Spatial Agglomeration Characteristics Research Articles

The impact of rice-crayfish field on socio-ecological system in traditional farming areas: Implications for sustainable agricultural landscape transformation

Agricultural landscape transformation has profound impacts on regional sustainable development. Understanding the relationship between agricultural landscape transformation and socio-ecological system is fundamental to both social prosperity and ecological environment. Rice-crayfish field (RCF) as a unique agricultural model is widely practiced in traditional farming areas and causes significant landscape transformation. However, the RCF remains less understood and its impacts on socio-ecological systems need to be comprehensively investigated. China has a developed crayfish industry with over 90% of the world's crayfish production, which provides an interesting lens to examine the RCF-led agricultural landscape transformation. This research proposes a novel research framework to analyse the spatial dynamic of RCF and its complex impact on socio-ecological system. Using remote sensing and geospatial data analysis, this study explores the spatiotemporal heterogeneity of RCF-led landscape transformation and socio-ecological system. In addition, the impacts of RCF on socio-ecological system are examined by the Pearson correlation analysis, root mean square error and regression model. The results reveal that RCF has dramatically expanded and transformed from paddy fields. The socio-ecological system presents obvious spatial agglomeration characteristics. RCF has the potential to increase farmers' income and alleviate rural poverty, but it is not conducive to grain production and water consumption. The RCF-led agricultural landscape transformation could be a double-edged sword to socio-ecological system. To balance social and ecological systems, it is necessary to manage and design the rational development of RCF to support sustainable agricultural landscape transformation.

Towards a low-carbon society: spatial distribution, characteristics and implications of digital economy and carbon emissions decoupling

Reducing carbon emissions and attaining sustainable economic, social, and environmental development are vital components of the 2030 Agenda for Sustainable Development. Previous research has overlooked the influence of the digital economy on urban carbon decoupling. To bridge this gap, this study employs GIS software and econometric models for analyzing the spatial distribution and characteristics of the digital economy and carbon decoupling and also investigates the direct, heterogeneous, and spatial effects of the digital economy on carbon decoupling. This study reveals: (1) A lesser digital economy presence in the northeast and northwest, while more developed in the Southeast Coast and municipalities directly under the Central Government. Cities with weak carbon decoupling are concentrated in Northeast and North China. (2) The digital economy and the decoupling of urban carbon emissions have spatial correlation and agglomeration characteristics. (3) The digital economy can contribute to decoupling carbon emissions in cities. (4) Improved urban carbon decoupling by the digital economy in central, eastern, and non-resource-based cities. (5) Spatial spillover effect in urban carbon emissions decoupling, yet the digital economy worsens nearby cities’ carbon decoupling due to a siphon effect. That research indicates that the digital economy holds significant promise not only in advancing human progress, bridging the digital divide, and fostering social development but also in driving the decoupling of urban carbon emissions.

Mechanism and evolution trend of digital green fusion in China's regional advanced manufacturing industry

This paper has observed pivotal changes in innovative frameworks at the intersection of the digital revolution and sustainable initiatives. Within Industry 4.0, the fusion between intelligent manufacturing and green innovation has become a central driver for sustainability. Integrating these two pivotal forces to harness their collective efficiency is crucial. However, current literature offers limited insights into their combined impact, and the direction of their evolving trends still needs to be defined. Considering this, the research elucidates the core concepts and traits of digital-green fusion (DGF) within regional advanced manufacturing (RAMIDGF). Moreover, this research proposes a double-helix fusion mechanism model. Utilizing data from the advanced manufacturing sectors in six key Chinese urban clusters, this paper adopts a comprehensive analytical toolkit that includes the Coupling Modified Model, Kernel Density Estimation, Markov Chain algorithms, and the Dagum Gini Coefficient for trend analysis. The findings indicate that between 2009 and 2021, RAMIDGF exhibited a trend of initial growth followed by a decline, showing a strong correlation with per capita GDP (RGDP). The principal source of variation in RAMIDGF stems from differences between urban agglomerations, with the Yangtze River Delta and the Beijing-Tianjin-Hebei clusters exhibiting transitional behavior and a ‘ladder-type trend’ in RAMIDGF. As metropolitan clusters become more economically integrated, the probability of transitional behavior in RAMIDGF heightens. However, achieving elevated leapfrog development proves challenging, with an inherent risk of decline. Spatial spillover implications, agglomeration characteristics, and club convergence tendencies mark the RAMIDGF process. These findings expand upon new paradigms for regional sustainable development, offering novel avenues for realizing high-quality growth.

