Yangtze River Economic Zone Research Articles

Exploration of the Path of Industrial Structure Adjustment Forced by the Rigid Constraint of Water Ecology in the Yangtze River Economic Belt

Considering the two-way influence of water ecology and industrial structure, decompose and quantify the water ecological rigidity constraints into water environment constraints and water resources constraints, construct the evaluation system based on the theoretical framework of PSR, and analyze the spatio-temporal evolution characteristics of water ecological rigidity constraints of the Yangtze River Economic Belt from 2010 to 2021 by using the entropy weighting method, the method of catastrophe progression, and the kernel density estimation. Then, putting forward the types of zoning in the Yangtze River Economic Zone through K-means algorithm analysis to explore the rigid constraints of water ecology to force the path of industrial structure adjustment. The results indicate that: (1) the water ecological rigidity constraints show a decreasing trend, and the decreasing amplitude is upstream > downstream > midstream; (2) the water ecological rigidity constraints generally show the characteristic of “gradually decreasing from east to west”, and the degree of regional differences first decreases, then increases, and then decreases again; (3) it can be divided into six types, and the zoning results gradually change from the concentration in the medium-high type and high-high type to the concentration in the low-low type and medium-low type, and the rigidity constraint of water ecology is obviously improved. In light of the findings, the Yangtze River Economic Belt is divided into five types of development regions and further discusses that the industrial restructuring in different zones has different influencing effects on the regional socio-economic development, which provides suggestions for differentiated paths of water ecological protection and industrial restructuring.

Study on the ecosystem service flow based on the relationship of between supply and demand in Yangtze River Economic Belt

Ecosystems supply goods and services to humans and are the basis for sustainable development of human society. The study of the supply of ecosystem services and the demand and consumption of ecosystem services by human society, and the analysis of the supply and demand characteristics and flow relationships of ecosystem service flows are of great significance for the management of regional ecosystems and the development of ecological compensation. Taking the Yangtze River Economic Belt as an example, this paper calculates the supply and demand indices of ecosystem services in 2015 and 2020, and determines the ecosystem spatial flow paths and flow volumes from the ecosystem supply area to the demand area based on various methods and models such as the minimum cumulative resistance (MCR) model and distance decay model. The results indicate that 1). In 2015 and 2020, the supply and demand of ecosystem services in the Yangtze River Economic Zone show an increasing trend numerically, and there is spatial heterogeneity in the spatial distribution. In terms of ecosystem service supply per unit area, the midstream region is higher than the upstream and downstream regions. In terms of the demand for ecosystem services per unit area, the downstream is higher than the midstream and upstream. 2). From the supply-demand balance of ecosystem services in the Yangtze River Economic Zone, the midstream region is mainly the area of surplus supply of ecosystem services, and the downstream region is mainly the area of deficit supply. From 2015 to 2020, the number of areas with balanced supply and demand of ecosystem services in the Yangtze River Economic Belt decreases and the number of areas with unbalanced supply and demand increases, which is related to the changes in the level of economic development and land use patterns. 3). The flow of ecosystem services in the Yangtze River Economic Belt shows an increasing trend, from 726.59 billion yuan in 2015 to 1,450.54 billion yuan in 2020, with Jiangxi Province being the main ecosystem service supply area and Zhejiang Province being the main ecosystem service demand area in the Yangtze River Economic Belt.

Study on The Evaluation of Eco-Economic Efficiency in The Yangtze River Economic Zone

Eco-economic efficiency is of tremendous significance to the coordinated development of ecological environment and economy. This study uses the super-SBM model to assess the Yangtze River Economic Belt’s ecological and economic performance from 2011 to 2020. The Malmquist index approach is then used to dynamically analyze the total factor productivity. The findings indicate that there is a non-equilibrium feature in space and that the eco-economic efficiency of the Yangtze River Economic Zone as a whole exhibits a fluctuating rising trend. A downstream > midstream > upstream pattern is shown. Based on the dynamic Malmquist index and its decomposition, the Yangtze River Economic Zone’s total factor productivity has a robust upward tendency. The primary cause of the shift in total factor productivity is technological advancement.

