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BACKGROUND: This study aims to explore the development status of the supply level of professional public health resources in Beijing Municipality, analyze the areal differences and spatial distribution characteristics of the supply level in 16 districts, and provide a scientific basis for promoting the balanced development of the supply level of professional public health resources in each district of Beijing Municipality. METHODS: Based on panel data from Statistical Yearbook of Health Work in Beijing Municipality and Health and Family Planning Work in Beijing Municipality from 2014 to 2022. Using the entropy method to measure the supply level of professional public health resources in Beijing, employing the Dagum Gini coefficient and Kernel density estimation method to analyze the spatial differentiation characteristics and dynamic evolution process of the supply level, and using heat maps to display the spatial distribution of the supply level in various districts of Beijing. RESULTS: The Dagum Gini coefficient of the supply level of professional public health resources in Beijing Municipality decreased continuously from 0.3419 in 2014 to 0.29736 in 2020, then gradually increased, showing a trend of initially decreasing and then increasing overall spatial differences. The spatial differences mainly stem from differences between areas. The kernel density curve shows that the supply level of professional public health resources in Beijing Municipality gradually increased, slightly decreased after 2021, and did not form a situation of two or multi-level differentiation. CONCLUSION: From 2014 to 2022, the supply level of professional public health resources in Beijing Municipality showed an overall upward trend, but attention should be paid to the decline after 2021; spatial differences initially decreased and then increased, and the differences between areas is the main source of the overall difference in Beijing. Therefore, the Beijing Municipal Government should focus on narrowing the differences between areas, determine the allocation and management of public health resources based on the actual situation of core areas, promote coordinated development within and outside areas, and thus enhance the supply level of professional public health resources.

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Background: In recent years, the development of global public health has become a matter of great concern and importance for governments worldwide. China, as the largest developing country, plays a crucial role in shaping the development of the public health and its ability to respond to sudden public health emergencies through the fairness of its human resource allocation in center for disease control and prevention (CDC). Objective: This study aims to analyze the situation of health human resource allocation in the China Centers for Disease Control and Prevention (China CDCs), assess the fairness of the allocation, and provide reference for the rational allocation of human resources. Methods: We selected data from the China Health Statistics Yearbook on healthcare technical personnel, other technical personnel, managerial personnel, and workforce technical personnel of China CDCs for the period of 2016-2020. We utilized the Health Resource Density Index to evaluate the level of human resource allocation in China CDCs. Additionally, we used the Gini coefficient and Theil index to assess the fairness of human resource allocation in China CDCs from both a population and geographical perspective. Results: Firstly, the educational qualifications and professional titles of CDC staff have improved, but the workforce is aging. Secondly, HRDI development trends vary among different personnel types and regions with varying levels of economic development. Finally, the results of the Gini coefficient and Theil index indicate that population distribution fairness is better than geographical distribution fairness. Overall, the unfair population distribution is primarily due to regional disparities. Conclusion: The China CDCs should tailor different standards for the allocation of health human resources based on regional characteristics, aiming to enhance the accessibility of health human resources in various regions and achieve equitable allocation.

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The coupling coordination of digitalization and green development has become an inevitable requirement for building a new development pattern and achieving high-quality development of China's economy. Based on the panel data of 284 Chinese cities from 2011 to 2021, this study uses the coupling coordination degree model, Dagum Gini coefficient, spatial convergence, Markov transfer probability matrix, and panel Tobit model to quantitatively analyze the spatial-temporal evolution characteristics and influencing factors of the coupling coordination degree of digitization and green development. The study results show that the coupling coordination degree (CCD) of digitalization and green development has an overall increasing trend during the study period, and the eastern region is higher than other regions which showing spatial non-equilibrium characteristics. The spatial difference of the CCD continues to downward, and inter-regional differences are the main source of the CCD. In the long run, there is a "catch-up effect" between cities with low CCD and those with high CCD, and the CCD of digitalization and green development will tend to a steady state. The transfer type of the CCD has the characteristics of "club convergence", the probability of maintaining the original state is high, and the overall CCD shows a good development trend in the future. Factors such as environmental regulation, green innovation, industrial structure upgrading and financial efficiency can significantly contribute to the CCD of digitalization and green development. The above findings provide empirical evidence of the CCD of digitalization and green development to achieve high-quality economic development.

