A Comprehensive Evaluation of Carbon Emission Reduction Capability in the Yangtze River Economic Belt.

<sec><title>Objective</title> The world is still in a phase of rapid industrialization and urbanization. Excessive carbon emissions has become the primary root cause of various urban or even global environmental problems, further impacting human physiological and psychological health. Cities are the largest sources of carbon emissions and are crucial regions for achieving carbon neutrality goals. Urban blue-green infrastructure (UBGI), comprising natural, semi-natural, or artificial green and blue spaces within cities, is considered as the most important carbon sink space in urban areas and has increasingly attracted widespread attention from researchers. However, there are still many unresolved issues regarding the effectiveness of UBGI in carbon sink enhancement and emission reduction: 1) How is the energy efficiency of carbon sink enhancement and emission reduction measured, and what factors influence it? 2) What are the mechanisms and pathways through which UBGI enhances carbon sink and reduces carbon emission? 3) How can UBGI be regulated to better enhance its effectiveness in carbon sink enhancement and emission reduction? 4) What are the limitations and potential directions for future research? This research aims to address these issues and propose scientifically sound planning strategies for UBGI construction to achieve urban carbon neutrality goals. </sec><sec><title>Methods</title> Through literature synthesis and deduction, this research organizes and analyzes the multi-scale measurement methods for UBGI’s efficiency in carbon sink enhancement and emission reduction, identifies corresponding influencing factors at each scale, and constructs multi-scale planning strategies for UBGI based on the logical framework of “measurement methods–influencing factors – planning strategies”. </sec><sec><title>Results</title> The research proposes UBGI planning strategies across three spatial scales (site, community and urban area), covering three key aspects: Carbon sequestration and sink enhancement, carbon reduction based on temperature reduction (or preservation), and travel-related carbon reduction. Based on current research gaps and planning needs, five major research topics are further identified. This research provides a detailed analysis of the measurement methods and influencing factors of UBGI’s efficiency in carbon sink enhancement and emission reduction from three perspectives: Carbon sequestration and sink enhancement, carbon reduction based on temperature reduction (or preservation), and travel-related carbon reduction. The research finds significant differences in the measurement methods for UBGI’s efficiency in carbon sink enhancement and emission reduction efficiency across different scales. Contradictory results may occur at different scales, and large-scale research often lacks characterization of internal features, leading to unclear mechanisms of influencing factors and obstructing practical planning. Based on the interpretation of UBGI’s mechanisms for carbon sink enhancement and emission reduction at different scales, this research formulates UBGI planning strategies across three spatial scales (site, community, and urban area). These strategies include: 1) At the site scale, for carbon sequestration and sink enhancement – carbon sink at the source, land balance, and ecological design; for emission reduction – symbiosis with buildings and integration into daily life. 2) At the community scale, for carbon sequestration – overall balance of revenue and expenditure, precise positioning, and proper interconnection of the carbon chain; for emission reduction – incorporation of cool islands and co-construction. 3) At the urban area scale, for carbon sequestration – enhancement of ecological space management and establishment of a carbon-safe pattern; for emission reduction – demand-based layout and organic dispersion. Finally, the research proposes five major research topics for the planning of UBGI’s carbon sink enhancement and emission reduction: How to construct unified measurement methods for UBGI’s efficiency in carbon sink enhancement and emission reduction across scales? How to measure UBGI’s efficiency in carbon reduction based on temperature reduction (or preservation) at the site scale? How to integrate the pathways of carbon sink enhancement and emission reduction for a life cycle assessment of UBGI? How to balance UBGI’s carbon sink enhancement and emission reduction with other functions to achieve the optimal layout for comprehensive benefits? How to achieve urban “carbon justice” through UBGI? </sec><sec><title>Conclusion</title> The carbon sink pathway of the strategy framework requires “carbon sink at the source – precise positioning – safe pattern”, and the emission reduction pathway requires “symbiotic integration – co-construction and sharing – organic dispersion”. The key trade-offs between these two pathways at three spatial scales may provide theoretical support and practical guidance for UBGI construction and management. The five major research topics mentioned above may offer valuable assistance for UBGI construction and future research. </sec>