Multi-Scale Analysis of Spatial and Temporal Evolution of Carbon Emissions in Yangtze River Economic Belt and Study of Decoupling Effects

An in-depth, longitudinal examination of carbon emissions and decoupling within the Yangtze River Economic Belt, supplemented by a dynamic assessment of its evolutional trajectory, provides a scientifically grounded framework and pragmatic value for the drafting of regional carbon emission mitigation strategies. Using the Yangtze River Economic Belt as a context, this study formulates a carbon emission model spanning provincial, city, and county levels. The model serves to uncover the spatiotemporal characteristics of carbon emissions within the Yangtze River Economic Belt from a multi-scalar vantage point. The Tapio decoupling model is then invoked to examine the extent and nature of decoupling between economic advancement and carbon emissions across these disparate scales. The outcomes divulge the following: (1) At the provincial echelon, the progression of carbon emissions born from energy consumption within the Yangtze River Economic Zone presents an escalating then stabilizing trend line. The carbon emissions growth rate transitions from a swift ascension of 8.44 percent initially, subsequently tapering to a moderate increment of 0.42 percent at the period’s culmination. The trajectory of carbon decoupling at the provincial scale tends to be generally propitious. (2) At the municipal scale, the overall carbon emission level shows a gradual upward trend, and then gradually forms a pattern of centripetal aggregation and peripheral diffusion. The decoupling status during the study period is mainly weak and strong decoupling, with the number of weak decoupling showing a fluctuating change in increasing and then decreasing, while the strong decoupling shows a slow and orderly growth trend, and is mainly distributed in most of the municipalities in Jiangsu, Zhejiang, and Shanghai. (3) At the county scale, centripetal aggregation and peripheral diffusion were already present at the beginning of the study period, followed by the gradual expansion and formation of several carbon emission centers of different sizes. The temporal evolution of county-level decoupling is more significant, with weak and strong decoupling dominating the county-scale decoupling during the study period, especially in the upper and middle reaches of the Yangtze River Economic Belt, but the overall trend shows signs of gradual decoupling.

Digital economy, land resource mismatch, and urban housing costs: Evidence from China's digital governance policy perspective

Live in peace and work in contentment" encapsulates people's aspirations within a digital economy framework. Has the digital economy truly realized this ideal? To answer this query, this paper delves into the correlation between the digital economy, resource mismatch, and urban housing costs across 272 Chinese cities. It evaluates the impact of policies propelled by the digital economy, using the “Broadband China” strategy as a benchmark. The findings suggest several key conclusions: (i) The imbalance in land resources exacerbates the digital economy's impact on escalating urban housing expenses. This effect is particularly pronounced in cities within the Yangtze River Economic Zone, cities experiencing low economic growth rates, large cities with high employment levels, and cities with relatively low wages. (ii) The rise of the digital economy has contributed to increased urban housing costs. For every 0.1 unit increase in a city's digital economy level, there is an observed average rise of 9.87% in housing costs. (iii) Policies steered by the digital economy, such as the "Broadband China" strategy, have significantly increased urban housing costs. A higher degree of resource mismatch correlates with a more pronounced impact of the “Broadband China” strategy pilot in elevating urban housing expenses. It is imperative to emphasize the qualitative ramifications of the digital economy. This should coincide with efforts to enhance resource utilization efficiency, aiming to mitigate the adverse effects of the digital economy's advancement on housing costs.

Coupled Coordination and Drivers of Green Technology Innovation and Carbon Emission Efficiency

The coupled and coordinated development of green technology innovation and carbon emission efficiency in the Yangtze River Economic Belt is crucial for its realization of green and low-carbon transformation. Based on the panel data of the Yangtze River Economic Belt from 2011 to 2021, the comprehensive evaluation levels of green technological innovation and carbon emission efficiency were measured, and the coupling degree of coordination model and panel Tobit model were constructed to empirically analyze the coupling degree of coordination and driving factors of the two. The results show that, overall, the comprehensive evaluation value of green technology innovation level in the Yangtze River Economic Zone shows an upward trend; the value of carbon emission efficiency first rises and then falls. From the perspective of spatial distribution, both of them present the characteristic of “high in the east and low in the west”. The coupling coordination degree shows a growing trend and initially realizes the basic coordination. The coupling degree of coordination shows a significant negative correlation between the energy structure and the coupling degree of both of them, while urbanization level, environmental regulation, industrial structure, level of economic development, degree of openness, and labor level all show a significant positive correlation.

Exploring the relationships between human consumption and environmental pressure: A case study of the Yangtze river economic zone in China.