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Exploring the coupling coordination degree (CCD) between digital village construction (DVC) and agricultural carbon emissions (ACE) is crucial for promoting village revitalization and sustainable agricultural development. Analyzing data from 30 provinces in China in 2011-2020, this paper employs the CCD model, the Dagum Gini coefficient, and the geographic detector for in-depth analysis. The results show that the overall level of CCD gradually increases over time, but the national CCD still remains in a state of "low coordination," and there are apparent spatial differences in the CCD among provinces. In addition, the overall difference in CCD shows a decreasing trend, and the contribution of inter-regional differences has gradually become the most critical source of CCD's regional difference. Finally, the spatial differences of CCD are the result of two-factor interaction, among which the innovation level is the most core driving factor. The above findings provide important implications for China and other developing countries to fully leverage the interaction between village digitalization and agricultural decarbonization to promote sustainable agricultural development.

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As the main vehicle for the tertiary distribution, charity has a certain regulating effect on regional medical level. However, the improvement of regional medical effect of charity has yet to be tested. Based on provincial panel data from 1997 to 2019, this study analyzes the impact of charitable donations on regional medical level. The empirical results show that charitable donations widen the gap of overall regional medical level in China, which not only results from the current period but also from charity accumulation in the past. The regional heterogeneity analysis show that charitable donations have expanded the regional medical level of the eastern and western regions, while have no significant effect on the regional medical level gap in the central region. The widening effect in the eastern region of charitable donations is the largest. In addition, charitable donations expand the regional medical level gap between urban and rural areas in China. Charity, as the regional medical development mechanism, has not yet played its due role and advantages in regulating regional medical level gap. Formulating and adjusting the corresponding charity promotion policies is necessary.

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Background/purpose: Taiwan's dentistry entered into a new era of modernization and flourished during the Japanese colonial period. However, we know very little about the composition of dentists at that time. This study attempted to analyze the ethnicity, gender, and geographical distribution of dentists in Taiwan in 1939 (Showa 14). Materials and methods: The methods of documentary analysis and secondary data analysis were adopted to find the composition of dentists during the late Japanese colonial period through a name list of contract dentists for the Postal Savings Insurance published in August 1939 (Showa 14) by the Taiwan Government Transportation Department Information Bureau. Results: The total number of contract dentists was 368, accounting for 86.79% of the 424 practicing dentists in Taiwan in 1939 (Showa 14). Of the 368 contract dentists (328 males and 40 females), 225 (61.14%) were Taiwanese and 143 (38.86%) were Japanese. Among the 8 prefectures in Taiwan, Tainan Prefecture had the largest number of dentists (97), followed by Taipei (84) and Taichung (78) prefectures. The number of contract dentists per 100,000 people was 6.24, equivalent to 16,021 people served by each contract dentist in 1939 (Showa 14). The chi-square test for the trend analysis of gender distribution indicated a significantly higher proportion of male than female contract dentists in either Taiwanese or Japanese ethnic group. Conclusion: In the late Japanese colonial period, the number of Taiwanese dentists exceeded that of Japanese dentists. Furthermore, there were more male than female dentists in either the Taiwanese or the Japanese population.

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BACKGROUND: The Health and Medical Assistance Program for Poverty Alleviation is part of China's targeted poverty elimination strategy, which aims to protect poor people's right to health and prevent them from becoming trapped in or returning to poverty because of illness. Many tasks have been defined in this program, including raising the medical insurance level, providing a triage system, improving medical and health services, and enhancing people's health. One pivotal aspect of this initiative involves equitable health resource allocation, a key measure aimed at bolstering medical and health services. This study aimed to analyze and compare health resource allocations in different counties in Northwest China after the implementation of the program. METHODS: The Gini coefficient quantifies the level of distributional equality, the Theil index assesses the sources of inequality, and the Health Resource Agglomeration Degree gauges the accessibility of health resources. RESULTS: 1) The health resource allocation distributed based on population(Gini Coefficient < 0.45) was more equitable than that distributed based on area(Gini Coefficient > 0.35) among counties in Northwest China. 2) The contribution rate within non-impoverished counties is higher than that of impoverished counties, which means the inequality within non-impoverished counties. 3) The allocation of beds in medical institutions by area in non-impoverished counties was better than that in impoverished counties, and accessibility to health services for residents in non-impoverished counties was better than that in impoverished counties. CONCLUSION: The analysis of health resource allocation among the five provinces in Northwest China revealed significant differences in equality among the five provinces in Northwest China, and the differences were mainly derived from the non-impoverished counties. Although the equality is gradually improving, the number of health resources in impoverished counties remain lower than that in non-impoverished counties.Subsequently, it is essential to ensure equitable distribution of healthcare resources while also taking into account their utilization and quality.