Reasonable allocation of carbon emission rights aids in the realization of the goal of carbon emission reduction. The purpose of this paper is to examine how carbon emission rights in the power sector in the Yangtze River Economic Belt (the YREB) are distributed. The YREB spans China’s eastern, central, and western areas. The levels of development and resource endowment differ significantly across regions, resulting in great heterogeneity in the YREB provinces’ carbon emission rights distribution in the power sector. The ZSG–DEA model is used in this paper to re-adjust the power sector’s carbon emission quotas in each province to achieve optimal efficiency under the country’s overall carbon emission reduction target. The results show that: (1) In most provinces, the power sector’s initial distribution efficiency is inefficient. Only Zhejiang and Yunnan have reached the production frontier, with Jiangxi and Chongqing having the lowest distribution efficiency. In the future, we should concentrate our efforts on them for conserving energy and lowering emissions; (2) The initial distribution efficiency of the power sector in the YREB’s upstream, midstream, and downstream regions is considerably different. Most upstream and downstream provinces have higher carbon emission quotas, while most midstream provinces have less, implying that the power sector in the midstream provinces faces greater emission reduction challenges; (3) The carbon emission quotas of the power industry varies greatly between provinces and shows different spatial features over time. In the early stage (2021–2027), the carbon emission quota varies substantially, while for the later stage (2027–2030), it is rather balanced. Zhejiang, Jiangsu, Sichuan, and Yunnan are more likely to turn into sellers in the market for carbon emission trading with larger carbon emission quotas. While Jiangxi and Chongqing are more likely to turn into buyers in the market for carbon emission trading with fewer carbon emission quotas. Other provinces’ carbon emission quotas are more evenly distributed. To successfully achieve China’s emission reduction target by 2030, the YREB should promote regional collaboration, optimize industrial structure, accelerate technical innovation, establish emission reduction regulations, and provide financial support based on local conditions.

Reducing carbon emissions and realizing green, circular, and low-carbon development is essential for high-quality economic development. Following the construction of a superefficiency SBM model and combining the panel data of three major urban agglomerations in the Yangtze River Economic Belt from 2003 to 2017, carbon emission efficiency was measured and analyzed. A spatial Durbin model (SDM) was incorporated to analyze the urban agglomerations in the Yangtze River Economic Belt and the impact of urbanization quality and foreign direct investment (FDI) on carbon emission efficiency. Finally, the SDM model was used to decompose the spillover effect. Generally, carbon emission efficiency in the three major urban agglomerations in the Yangtze River Economic Belt is low, with regional differences. FDI only has a positive impact on the carbon emissions of the Yangtze River Delta and the middle reaches of the Yangtze River. Furthermore, urbanization and population density have led to high levels of carbon emission in the region; however, the industrial structure and energy intensity factors have inhibited the improvement of regional carbon emission efficiency. Improving the quality of urbanization and trade structure is important to achieve energy conservation and emission reductions, which are pillars of sustainable economic development.

It is greatly important to promote low-carbon green transformations in China, for implementing the emission reduction commitments and global climate governance. However, understanding the spatial spillover effects of carbon emissions will help the government achieve this goal. This paper selects the carbon-emission intensity panel data of 11 provinces in the Yangtze River Economic Belt from 2004 to 2016. Then, this paper uses the Global Moran’s I to explore the spatial distribution characteristics and spatial correlation of carbon emission intensity. Furthermore, this paper constructs a spatial econometric model to empirically test the driving path and spillover effects of relevant factors. The results show that there is a significant positive correlation with the provincial carbon intensity in the Yangtze River Economic Belt, but this trend is weakening. The provinces of Jiangsu, Zhejiang, and Shanghai are High–High agglomerations, while the provinces of Yunnan and Guizhou are Low–Low agglomerations. Economic development, technological innovation, and foreign direct investion (FDI) have positive effects on the reduction of carbon emissions, while industrialization has a negative effect on it. There is also a significant positive spatial spillover effect of the industrialization level and technological innovation level. The spatial spillover effects of FDI and economic development on carbon emission intensity fail to pass a significance test. Therefore, it is necessary to promote cross-regional low-carbon development, accelerate the R&D of energy-saving and emission-reduction technologies, actively enhance the transformation and upgrade industrial structures, and optimize the opening up of the region and the patterns of industrial transfer.