The Impact of Agricultural Insurance on Urban–Rural Income Gap: Empirical Evidence from China

Based on the panel data of 31 provinces in China from 2005 to 2020, this paper analyzes the mechanism and spatial spillover effect of agricultural insurance on the urban–rural income gap using a fixed effect model, an intermediary effect model, and a two-stage least square method. The results show that agricultural insurance has a significant inhibitory effect on the income gap between urban and rural areas. This inhibitory effect is realized through the path of “improving the development level of agricultural insurance-improving agricultural total factor productivity-reducing the income gap between urban and rural areas”, in which the intermediary effect of agricultural total factor productivity accounts for 19.74% of the total effect. At the same time, the income gap between urban and rural areas in China exhibits typical spatial agglomeration characteristics. The western region has always been the region with the largest income gap between urban and rural areas, while the eastern region is the region with the smallest income gap between urban and rural areas. The development of agricultural insurance has had a spatial spillover effect on the income gap between urban and rural areas, and the development of agricultural insurance in neighboring areas expands the income gap between urban and rural areas in this region. In order to prevent the siphon effect, agricultural insurance investment should be increased in the neighboring regions. The results of this paper support the view of the resource flow model. Finally, we put forward some suggestions for the development of agricultural insurance, improvement in agricultural total factor productivity, and the narrowing of the income gap between urban and rural areas.

Retracted: Research on Spatial Agglomeration Characteristics of Aerospace Cultural and Creative Industries in Smart City under Multidata Fusion

Retracted: Research on Spatial Agglomeration Characteristics of Aerospace Cultural and Creative Industries in Smart City under Multidata Fusion

Spatial and temporal variations of landscape ecological risk in the dry and hot valley of the Jinsha River during 2000-2020

Scientific assessment of landscape ecological risk in ecologically fragile areas of the upper reaches of the Yangtze River is of great significance to regional ecological regulation and construction of the Yangtze River ecological security barrier. With the dry-hot valley area of Jinsha River in Yunnan Province as the research area, we constructed a landscape ecological risk evaluation model, and analyzed the spatial and temporal variations of regional landscape ecological risk. The results showed that the average values of landscape ecological risk index (LER) in the study area were 0.414, 0.398, and 0.462 in 2000, 2010 and 2020, respectively. The LER value of the whole region had reached a higher risk level by 2020. In 2000 and 2010, the landscape ecological risk zones of each level were staggered, and the high-risk zones showed a centralized distribution in 2020. During the two decades, the average LER of each section in the study area was around 0.42, which was close to the high risk level, indicating high landscape ecological risk level. The area of middle and low risk zones had decreased, while the area of high risk zone had significantly increased. The area of high risk zone in the western and middle sections was much higher than that in the eastern section. The area with significant changes of landscape ecological risk accounted for about 55% of the total study area, with obvious spatial agglomeration characteristics of significant increase and decrease of risk. The competition between government-led ecological management policies and measures and market-led land use activities was the main cause of landscape ecological risk variations in this region. In the future, the driving mechanism of climate change coupled with human activities on global and local landscape ecological risk changes in the study area should be uncovered to effectively cope with regional ecological risks.

Research on the spatial-temporal evolution pattern of China's industrial carbon emission efficiency-based on the super-efficiency SBM model

This paper uses the super efficiency SBM model based on unexpected output to calculate the industrial carbon emission efficiency of 30 provinces in China from 2005 to 2019, and uses spatial autocorrelation and other methods to conduct an empirical analysis on the dynamic evolution process and temporal and spatial differences of carbon emission efficiency. The results show that China's industrial carbon emission efficiency is still in the low efficiency stage, with an average value of 0.34. In the study period, although the overall trend is rising, the spatial and temporal differences between provinces are obvious. The overall Moran's I index is subject to the impact of social policy environment on the time path, showing an overall "M" type fluctuation trend, and its spatial difference characteristics change in stages. At the same time, there is a significant global spatial agglomeration effect across the country, and there is a spatial dependency between provinces. The agglomeration trend is significant, forming a cluster with the eastern coastal area as the high value center, and the northwest inland area as the low value center. The Getis OrdGI * index reveals that the local spatial agglomeration characteristics of China's industrial carbon emission efficiency always maintain the pattern of "hot in the east and cold in the west", which echoes the overall spatial evolution pattern of China. The hot spots and sub hot spots of China's industrial carbon emission efficiency are mainly concentrated in the southeast coastal areas with relatively superior economic development, and present a "semi enclosed" pattern. Cold spot area and sub cold spot area gradually evolved into a "suppression" pattern dominated by provinces in northwest China, comprehensively suppressing hot spots. This paper conducts an all-round evaluation of China's industrial carbon emission efficiency from the perspective of regional differentiation, and deeply studies the regional differences and spatial evolution pattern of carbon emission efficien cy in various provinces. It is crucial to achieve the goal of carbon emission reduction in China, and has important practical value and practical significance.