It is crucial to decouple and coordinate human consumption and its environmental pressure for achieving sustainable development. As an important aspect of United Nations Sustainable Development Goal (SDG12), sustainability on material consuming is still in its early stages of research. To address the research gap in sustainable consumption of vegetation net primary productivity (NPP), this study analyzed the spatio-temporal dynamics of human consumption and environmental pressure in the Yangtze River Economic Zone (YREZ) using consumption-based HANPP (cHANPP) and Human Appropriation of Net Primary Production (HANPP) as indicators. Later, we measured their decoupling relationship using Tapio decoupling approach. We found that distribution of HANPP and cHANPP were regionally separated, with the former mainly concentrated in the middle and upper reaches provinces, while the latter concentrated in the lower reach provinces. From 2004 to 2019, the relationship between HANPP and cHANPP changed from strong negative decoupling to weak decoupling in the YREZ. Furthermore, the relationship was differed among different regions. As a whole, developing regions showed a weak decoupling state, experiencing an increase in environmental pressure (i.e., HANPP) alongside increased human consumption (i.e., cHANPP). In contrast, developed regions showed a strong decoupling state, experiencing a decrease in environmental pressure (i.e., HANPP) alongside increased human consumption (i.e., cHANPP). Our study highlights that different countermeasures should be formulated by regions according to their own situation to realize sustainable regional development.

Flood disaster industry-linked economic impact and risk assessment: a case study of Yangtze River Economic Zone

Flood disaster industry-linked economic impact and risk assessment: a case study of Yangtze River Economic Zone

Synergizing natural resources and sustainable development: A study of industrial structure, and green innovation in Chinese region

Amid China's rapid economic growth, the depletion of resources and escalating environmental pollution have emerged as critical impediments to its sustainable development. The efficient, convenient, and inclusive features of green innovation can facilitate economic transformation and provide technical support for sustainable industries. Optimization of the industrial structure can promote the allocation of resources in a more environmentally friendly and sustainable direction. Thus, we explore the impact of natural resource dependence on environmental quality and possible mechanisms through industrial structure, and green innovation using China's provincial panel data from 2011 to 2021. Research has shown that the decrease in natural resource dependency has a more obvious effect on improving environmental quality in the eastern region and the Yangtze River economic zone. Natural resource dependency influences sustainable ecology mainly through positive industrial structure upgrading and reverse spillovers in terms of green technological innovation. Industrial structure optimization and upgrading, improving factor allocation efficiency, and fostering a diversified industrial system are imperative for sustainable regional development.

How do urban function and development level effect construction level of green infrastructure? A case study of 110 built-up areas of cities in the Yangtze River Economic Zone

Urban green infrastructure (GI) is proposed for providing residents with welfare. However, there is little research on how to quantitatively and systematically assess the construction level of green infrastructure (CLGI), especially its relationship with urban function and development. This paper provides empirical evidence by a case study of built-up areas of 110 cities in the Yangtze River Economic Zone (YREZ) to investigate how urban characteristics affect CLGI. First, CLGI varies significantly between cities. GI waterfront level is the most dominant advantageous type, while GI allocation is the most dominant disadvantageous type. Second, most cities generally are in a slightly unbalanced or barely coordinated state between CLGI and urban development level (UDL). Subsystems of UDL and CLGI greatly influence each other, in which economic urbanization plays an almost decisive role in CLGI. Third, CLGI is the highest in most cities with cultural and scientific services as the major function especially in allocation and accessibility aspects, while the lowest in most cities with mining as the major function. Finally, this study presents a judgement model for GI priority goals and some practical implications, which is expected to facilitate evidence-based policymaking of urban planning and coordinated development of GI construction and urban characteristics.

Examining the Factors Influencing Agricultural Surface Source Pollution in the Yangtze River Economic Zone from the Perspectives of Government, Enterprise, and Agriculture

In this study, for the period between 2006 and 2021, we used the spatial Durbin model and dynamic Generalized Method of Moments to analyze the spatial and temporal characteristics and contributory factors of agricultural surface source pollution in 11 provinces and cities within China’s Yangtze River Economic Belt from the perspectives of governments, enterprises, and farmers. In addition, we also investigated the threshold characteristics of the distortion of the factor market for agricultural surface source pollution under different levels of environmental regulation. Our results revealed a positive spatial correlation between agricultural surface pollution in the Yangtze River Economic Belt which was significant at the 1% level. Furthermore, we established that government environmental regulation, input factor market distortion, and labor transfer have significant effects on agricultural surface pollution, among which factor market distortion has a significant spatial spillover effect in this economic zone, and environmental regulation has a significant single-threshold effect, with a threshold value of 0.1405. Based on these findings, we propose practical steps for the mitigation of agricultural surface pollution from the perspectives of governments, enterprises, and farmers which could be adopted to support countryside revitalization.