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Objective: To evaluate the current status and equity of older adult resource allocation in the 31 provinces (autonomous regions and municipalities) of mainland China, and to offer recommendations for the optimization of these allocations. Methods: Four key indicators, namely, the number of older adult institutions, employees, professionals, and beds in mainland China in the year 2020, were used and analyzed using various methods and tools, including agglomeration analysis, the Gini coefficient, and the Lorenz Curve. These methods were applied to evaluate the equity of older adult resource allocation across the different provinces (autonomous regions and municipalities) and regions of China, using two dimensions, namely, the geographical area and the older adult population. Results: Overall, the number of older adult resource allocations was found to be increasing in China, while the number of employees with educational levels of junior college or above was relatively low and the population structure was aging. In terms of the equity of older adult resource allocation, the results showed that this was good according to the dimensions of the older adult population but was on the low side based on the dimension of geographical area, and the Gini coefficient of the western region, in particular, was in an alarming state. Different provinces (autonomous regions and municipalities) were found to have an uneven allocation of resources for older adults, with large differences, with some areas having a serious under-allocation of resources, while others showed resource over-allocation. Conclusion: While China's allocation of older adult resources is relatively equitable, there is nevertheless a need to take into account recent changes in the older adult population and strengthen the construction of a reasonably structured, high-quality team of professionals and technicians, as well as consider factors such as geographical area and the older adult population, and rationally allocate older adult resources in the eastern, middle, and western regions, to achieve a balanced allocation in terms of equity and efficiency and enhance social capital, to better satisfy the demands for older adult services in older adults at multiple levels.

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Background: As the vital and scarce resource of the health system, physicians are responsible for treating patients and saving lives and the equitable distribution of physicians among the whole population is a prerequisite to achieving health for all. We aimed to investigate inequality in physician distribution in the world using the Gini coefficient. Methods: This descriptive-analytical study was conducted in 2021. The number of physicians and the population of countries were obtained from the WHO and United Nations (UN) databases. The Gini coefficient was calculated in three different modes and the distribution of physicians among countries in various Human Development Index (HDI) groups was determined using the physician ratio per 10,000 population. Results: There were generally more than 13 million doctors in the world. About 43% of the world's physicians were available to 20% of the world's population in very high HDI countries, and 12% of the population had access to about 1% of physicians in low HDI countries. An average of 19.5 physicians are distributed per 10,000 population worldwide. The Gini coefficient between the four groups of HDI countries was 0.55, and that of all countries in the world was 0.640. Conclusion: There was a shortage and inequality in the distribution of physicians worldwide. Governments should eliminate inequality in the distribution of the medical workforce, in particular physicians, by redoubling their efforts and accurate planning.

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The United States offers two markedly different subsidy structures for private health insurance. When covered through employer-based plans, employees and their dependents benefit from the exclusion from taxable income of the premiums. Individuals without access to employer coverage may obtain subsidies for Marketplace coverage. This paper seeks to understand how the public subsidies embedded in the privately financed portion of the U.S. healthcare system impact the payments families are required to make under both ESI and Marketplace coverage, and the implications for finance equity. Using the Household Component of the Medical Expenditure Panel Survey (MEPS-HC) and Marketplace premium data, we assess horizontal and vertical equity by calculating public subsidies for and expected family spending under each coverage source and using Lorenz curves and Gini and concentration coefficients. Our study pooled the 2018 and 2019 MEPS-HC to achieve a sample size of 10,593 observations. Our simulations showed a marked horizontal inequity for lower-income families with access to employer coverage who cannot obtain Marketplace subsidies. Relative to both the financing of employer coverage and earlier Marketplace tax credits, the more generous Marketplace premium subsidies, first made available in 2021 under the American Rescue Plan Act, substantially increased the vertical equity of Marketplace financing. While Marketplace subsidies have clearly improved equity within the United States, we conclude with a comparison to other OECD countries highlighting the persistence of inequities in the U.S. stemming from its noteworthy reliance on employer-based private health insurance.