Research on the Distribution Characteristics of Cultivated Land Quality Grades in A County,Liaoning

Cultivated land quality has an important impact on the production capacity of cultivated land and the level of regional development, and is also directly related to national food security. The area-weighted method was used to study the quantity of different cultivated land quality classes in A county, and the spatial autocorrelation analysis was used to study the spatial agglomeration characteristics and differences of cultivated land quality in A county. The results showed that: (1) The natural quality of cultivated land in A county was mainly concentrated in 10-12 grade, while the utilization and economic grades of cultivated land quality were mainly in 11-13 grade, and the utilization and economic qualities of cultivated land were lower than the natural quality. The overall quality of cultivated land in A county was at a medium level. (2) The Moran's I index of natural, utilized and economic quality of cultivated land in A County is greater than 0. 4, showing a strong positive spatial autocorrelation in spatial distribution; In the LISA analysis, the spatial aggregation features of natural, utilized and economic quality of cultivated land turned out to be positive correlated HH type and LL type, and the insignificant NN type distribution was more obvious. (3) Based on the spatial pattern presented by the spatial autocorrelation results, corresponding measures were proposed to provide more scientific references for decision-making and technical support for the implementation of cultivated land fine management in A county.

Spatial Variations and Distribution Patterns of Soil Salinity at the Canal Scale in the Hetao Irrigation District

Soil salinization is a major factor impacting global crop yields. To explore the spatial distribution and influencing factors of soil water and salt in typical canals of the Hetao irrigation district, regional soil information was monitored at fixed locations. In this study, classical statistics, geostatistics, and spatial autocorrelation methods were used to conduct quantitative analyses of soil salt content, water content, soil particle size distribution, and groundwater depth. The variation coefficient of the soil salt content in the 20–40 and 40–60 cm soil layers was between 10% and 100%, which corresponds to a medium degree of variation; the other soil layers had strong degrees of variation. The soil moisture content in each layer varied moderately. The gold coefficients of soil salt content and water content were less than 0.25, and the Z value was greater than 0, showing a strong spatial correlation and certain spatial agglomeration characteristics, which were mainly affected by structural factors in the study area. The distribution patterns of soil water and salt were affected by soil particle size. Sand content decreased with increasing depth, soil salt was negatively correlated with sand content, and soil water was positively correlated with sand content. Soil salinity was significantly affected by groundwater depth and increased with decreasing groundwater depth, following an exponential relationship. When the groundwater depth exceeded 1.7 m, the soil salt content exhibited small changes with groundwater depth. The results of this study could play a guiding role in terms of understanding the degree of soil salinization surrounding canals in the Hetao irrigation area and adjusting land management strategies over time.

Exploration of spatial heterogeneity in the effect of woodland proportion on PM2.5: An empirical study from the Yangtze River economic Belt, China

Woodland is the most important land cover type for enhancing the environmental governance capacity and ecological protection benefits. Woodland proportion is crucial in reducing the quality and concentration of atmospheric fine particulate matter (PM2.5) and improving the atmospheric environment. Existing studies have mostly examined the connection between the woodland proportion and PM2.5 on a global scale, while ignoring the geographical variability and differences in the scope and intensity of the effect. Therefore, this study investigated the regional features of the effect from the perspective of spatial heterogeneity, using a spatial agglomeration analysis method, and global and local regression analyses models with 1049 counties in the Yangtze River Economic Belt (YREB). The studies reveal that woodland proportion has a considerable impact on PM2.5, and the effect’s direction is identical to that of the expectation at the global scale. The PM2.5 concentration falls by 0.017% for every 1% increase in the woodland proportion. The influence of woodland proportion on PM2.5 showed noticeable spatial heterogeneity, and the woodland proportion in 794 counties is strongly associated with PM2.5 concentration in local areas, with 66.44% of counties having the most obvious negative effect, and the areas with the greatest effect intensity are mostly distributed in mountainous areas. The concentration of PM2.5 in the YREB exhibiting a prominent characteristics of local spatial correlation and agglomeration, and a spatial characteristics of eastward peak and an westward low. Contrastingly, the distribution of the woodland proportion were the opposite—eastward high and westward low—with noticeable spatial variability. The findings of this study offer a foundation for decision-making and theoretical support for national or regional implementation of regionally differentiated and precise measures to prevent and reduce air pollution.

