In terms of coupling and coordination development, the degree of coupling and coordination of age-friendly environments in China shows a consistent upward trend over the years. The eastern region exhibits the highest level of development, surpassing the national average, while the western region has the lowest level, followed by the northeast and central regions. (2) In terms of regional development disparities, inter-regional differences gradually intensify due to variations in development status and resource endowment, playing a significant role in overall variations. Within regions, the highest intra-regional differences occur in the eastern region, while the lowest occur in the western region. (3) Considering the spatial spillover effect, the coupling coordination degree of age-friendly environments demonstrates positive spatial autocorrelation. Various development clusters and variables exert diverse influences on the coupling coordination degree of age-friendly environments within the region, while the spatial spillover effect of surrounding regions manifests distinct development patterns. The findings of this study contribute to enhancing the quality of age-friendly environment construction and promoting coordinated development among different regions.

Geographical Patterns and Influencing Mechanisms of Digital Rural Development Level at the County Scale in China

Digital rural development has become an emerging dynamic force for high-quality rural development in China. This paper constructs the “environmental-economic-social” analysis framework for digital rural development, analyzes the spatial variation of the digital rural development level (DRDL) in Chinese counties in 2020, and conducts the factor detection and interaction detection of its influencing factors. It is found that: (1) digital rural development has its own unique spatial differentiation mechanism, which can be analyzed from three dimensions: environmental system, economic system, and social system, which play a fundamental role, decisive role, and a magnifying effect on digital rural development, respectively. (2) The DRDL in China’s counties has significant spatial distribution, spatial correlation, and spatial clustering characteristics. The DRDL in general shows a decreasing distribution trend from coastal to inland regions, and the overall differences in DRDL mainly come from intra-regional differences rather than inter-regional differences. The rural infrastructure digitalization dimension has stronger spatial correlation while the spatial correlation of the rural governance digitalization dimension is weaker. There are obvious hotspot and coldspot areas in the DRDL, with large differences between the coldspot and hotspot areas of different sub-dimensions. (3) The spatial divergence of the DRDL is closely related to geographical elements and is the result of the combined effect of several geographical factors. The factor detection results show that the dominant factors within the four regions are significant different. The interaction detection results show that the driving force of the two-factor interaction is stronger than that of the single-factor interaction and that the interaction among the factors further deepens the spatial differentiation of the DRDL.

Spatial-temporal variation and driving forces of the synergy of “pollution reduction, carbon reduction, green expansion and economic growth”: evidence from 243 cities in China

IntroductionPollution reduction, carbon reduction, green expansion and economic growth—the synergistic effects of the four—have become essential in maintaining urban ecological security and promoting a green and low-carbon transition. And it is inherently consistent with the globally accepted concept of sustainable development. MethodsBased on the evaluation index system and the coupling mechanism of the four, we adopt the entropy method and the coupling coordination model to measure the synergistic level of “pollution reduction, carbon reduction, green expansion and economic growth” in 243 cities above prefecture level in China from 2005 to 2020. Furthermore, the study examined the temporal and spatial evolution and regional differences by utilizing the center of gravity-standard deviation ellipse, Dagum Gini coefficient method, Kernel density estimation, and Markov chain. In addition, the spatial econometric model was used to analyze the driving factors affecting the synergistic development.ResultsThe results show that the overall synergistic level is rising, the spatial distribution characteristics of “high in the east and low in the west.” The standard deviation ellipse shows a “northeast–southwest” pattern, and the center of gravity moves in a “southeast–northwest–southwest” migration trend. Regional differences are mainly rooted in inter-regional differences. The intra-regional differences are East > West > Central, with the most prominent East–West inter-regional differences. Without considering the spatial factor, the synergistic level shows a steady increase and has continuity. Under the spatial condition, the synergistic level has a positive spatial correlation. However, the positive spatial correlation decreases significantly as the years go by. Also, the probability of “rank locking” of synergistic development has been reduced, and there is a leapfrog shift. In terms of driving factors, the innovation level, level of external openness, population size, and industrial structure positively drive synergistic development. While government intervention negatively affects synergistic development. DiscussionsBased on the above findings,policy recommendations are proposed to strengthen the top-level design and build a policy system, play the radiation linkage, apply precise policies according to local conditions, and optimize the industrial structure fully. Which is of great significance for improving the urban ecological resilience and helping to achieve the “double carbon” target.