To achieve the goal of "double carbon" is the only way for our country to achieve emission reduction strategy. The Yangtze River Economic Belt is one of the strategic support belts for emission reduction, so it is of great significance to study the decoupling effect of energy and carbon emissions. Based on the carbon emission data of the Yangtze River Economic Belt from 1995 to 2021, this paper firstly analyzes the basic characteristics and spatial pattern of carbon emission in the Yangtze River Economic Belt. Secondly, a spatial econometric model is constructed to decompose the main influencing factors of carbon emissions in the Yangtze River Economic Belt, and the main influencing factors of economic and energy decoupling in the Yangtze River Economic Belt are explored by using the canonical correlation analysis method. Finally, BP neural network is used to forecast and analyze the carbon emission of the Yangtze River Economic Belt from 2022 to 2030. The results show that: (1) The center of gravity of carbon emissions in the Yangtze River Economic Belt is gradually shifting to the southeast, and there is a spatial correlation between regional carbon emissions. (2) The strong influencing factors of carbon emission in the Yangtze River Economic Belt are industrial composition and development differences; The influencing factors are city size and resource consumption intensity. The weak factor is the level of energy #consumption. The level of energy consumption and industrial composition are the main influencing factors of economic and energy decoupling in the Yangtze River Economic Belt. (3) Carbon emissions in the Yangtze River Economic Belt will continue to grow from 2022 to 2030, and will grow fastest from 2029 to 2030.

In order to explore the coordinated relationship between logistics industry carbon emissions and economic growth in the Yangtze River Economic Belt， with the goal of achieving the positive interaction between economic development and carbon emission reduction in logistics， this study calculated the carbon emissions of the logistics industry based on panel data from 11 provinces in the Yangtze River Economic Belt from 2010 to 2022 and analyzed the dynamic relationship between logistics industry carbon emissions and economic growth using the coupling coordination model and Tapio decoupling model. The results showed that： ① The average coordination between carbon emissions and economic growth in the logistics industry of the Yangtze River Economic Belt was relatively low， but it showed an increasing trend year by year， while provinces with higher economic levels exhibited higher coupling coordination levels in the same year. ② The number of provinces in the Yangtze River Economic Belt exhibiting weak and strong decoupling states between logistics industry carbon emissions and economic growth has gradually increased， indicating that these provinces have made progress in reducing logistics industry carbon emissions in recent years. ③ In heterogeneity analysis， the coordination degree between logistics carbon emissions and economic growth in the eastern， central， and western regions of the Yangtze River Economic Belt showed an "east-high， west-low" structure. Meanwhile， the proportion of strong decoupling states between logistics industry carbon emissions and economic growth in these regions has gradually increased， and the decoupling trend has become increasingly evident.

The contradiction between China's economic development and the reduction of carbon emission is increasingly deepening along with the complex carbon emission transfer. Optimizing provincial-level carbon emission transfer in China is important for facilitating economic development and carbon emission reduction. Under these dual constraints, this study uses the slacks-based measure, marginal abatement cost, and geographically and temporally weighted regression models to measure the economic and carbon emission reduction effects and the carbon emission reduction baseline. Then, the optimization strategy and path of provincial carbon emission transfer network structure are proposed to provide policy support for achieving the dual goals of economic development and carbon emission reduction in China. This article draws the following important research conclusions. First, under the three economic development scenarios, provinces in the eastern coastal developed regions are capable of completing the expected carbon emission reduction, whereas the underdeveloped provinces in the central and northern regions are not. Second, from the perspective of the economic effect of carbon emission transfer, carbon emission transfer from most provinces promotes economic development, whereas carbon emission transfer from a few economically underdeveloped provinces hinders economic development. Third, from the perspective of the carbon emission reduction impact of carbon emission transfer, carbon emission transfer in the northeast region has a negative impact on carbon emission reduction, and carbon emission transfer in developed regions also has a negative impact on carbon emission reduction. Fourth, the optimization of the carbon emission transfer can be divided into four categories.