Spatial matching relationship between health tourism destinations and population aging in the Yangtze River Delta Urban Agglomeration

In order to address population aging and the healthy China strategy, this paper takes three provinces and one city in the Yangtze River Delta urban agglomeration as the empirical target. Firstly, using the 2010 and 2020 census data, and taking the aging coefficient and the density of the elderly population as the basic research indexes, this paper adopts the center of gravity migration model and the standard deviation ellipse to outline the spatial evolution path of the aging coefficient and the density of the elderly population. Second, using the data of recreational tourism sites in each prefecture-level city of the Yangtze River Delta urban agglomeration from 2016 to 2022, the closest neighbor index is used to judge the overall distribution characteristics of recreational tourism sites, and the judgment results are further verified with the help of Tyson polygonal analysis. Finally, based on the cross-section data of the elderly population in 2020, the spatial distribution of recreation and tourism sites and the elderly population are matched by the geographic concentration index, the center of gravity model and the matching coefficient. The results show that (1) the degree of population aging is deepening, and the characteristics of spatial Agglomeration are obvious, but the development speed among regions is inconsistent; (2) the distribution of health tourism destinations is wide and uneven between regions, showing the characteristics of ‘overall dispersion and local concentration’; (3) the spatial distribution of health tourism destinations and the elderly population shows a certain matching relationship, but the matching degree is not high. With the Yangtze River as the boundary, the distribution of health tourism destinations is ‘high in the south and low in the north’ and assumes a ladder shape from south to north, with obvious regional differences. Overall, health tourism lags behind the development process of aging.

Toward understanding the interaction of shale gas-water-carbon nexus in Sichuan-Chongqing region based on county-level water security evaluation.

This study develops a comprehensive framework for understanding the interaction of shale gas-water-carbon nexus in Sichuan-Chongqing region. Within this framework, a county-level water security index (WSI) evaluation system is structured. Spatial autocorrelation model and spatial matching degree model are integrated to illustrate the spatial agglomeration characteristics of water security and the water-carbon relationship, respectively. The impacts of shale gas development on water security and carbon emissions are evaluated based on identification of shale well productivity. Results show that about 25.17% of counties with WSI < 0.4 (unsafe), especially in the eastern region. The central cities (such as Chengdu and Neijiang) should take active steps to reach a safety threshold (WSI ≥ 0.6). Population growth can accelerate water security deterioration through uncertainty analysis. Moreover, the spatial matching degree between WSI and carbon emissions in most cities is extremely poor (< 0.5), implying that these cities should optimize their energy structure and promote green transformation. Water used for shale gas extraction can hardly be ignored from a county-scale perspective, especially in Tongliang, Tongnan, and Jianyang. The future shale gas development would pose a threat to the regional climate.

Impact of Chinese Local Government‐led Construction Land Supply Strategies on Urban Innovation and its Spatiotemporal Differences

AbstractThis study constructs a theoretical framework to analyze the impact of local government‐led construction land supply (LGCLS) strategies on urban innovation. It uses data related to 265 cities in China from 2005 to 2019 for empirical analysis. Its conclusions are as follows. For development stage differences, the impact of LGCLS strategies on urban innovation exhibited an inverted U shape with economic growth. The inflection point occurred when the per capita GDP equaled approximately RMB23,101 in 2008. For regional differences, the inflection point in eastern China is higher and earlier than that in central and western China; before the inflection point, the positive influence was more obvious in the central and western regions, whereas after the inflection point, the negative influence was more obvious in the eastern region. For the eastern Yangtze River Delta urban agglomerations and the northwestern resource‐based urban agglomerations with relatively high per capita GDP, the negative impact of LGCLS strategies on urban innovation occurred earlier and showed spatial agglomeration characteristics.