What drives the temporal dynamics and spatial differences of urban and rural household emissions in China?

Temporal dynamics and spatial differences of urban and rural household CO2 emissions are worth exploring in the face of climate change. This study combines decomposition analysis models and Dagum's Gini coefficient method to explore household emission characteristics and key drivers of 30 provinces in China. Income is still the major factor driving the growth of household emissions. Urbanization is accompanied by a population shift from rural areas to urban areas. Population has a positive effect on urban household emissions and a negative effect on rural household emissions. Although the rural population gradually decreases, their increasing income level and propensity to consume lead to emissions that are not negligible. Household CO2 emissions have significant spatial differences. For urban households in the eastern coastal region and rural households in the northern region, the population size effect drives the growth of household emissions. Rational population mobility is beneficial to reduce intra-regional differences in household emissions. Propensity to consume and emission intensity are important factors driving household emission growth in underdeveloped provinces and resource-based provinces, respectively. Thus improving household green awareness and promoting consumption upgrades are urgent. To enhance the coordination of regional development, cross-regional flows of technology and capital will help reduce regional emission disparities.

Spatiotemporal Variations and Convergence Characteristics of Green Technological Progress in China’s Mariculture

The sustainability of mariculture depends on adopting green technologies, which can mitigate the negative impacts on the environment and ensure long-term viability. However, existing studies do not comprehensively understand the characteristics and regional differences of green technology progress (GTP) in mariculture. According to data from ten coastal regions from 2008 to 2020, this study adopts the Epsilon-Based Measure (EBM)-Malmquist model to measure the GTP of mariculture, uses the Dagum Gini coefficient to analyze the spatial differences of GTP, and uses convergence models to explore the convergence of GTP. The results showed that: (1) the GTP of China’s mariculture showed a fluctuating upward trend temporally and significant spatial differences. The overall differences showed a dispersion trend over time. The contributions of inter-regional super variable net value difference (Gnb), inter-regional transvariation intensity (Gt), and intra-regional difference (Gw) were 38.813%, 31.256%, and 29.931%, respectively. (2) The degree of dispersion of GTP among different regions has not decreased with time, which means there is no apparent σ convergence. Absolute β convergence and conditional β convergence existed in GTP, and the absolute value of the latter was greater than that of the former. That is, the growth rate of GTP will first reach their respective steady-state levels and then approach a unified steady-state equilibrium level.

Spatial Disequilibrium and Dynamic Evolution of Eco-Efficiency in China’s Tea Industry

Eco-efficiency is a significant target for evaluating the agricultural ecosystem and measuring sustainable agricultural development through quantitative analysis. It is also an essential part of constructing the ecological tea garden, which offers a directional function in realizing the green development of the tea industry. After measuring the eco-efficiency of China’s tea industry using the super-efficiency SBM model, this paper analyzes the spatial disequilibrium and dynamic evolution trend of the eco-efficiency in China’s tea industry through the method of Dagum Gini Coefficient and Kernel Density Estimation. The results show that the level of eco-efficiency in China’s tea industry was improved overall, and the spatial disequilibrium was significantly reduced. The differences within the tea region decreased as follows: tea regions in Southwest China, South China, south of the Yangtze River, and north of the Yangtze River; the overall difference in the eco-efficiency in the tea industry mainly comes from the contribution of the interregional difference in tea regions, and the second contribution comes from the intraregional difference in tea regions and the difference in super-variable density. The eco-efficiency of the tea industry has been improved both nationally and within the top four tea regions; the disequilibrium between areas and within the tea region has been largely alleviated, but there is still room to optimize the input–output structure and promote the eco-efficiency.