The Impact of Environmental Regulation on the Green Overall Factor Productivity of Forestry in the Yangtze River Economic Belt

Environmental regulatory instruments are key to achieving synergy between high-quality economic development and ecological civilization construction. This paper measures the green overall factor productivity of the forestry in the Yangtze River Economic Belt by using the super-efficient nonexpected output SBM-ML index model. Additionally, it investigates the environmental regulation’s impact on forestry’s overall green factor productivity by using the conventional panel regression and panel smooth transformation model. The model was based on the relevant data obtained from eleven provinces along the Yangtze River Economic Belt in China from 2006 to 2021. This study concludes that command-and-control regulation of the environment and public engagement with environmental regulation can significantly promote the forestry green overall factor productivity in the Yangtze River Economic Belt, and the environmental regulation’s effects on the forestry green overall efficiency in the economic region of the Yangtze River are regionally and temporally heterogeneous. The command-and-control environmental regulation also needs to exceed a certain level of regulatory coercion to promote the forestry green overall factor productivity positively. The effects of market-incentive environmental regulation were more pronounced with the increase in the regulatory intensity. When the regulation intensity surpasses the threshold, the public participation form of environmental regulation has a depressing impact on the forestry green overall factor output. To promote the development of the forestry industry in the Yangtze River Economic Zone, it is therefore necessary to strengthen the coordination of different environmental regulations, implement measures in each region, build a market-oriented green innovation system, and promote the structuralization and upgrading of the forestry industry.

Regional Differences and Convergence of Urban Water Use Efficiency in the Yangtze River Economic Belt

This study used a two-stage network data envelopment analysis model to measure the water use efficiency of 108 cities in the Yangtze River Economic Belt in the initial water use and wastewater treatment phases from 2009 to 2019. We divided the urban water use efficiency of six significant urban clusters in the Yangtze River Economic Belt using the Dagum Gini coefficient. We also tested the convergence characteristics of urban water use efficiency in six significant urban clusters in the Yangtze River Economic Belt using convergence and convergence kinds. According to this report, the Yangtze River Economic Zone’s cities often have low levels of water use efficiency, which is primarily due to ineffective wastewater treatment. The 108 cities in the Yangtze River Economic Zone are divided into four types based on the average values of water use efficiency in the initial use and wastewater treatment phases; the highest number of cities are in the double-low category, with low average values of water use efficiency in the initial use and wastewater treatment phases. During the study period, spatial differences in urban water use efficiency in the Yangtze River Economic Zone narrowed, with the differences stemming mainly from hyperdensity, followed by intra- and inter-regional differences. Meanwhile, there is convergence in urban water use efficiency in the Yangtze River Economic Belt, significant β convergence in the urban agglomerations of the Yangtze River Delta, Jianghuai, middle reaches of the Yangtze River, Chengdu–Chongqing, and Central Yunnan, and insignificant β convergence in the Central Qian urban agglomeration. After considering control factors, such as industrial structure, financial development level, environmental regulation, economic development level, and science and education development level, the water use efficiency of the six major urban clusters in the Yangtze River Economic Belt converges faster, but the influence of these control factors on the water use efficiency of each urban cluster is heterogeneous. Research results have reference value for the development of improvement strategies on differentiated urban water use efficiency in the Yangtze River Economic Belt. By measuring the regional differences in water use efficiency of urban agglomerations in the Yangtze River Economic Belt and clarifying their convergence mechanism, it provides a basis for analyzing the spatial pattern of water use efficiency in urban agglomerations and has reference value for formulating differentiated urban water use efficiency improvement strategies in the Yangtze River Economic Belt.

Quantifying night-time light change drivers in China’s Yangtze River economic zone

ABSTRACT Nighttime light (NTL) is a valuable data source for understanding urban sprawl and human activities. Radiometric quantification of NTL data can be used to explain the reasons for changes in NTL. We used average annual NTL data from 2013 to 2020 to investigate the magnitude and distribution of NTL change in the Yangtze River Economic Belt (YREB) in China. We found that NTL increased annually, with 93.06% of the area experiencing brightening. The annual NTL in 2020 was 2.42 times higher than that in 2013, and the NTL in the densely populated eastern provinces was 16.17 times higher than that in the west. Therefore, the east-west development of the research area is extremely uneven. Urbanization is often accompanied by dramatic NTL brightening, and the area of cropland being brightened is the largest of all landuse types. Urban development inevitably encroaches on cropland space. To address this issue, future policies should focus on sustainable regional development, for example encouraging urban densification development patterns. This will help to avoid the negative impact of urban expansion on the entire ecosystem.