Spatial Pattern Evolution of the Manufacturing Industry in the Yangtze River Economic Belt and Its Impact on PM2.5

Instead of being merely an important embodiment of regional productivity, the manufacturing industry also serves as a significant sector of economic operation and the supply chain system that is highly dependent on resources and the environment. Studying the spatial pattern of the manufacturing industry and its environmental effect is extremely significant for optimizing the spatial layout of urban industry, allocating production factors in a rational manner, and promoting the green transformation of industry. In this regard, this study aimed to further reveal the spatial pattern characteristics of the regional manufacturing industry and its impact on PM2.5. Using data from micro-enterprises in the manufacturing industry in the Yangtze River Economic Belt, its spatial pattern characteristics are explored and an econometric model is constructed to analyze the impact of the manufacturing industry on PM2.5 by comprehensively applying approaches including kernel density estimation, nearest proximity index, and Dagum Gini coefficient decomposition. Three research conclusions were drawn: (1) an obvious “core-edge” feature is present in the spatial distribution of the manufacturing industry in the studied area showing an apparent pattern of “high in the east and low in the west”. The core density of the manufacturing industry in the central cities is significantly higher than that in the surrounding cities. (2) In the manufacturing industry and its subdivisions, the characteristics of spatial agglomeration are unveiled, while the agglomeration and spatial differences are diminished during the study period for the spatial equilibrium of the manufacturing industry. (3) A significantly positive impact is exerted on PM2.5 pollution that is not limited to local cities by the manufacturing industry, which, due to the development differences within the study region, is also heterogeneous. In view of this, policy proposals for aspects such as forging a green manufacturing cluster area, establishing an industrial integration development platform, giving play to regional advantages and technological potential, etc., are put forward in this study, so as to provide a useful reference for optimizing the industrial pattern and promoting the green transformation of industries.

Spatial Distribution and Typological Classification of Heritage Buildings in Southern China

Heritage buildings are a crucial aspect of a country’s cultural heritage, serving as a means of preserving and passing down its history and traditions to future generations. The heritage buildings in southern China possess significant conservation, utilization, and research value. However, research is lacking on the spatial distribution characteristics and subdivision types of these buildings in the region. This study aimed to investigate the spatial agglomeration and distribution characteristics of heritage buildings in southern China, as well as the factors contributing to the formation of these spatial distribution patterns. This article focused on the protection of 981 heritage buildings in southern China since the founding of China. The study examined the buildings’ spatial agglomeration and distribution characteristics from various dynasties and subdivided types. It utilized the average nearest neighbor analysis, unbalance index, and kernel density estimation to analyze this distribution. Additionally, this study also investigated the primary factors influencing the spatial distribution and differentiation of these buildings. The results demonstrated the following: (1) In general, the spatial distribution of heritage buildings in southern China is characterized by unevenness and clustering, with a concentration in the eastern coastal and Sichuan provinces. (2) In terms of temporal dimension, the spatial distribution of heritage buildings exhibits unique characteristics in various dynastic zones. (3) In the type dimension, the number of different types of heritage buildings varies greatly. (4) Further analysis of the distribution and types of heritage buildings indicates that quantitative differences are primarily influenced by natural, human, and socio-economic factors. This research was unique as it explored the geospatial distribution characteristics and determinants of heritage buildings. It offers a valuable perspective on the spatial distribution of heritage buildings and can serve as a reference for future studies on the preservation and protection of such buildings in China. Additionally, the findings can provide guidance for the management and rational use of heritage buildings in southern China.

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.

Spatial spillover effect of China's tax and fee reduction policies on independent research and development evidence from dynamic Spatial Dubin analysis.

To test the driving effect of China's tax and fee reduction policies on independent innovation, we established a model of Dynamic Spatial Durbin (SDM) and introduced DMSP/OLS night lighting data and Malmquist productivity index for partial differential decomposition. We found that: (1) Affected by the tax and fee reduction policies, the local province tends to increase the level of independent innovation in the short term, while neighboring provinces tend to purchase and rely on foreign technology; (2) In the long term, the tax and fee reduction policies do not significantly increase the level of independent innovation in local and neighboring regions; (3) There is a strategic choice behavior of local government between political promotion incentives and promoting independent innovation; (4) The policy externality of tax reduction and fee reduction has a two-way feedback effect. We conclude that: (1) The spatial agglomeration characteristics of tax and fee reduction policies require the government to fully consider the local innovation and economic foundation, and break the resource endowment of administrative divisions; (2) The spatial feedback feature of the tax and fee reduction policies requires the government to focus on the two-way interaction of independent innovation in the adjacent regions, rather than just one-way assistance, imitation and learning; (3) The spatial lag characteristics of tax and fee reduction policies require the government to establish a accountability system or life-long system for innovative performance evaluation. Moreover, the study fails to provide causality evidence from the spatial agglomeration and spatial time-delay.