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Rural transformation plays a crucial role in enhancing the income and employment prospects of the rural labor force. We investigate the effects of rural transformation on rural income inequality at the district level in Bangladesh using data from five years of nationally representative Household Income and Expenditure Surveys. The Gini coefficient is used to measure rural income inequality. In contrast, the share of high-value agricultural outputs and the share of rural non-farm employment are used as indicators of rural transformation. We find that rural income inequality is positively associated with the share of high-value agricultural outputs and the share of rural non-farm employment. The non-linear regression result shows an inverted U-shaped relationship between rural transformation and income inequality, which indicates that income inequality initially increases with rural transformation but decreases in the long run. Additionally, we find that rural income inequality is positively correlated with the proportion of household education expenditures, agricultural rental activity, and the share of remittances. This study also reveals that income inequality in rural areas of Bangladesh has a significant negative correlation with the government's social safety net program.

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Background/purpose: Taiwan's eight dental schools are all located in the western region. This study attempted to analyze the relationship between the geographical distribution of dentists in Taiwan and their graduation school background and to develop several statistical indicators to analyze the geographical distribution of dentists. Materials and methods: The method of the secondary data analysis was adopted to collect the open information related to the number of the practicing dentists based on their graduation schools and practice locations by cities and counties in Taiwan in January 2023. The data were used to develop several statistical indicators to analyze the geographical distribution of dentists. Results: There were 16,533 practicing dentists in Taiwan in January 2023. Of the 16,533 dentists, 15,687 (94.88 %) graduated from domestic dental schools and 846 (5.12 %) graduated from foreign dental schools. For the school location, the coefficient of variation, Gini coefficient, population proportion index, and population density index were the largest (168.57 %, 0.47, 10.76 %, and 3927.01 people/square kilometer) in the dentists graduating from the northern dental schools. In overall, the dentists were concentrated in municipalities, cities, and the northern region of Taiwan, especially those graduating from the northern dental schools. Conclusion: In Taiwan, the geographical distribution of dentists is highly related to their graduation school background. Promoting a balanced distribution of dental enrollment quotas and dental student sources from different geographical locations and inducing the movement of dentists to the dentist-shortage areas may be the more feasible ways to solve the uneven geographical distribution of dentists in Taiwan.

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Objective: The regional inequality of emergency medicine beds distribution has a great impact on population health as well as the accessibility of emergency services. This study aimed to explore the regional inequality of emergency medicine bed distribution and its influencing factors. Methods: The Gini coefficient and health resource agglomeration were used to analyze the regional inequality of emergency medicine beds distribution by area from 2012 to 2021 in China. Grey correlation models were used to explore the factors influencing the regional inequality of emergency medicine beds distribution. Results: From 2012 to 2021, Gini coefficients of emergency medicine beds distribution by geographic in China showed a worsening trend, rising from 0.6229 to 0.6636. The average HRAD index was 3.43 in the east and 0.44 in the west. Population structure factors have the greatest influence on the regional inequality of emergency medicine beds distribution. Conclusion: Health resources allocation strategy only according to population size should be changed. In formulating policies for emergency medicine beds allocation should take into account population structure, financial structure of expenditure, the inequality of geographical distribution and so on.

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The intra-annual variability in sediment discharge was considerably influenced by the climate variability and vegetation dynamics. Because of the coupled or relationships between climatic and vegetation variables, it is still challenging to decouple the direct and indirect effects of climate variability and vegetation dynamics on hydrological and sediment transport processes. The purpose of this study is to decouple influences of individual driving force on intra-annual distribution of sediment discharge during 2003-2017 using the partial least squares structural equation model (PLS-SEM) method in four typical karst watersheds of Southwest China. The coefficient of variation (Cv), Completely regulation coefficient (Cr), Lorenz asymmetry coefficient and Gini coefficient were used to represent the intra-annual sediment discharge variability. Results showed that the monthly sediment discharge (190 % < Cv < 353 %) exhibited greater variability than its potential affecting factors (18 % < Cv < 101 %). From the PLS-SEM analysis, the water discharge, climate, and vegetation together explain 57 %-75 %, 64 %-79 %, and 53 %-80 % of the total variance in Cv, Cr, and Gini coefficient, respectively. Specifically, water discharge exerts the largest influence on sediment discharge variability (0.65 ≤ direct effect ≤0.97, P < 0.05), while vegetation dynamic mainly indirectly affects sediment discharge variability (-0.88 ≤ indirect effect ≤ -0.01) through influencing water discharge. The climate factors also principally indirectly affect the sediment discharge variability (-0.47 ≤ indirect effect ≤0.19) by affecting water discharge and vegetation. The PLS-SEM can effectively reveal the driving force and influencing mechanism of intra-annual sediment discharge changes, and provide an important reference for regional soil and water resources management in karst watersheds. Future studies can decouple the influences of the extreme climate, unique lithology, discontinuous soil, heterogeneous landscape, and special geomorphology on spatial variability in sediment discharge across different karst watersheds.