The Development of Digital Finance and Regional Green Innovation Coupling and Coordination Analysis

The coordinated developmental nature between regions is explored from two perspectives: the degree of coupled and coordinated development between digital finance and regional green innovation and the spatial characteristics. Firstly, the coupling coordination model is used to calculate the degree of development level of two-way promotion between the two systems, furthermore, the Moran index is used to analyze the spatial correlation of the coupling coordination degree values, and finally, the influence of each digital finance and green innovation influencing factor of neighboring cities on the coupling agglomeration effect is studied through the spatial error model. Through the empirical analysis, it is found that the coordination degree of digital finance development and green innovation degree in the region is good, and the two can show the trend of coordinated development on the whole, and the coordination degree of digital finance development and green innovation degree in the Yangtze River Economic Zone has the characteristics of more obvious spatial non-equilibrium in the studied interval, and improving the coordination value of the provinces on the verge of disorder is the key to improve the coordinated development of digital finance and green innovation in the Yangtze River Economic Zone. The key to improve the coordinated development of digital finance and green innovation in the Yangtze River Economic Zone is to improve the coordination value of the endangered provinces. From the perspective of global autocorrelation, it can be learned that the coupling coordination degree presents significant characteristics in spatial agglomeration, and the local Moran index indicates that the local agglomeration effect in the Yangtze River Economic Belt mainly presents "high-high", "low-low", and "high-low" types. "Finally, the regression results obtained from the spatial error model show that the five indicators of digital financial usage depth, economic growth rate, green total factor productivity, foreign direct investment, and digital financial digitization all play a positive role in promoting the improvement of the regional coupling agglomeration effect.

How does agricultural production agglomeration affect green total factor productivity?: empirical evidence from China

Economic growth in agriculture is often accompanied by environmental pollution. To overcome this dilemma, agricultural green total factor productivity is essential. The role of agricultural production agglomeration has been studied extensively; however, there is no apparent association between agricultural production agglomeration and agricultural green total factor productivity. We use the non-angular and non-radial super-efficiency slacks-based measure model and the global Malmquist-Luenberger productivity model to assess the agricultural green total factor productivity in 30 Chinese provinces from 2001 to 2019. In addition, we investigate the evolutionary trend, influence relationship, and internal mechanism between agricultural production agglomeration and agricultural green total factor productivity. The results show an inverted U-shaped relationship between agricultural production agglomeration and agricultural green total factor productivity. Heterogeneity analysis finds that this role is more pronounced in provinces located inthe Yangtze River economic zone with strong fiscal support for agriculture and high levels of regional economic development. Regarding the mechanism analysis, enhancing green technology progress and the quality of rural human capital leads to an increase in agricultural green total factor productivity. Therefore, this study provides a new perspective on global carbon emission reduction and a theoretical and practical reference for realizing global agricultural green development.

A comparative study of green growth efficiency in Yangtze River Economic Belt and Yellow River Basin between 2010 and 2020

The Yangtze River Economic Belt and the Yellow River Basin are important economic regions and ecological barriers in China. Promoting the development of the Yangtze River Economic Belt and promoting ecological protection and high-quality development in the Yellow River Basin are major regional strategies implemented by the Chinese government, and the green growth of the two regions is important for the high-quality sustainable development of the whole China. To investigate the regional differences in green growth efficiency of the same type of geographical units, this paper measures the green growth efficiency and decomposition indicators of the Yangtze River Economic Belt and the Yellow River Basin from 2010 to 2020 using a three-stage DEA model and the Malmquist index method and establishes a panel Tobit model to identify the influencing factors of green growth efficiency. The results show that: ①After using the three-stage DEA model to remove the influence of external environment and stochastic factors, the mean values of green growth efficiency of Yangtze River Economic Zone and Yellow River Basin from 2010 to 2020 are 0.996 and 1.089, respectively. The change of green growth efficiency of Yangtze River Economic Zone is slightly higher than that of Yellow River Basin. ②The Malmquist indexes of the Yangtze River Economic Belt and the Yellow River Basin have generally increased, with the Technological Progress Index, which characterizes technological innovation, being the main endogenous driver of green growth efficiency in the Yellow River Basin, while the technical efficiency index, which characterizes factor mix and management level, is more significant in the Yangtze River Economic Belt. ③The Tobit model regression results show that the factors influencing green growth efficiency are also different in the two regions. Among them, the urbanization rate has a significantly positive effect on the two regions, while the effects of environmental regulation and research intensity are not significant. External openness has a suppressive effect on green growth efficiency in the Yangtze River Economic Belt, while the level of financial development and human capital negatively affect green growth efficiency in the Yellow River Basin. Therefore, green development in the new era should pay attention to the differences between different regions, and make appropriate development policies according to the local conditions of the development status of different regions.