Geological Hazard Assessment of Secondary Collapses Due to Volcanic Earthquakes on Changbai Mountain in China

In recent years, the volcanic activity of Changbai Mountain has been accompanied by several earthquakes, and the frequent human engineering activities have led to a gradual increase in the number of collapses in the region, which severely impacts residents’ lives and property safety. In northeastern China, the Changbai Mountain area in the southeastern Jilin Province is a typical mountain environment. This paper selects 12 evaluation indicators to build a hazard assessment system, including slope, aspect, elevation, curvature, lithology, NDVI, land use type, distance from the fault, the river from the road, volcanic earthquake, and annual average precipitation. Using emotional weight (G1 method) and objective weight (WOE-CV method), the hazard due to collapses in the study area is evaluated too. Among them, the transcendence probability of volcanic earthquakes greater than VI degree represents the relationship between Changbai Mountain volcanic earthquakes and the assessment of geological collapse hazard. The results show that high- and very high-hazard areas are mainly distributed in densely populated areas and national and provincial trunk lines, with apparent spatial agglomeration characteristics. The low-hazard area, medium-hazard area, high-hazard area and very high-hazard area accounted for 19.33%, 44.19%, 33.85% and 2.63% of the total area of the study area, respectively. By comparing the previous geological hazard survey reports in the area with the collapse hazard zoning map in this paper, 87.72% of the known collapse hazard areas are distributed within high and very high hazard zones, indicating that the conclusions of the article are more accurate and in line with the actual situation. Results from collapse-related hazards can provide relevant guidance for preventing and controlling geological risks posed by volcanic earthquakes affecting Changbai Mountain.

Identifying the spatial differentiation factors of traditional villages in China

China's agricultural civilization had left numerous traditional villages (TVs) containing rich historical information and cultural landscape. Exploration the spatial agglomeration characteristics of TVs and their influencing factors is essential for the sustainable development, utilization, and protection of TVs in China. However, previous studies lacked a comprehensive analysis of the spatial distribution of TVs and their driving factors, especially at the national scale. To fill this gap, this study analyzed the spatial agglomeration characteristics and influencing factors of five batches of TVs in China during 2012–2019. The results show that TVs in China were mainly located east of the Hu Line, that is, in the southern and eastern regions of China. The spatial distribution of TVs had significant clustering characteristics, and the gravity center was mainly distributed in central China, and the compactness of the spatial distribution of TVs increased from the first to the fifth batches. The TVs were mainly located at low elevations, northern slope aspect, warm and humid areas. Ferralisol and cultivated vegetation were the main soil and vegetation types in most TVs. TVs tended to be more numerous in the vicinity of low economic development levels, low population density, and rivers. In addition, TVs had a significant correlation with intangible cultural heritage. The results of this study could provide scientific guidance for heritage protection and sustainable development of TVs.

The impact of carbon-biased technological progress on carbon haze coordinated governance: insights from China.

Superficial or cosmetic measures are unlikely to solve the complex challenges of carbon haze governance. Carbon-biased technological progress plays a significant role in low-carbon technology and economic sustainable development. This study introduces carbon resources as a production factor in the transcendental logarithmic function to calculate the biased technological progress index of 30 provinces in China between 2010 and 2020. Subsequently, this study constructs the spatial Durbin model to empirically investigate the spatial spillover effect of carbon-biased technology progress on carbon haze coordinated governance. The findings reveal that China's technological progress is primarily characterized by carbon bias, particularly in terms of labor-using carbon-saving technological progress and capital-using carbon-saving technological progress. Additionally, both levels of carbon haze coordinated governance and carbon-biased technological progress have significant spatial agglomeration characteristics. Moreover, the carbon-biased technological progress can facilitate synergy degree of carbon haze governance through energy-saving effects but can also hinder the carbon haze coordinated governance through rebound effects. Therefore, it is imperative to improve labor productivity, augment green capital investment, and stimulate the induction of technological progress towards carbon saving to achieve sustainable and high-quality economic development. The primary contribution is identifying the uncertainty surrounding the impact of carbon-biased technological progress on coordinated governance of carbon haze, while also providing theoretical explanations for the influence channels of carbon-biased technological progress.