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China's agricultural development has entered a period of transition, and improving the cultivated land use efficiency (CLUE) is of great significance for guaranteeing national food security. Based on the province panel data in China from 2000 to 2021, this research calculates the cultivated land use efficiency, and uses the Dagum-Gini coefficient, Kernel density estimation, and Markov chain to conduct an in-depth analysis of CLUE's regional variations and distribution dynamics in three food functional areas (TFA) of China. The study results showed that the trend of CLUE was characterized by "increasing levels and decreasing absolute differences," not only in the whole country but also in the TFA. The inter-regional variation among TFA is gradually narrowing, and the cross-group degree of inter-regional variation is on the rise. The upward probability of CLUE was more effective than the probability of a transitionary change, and the mutual influence of CLUE between neighboring cities would lead to spatial convergence in the level of CLUE in the long term. Therefore, improving CLUE in China's TFA should not only grasp the regional differences in CLUE but also actively utilize the spatial spillover effects among functional regions to realize the cross-regional synergistic development of cropland utilization efficiency in China.

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Income inequality had been one of the important manifestations of social inequality, which can affect the health level by affecting savings, health care and living standards. Existing researches about the relationship between income inequality and health ignored the comprehensive characteristic of health concept, and did not consider the intrinsic relationship between health and income inequality. This paper attempts to re-shed light on the relationship. Firstly, this paper constructs a new health level evaluation system from three aspects: health basis, health environment and behavior, and health security. By means of the combination evaluation method, the health levels can be obtained. Then, considering the interaction between health and income inequality, a simultaneous equation group model is constructed to empirically test the relationship between income inequality and health levels in China. The results reveal that health level is negatively correlated with income inequality. Reducing income inequality plays an important role in improving health levels in China.

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While the spatial distribution pattern of fish is increasingly used for toxicological test of chemicals or wastewater, no ideal parameter is available for quantitative assessment of spatial distribution, especially uneven distribution with multiple hotspots. Here, to develop a quantitative assessment parameter for spatial distribution, the zebrafish were exposed to ethanol, pentylenetetrazole (PTZ), paraquat dichloride (paraquat) and wastewater, followed by a behavioral test in a narrow tank. Behavioral data was acquired and analyzed by idTracker and MATLAB. By comparing the effects of all treatments on behavior parameters, we confirmed that the spatial distribution was more easily altered rather than general locomotor parameters, e.g. 0.7-70 mg/L PTZ and 5-20 mg/L paraquat being effective for altering spatial distribution but having little effects on general locomotor parameters. Based on the heatmap, i.e., the cumulative proportion of grids and that of frequency in grids, we calculated the behavioral Gini coefficient (Gb) for quantitative assessment of fish spatial distribution. The Gini coefficient ranged from zero to 1, with larger values meaning poorer evenness of spatial distribution. Of note, Gb showed smaller coefficient of variations (CV) with 3%-19% between replicate tanks in all treatments than the highest frequency (4%-79%), displaying well robustness. Especially, Gb addressed the challenge of the complicated heatmap with multiple hotspots. Overall, the behavioral Gini coefficient we established is an ideal parameter to quantitatively assess spatial distribution of fish shoal, which is expected to be applied in toxicity testing for chemicals and wastewater and automatic quality monitoring for surface water and aquaculture water.