An Innovative decision-making scheme for the high-quality economy development driven by higher education

It is essential to adhere to innovative leadership and teach students in accordance with their aptitude through the sustainable development of higher education. Promoting high-quality development of local universities is demanded and needed for the adaptive talent in this new era. This work aims to explore how high-quality higher education can provide innovative decision-making solutions for economic development in the digital economy (DE) era. First, the role of higher education in economic development is analysed. Then, the importance of human capital cultivated by higher education to economic development is explained. The innovations are as follows. (1) A high-quality economic development index system in the Yangtze River Basin is established according to the requirements of quality change, dynamic change, and efficiency change in the economic development of the Yangtze River Economic Zone (YREZ). (2) The entropy weight method in intelligent decision-making and TOPSIS sorting technology are used to study the dynamic relationship between DE development and the premium-quality economic advance of the provinces and cities in the YREZ from 2015 to 2021. (3) The analysis part adopts three indicators of mean logarithmic deviation, Theil index, and the Gini coefficient to discuss the regional differences in economic development. Finally, a targeted development strategy is proposed. The results indicate that the DE level of each province in the YREZ in recent years has reached a maximum of 3.9309 and a minimum of 0.2844. The economic development of each province is relatively different, and the level of development is uneven. The overall Moran's I of the premium-quality economic development level of the YREZ in recent years is greater than 0, passing the significance test. This result suggests a positive spatial autocorrelation between them. The research provides data support for the formulation of economic development strategies for the YREZ in the future and reflects the key role of higher education in human capital training and economic development.

SiamHRnet-OCR: A Novel Deforestation Detection Model with High-Resolution Imagery and Deep Learning

Forests play a critical role in global carbon cycling, and continuous forest destruction together with other factors has accelerated global warming. Furthermore, continued decline of forest areas will critically hinder the accomplishment of carbon neutrality goals. Although the geographical location of deforestation can now be rapidly and accurately detected with remote sensing technology, current forest change products are still not fine-grained, especially from the perspective of carbon trading. Here, we used a deep learning method to detect deforestation in large regions based on 2 m high-resolution optical remote sensing images. Firstly, we proposed a new deforestation detection dataset, which was generated from 11 provincial regions in the Yangtze River Economic Zone of China, containing a total number of 8330 samples (the size of each sample being 512 × 512 pixels). Then, a new deforestation detection model, SiamHRnet-OCR, was designed, based on this dataset. Compared with other deep learning models, SiamHRnet-OCR achieves better results in terms of precision, F1-score, and OA indicator: 0.6482, 0.6892, and 0.9898, respectively. Finally, two large-scale scenarios of deforestation experiments in Southern China were further tested; the deforestation detection results demonstrate that SiamHRnet-OCR can not only detect deforestation effectively but also capture the accurate boundary of the changing area.

Spatial and temporal evolution patterns of material, energy and carbon emission nexus for power generation infrastructure in China

Climate change and energy transformation has made huge alteration in power system, which led to great uncertainty in relation to material, energy and carbon emissions in power generation infrastructure. We aim to estimate material stock and carbon emissions of power generation infrastructure and explore material-energy-carbon emission nexus in China from 1993 to 2060 using stock-driven dynamic material flow analysis model for materials production and carbon emissions. Results indicate that cement is the largest used material and the southwest economic zone in China has highest cement intensity due to hydropower construction, whilst steel intensity is evenly distributed across the country, aluminum intensity the smallest and more distributed in northwest region, and copper stock is the lowest. Southwest and Yangtze River economic zone contributes most to carbon emissions from national power infrastructure. Material per unit installed capacity from 1993 to 2018 has an overall increasing trend, but carbon emissions per unit installed capacity of power generation are expected to decline. Carbon emissions of new installed capacity is expected to peak around 2028. This study provides a dynamic approach to assess resource consumption and carbon emissions intensity of power generation infrastructure for decision-making on China's carbon peaking and neutrality goals.