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This study establishes an indicator system encompassing economic, social, and environmental dimensions to assess the level of green development in animal husbandry from 2010 to 2020. It further examines the coupling coordination degree within each dimension. The Dagum Gini coefficient is employed to scrutinize the regional disparities in coupling coordination degree of the economic benefit, social benefit, and environmental benefit of the green development in Chinese animal husbandry. Additionally, Moran's I is utilized to identify the degree of spatial autocorrelation and aggregation types. The results demonstrate the following: (1) From 2010 to 2020, the level of green development in the animal husbandry in China has steadily improved. Among the three dimensions, economic benefits exhibit the highest performance, followed by environmental benefits and social benefits. There are obvious regional disparities in the green development of animal husbandry, which are "strong in north and weak in south" and "strong in west and weak in east." The Gini coefficient for green development in the animal husbandry in China experienced a fluctuating upward trend. (2) From 2010 to 2020, the overall coupling coordination degree of the economic benefit, social benefit, and environmental benefit of green development in the animal husbandry in China remains at a rudimentary level and demonstrates a steady upward trend. Spatially, it manifests an agglomeration pattern primarily centered around Beijing, with the northeastern region being the main focus. (3) The Gini coefficient for the coupling coordination degree experienced a slight fluctuating upward trend. In terms of inter-regional disparities, significant differences are observed between the northeastern region and the central region, as well as between the northeastern region and the eastern region. In terms of contribution to disparities, inter-regional contributions were the most substantial, followed by super-variable density, with intra-regional contributions being the smallest. (4) The coupling coordination degree displayed spatial autocorrelation, with "high-high" aggregation areas predominantly concentrated in the northeastern region.

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Poverty, an intricate global challenge influenced by economic, political, and social elements, is characterized by a deficiency in crucial resources, necessitating collective efforts towards its mitigation as embodied in the United Nations' Sustainable Development Goals. The Gini coefficient is a statistical instrument used by nations to measure income inequality, economic status, and social disparity, as escalated income inequality often parallels high poverty rates. Despite its standard annual computation, impeded by logistical hurdles and the gradual transformation of income inequality, we suggest that short-term forecasting of the Gini coefficient could offer instantaneous comprehension of shifts in income inequality during swift transitions, such as variances due to seasonal employment patterns in the expanding gig economy. System Identification (SI), a methodology utilized in domains like engineering and mathematical modeling to construct or refine dynamic system models from captured data, relies significantly on the Nonlinear Auto-Regressive (NAR) model due to its reliability and capability of integrating nonlinear functions, complemented by contemporary machine learning strategies and computational algorithms to approximate complex system dynamics to address these limitations. In this study, we introduce a NAR Multi-Layer Perceptron (MLP) approach for brief term estimation of the Gini coefficient. Several parameters were tested to discover the optimal model for Malaysia's Gini coefficient within 1987-2015, namely the output lag space, hidden units, and initial random seeds. The One-Step-Ahead (OSA), residual correlation, and residual histograms were used to test the validity of the model. The results demonstrate the model's efficacy over a 28-year period with superior model fit (MSE: 1.14 × 10-7) and uncorrelated residuals, thereby substantiating the model's validity and usefulness for predicting short-term variations in much smaller time steps compared to traditional manual approaches.

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Based on the panel data of 30 provinces (municipalities and autonomous regions) in China from 2005 to 2019, this paper uses Gini coefficient decomposition and kernel density estimation to investigate the regional differences and dynamic evolution trend of rural energy carbon emission intensity in China. Then, the convergence model is used to analyze the convergence characteristics and influencing factors of carbon emission intensity. The study found the following: (1) During the observation period, the carbon emissions of coal energy and oil energy were much higher than those of gas energy. The carbon emissions of rural energy consumption experienced three stages of development, and the carbon emission intensity showed a downward trend as a whole. The spatial distribution pattern of total carbon emissions present an "adder" distribution, and the spatial agglomeration phenomenon gradually strengthens with the passage of time. (2) The Gini coefficient of China's rural energy consumption carbon emission intensity shows a trend of "Inverted N-shaped." The Gini coefficient of carbon emission intensity in the eastern and northeastern regions shows an increasing trend, while the Gini coefficient of carbon emission intensity in the western and central regions shows a downward trend. The super variable density is the main source of carbon emission intensity difference. The peak value of the main peak of the nuclear density curve of the carbon emission intensity increased significantly, the bimodal form evolved into a single peak form, and the density center moved to the left. (3) The carbon emission intensity of rural energy consumption in the whole, central, and western regions of China has the characteristic of σ convergence, while the carbon emission intensity in the eastern and northeastern regions does not have the characteristic of σ convergence. There is a significant spatial positive correlation in the carbon emission intensity, there is also a significant ß convergence characteristic, the speed of conditional ß convergence is significantly higher than that of absolute ß convergence, and the spatial interaction will further improve the convergence speed. Industrial structure, industrial agglomeration, and energy efficiency will increase the convergence speed. In terms of sub-regions, the conditional convergence rate of carbon emission intensity in the four regions shows a decreasing trend in the northeast, central, eastern, and western regions.

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