Carbon emissions from the Yangtze River Economic Belt are an important element of China’s carbon emission endeavor, and a study of its emission reduction pathway can provide a reference for the country’s overall management of carbon emission reduction. From the perspective of energy consumption, this paper uses the carbon emission factor method to estimate the carbon emissions of the transportation industry in the Yangtze River Economic Belt during 2006–2020, based on the extended STIRPAT model, considering the influence of seven factors, i.e., population size, urbanization rate, GDP per capita, transportation added value, energy structure, energy intensity, and transportation intensity, on carbon emissions. Based on these factors, a scenario analysis, combined with a forecasting model, is used to predict the peak carbon performance of the transportation industry under different development scenarios. The results show that the overall carbon emissions of transportation in the YEB from 2006 to 2020 show a fluctuating upward trend, and the downstream carbon emissions are significantly higher than those in other regions. The main factors influencing carbon emissions from transportation in different upstream, midstream, and downstream regions vary, with both population and economic factors contributing to carbon emissions, while technical factors affect them differently. There are significant differences in the peak carbon performance of transportation under different development scenarios, and the government should take effective measures to work towards achieving the goals of the low-carbon or enhanced low-carbon scenarios.

China has entered a new stage of integrated development of urban and rural areas under the constraints of scarce land resources and the need for high-quality economic and social development. While there is concern about the state and speed of urban–rural integrated development (URID), increasing attention is being paid to efficiency improvement. This paper comprehensively measures the efficiency of URID from the input–output perspective, taking into account the impact of carbon emissions; it also studies the efficiency of URID and its developmental spatiotemporal characteristics in 73 cities within three major city clusters in the Yangtze River Economic Belt (YREB) from 2010 to 2019, and analyzes the input–output optimization strategies for URID within each of these major urban systems. The results show that (1) the comprehensive efficiency evaluation system constructed by the study can more objectively reflect the state and trends of URID. From 2010 to 2019, the efficiency of URID in the three major city clusters in the YREB showed a downward trend; in cities with better economic development, the efficiency of URID was lower than in cities with average economic development, where carbon emission indicators showed a significant impact. (2) The spatial distribution of URID efficiency in the three major city clusters in the YREB follows an inverted “U” shape; URID efficiency in the urban agglomeration in the middle reaches of the Yangtze River (MRYRUA) is higher than in the Chengyu urban agglomeration (CYUA), where it is higher than in the Yangtze River Delta urban agglomeration (YRDUA). (3) The input redundancy rates are high in the indicators for culture, sports and media, energy conservation and environmental protection, urban and rural communities, and housing security expenditures. Carbon emission redundancy has a negative impact on efficiency in URID. Based on the high redundancy rates of each input–output indicator, this paper proposes methods to optimize the efficiency of URID in each of the three major city clusters and provides directional guidance for promoting the high-quality development of regional urban–rural integration.

The digital economy (DE) is an essential transmitter of CO2 within the economic system, significantly impacting carbon emissions and high-quality development. The Yellow River Basin (YRB) and the Yangtze River Economic Belt (YREB), China’s two most important economic regions, are critical strategically for achieving the dual carbon target. This paper uses panel data from the YRB and YREB in China from 2011 to 2021 and adopts fixed and mediating effects to explore the internal impact mechanisms and spatial heterogeneity of the DE and carbon emission intensity (CEI) in the context of new quality productivity (NQP). The research results indicate that (1) the DE can significantly reduce CEI. A 1% increase in the DE reduces CEI by 0.1536% in the YRB and 0.0643% in the YREB, respectively. (2) The DE can affect CEI in the YRB and the YREB through mechanisms such as the economic development level, industrial structure advancement and rationalization, energy structure, and level of technological progress, with industrial structure advancement having the highest impact. (3) The YRB has a lower level of DE development and a higher overall CEI than the YREB. (4) A 1% increase in the DE leads to regional CEI variations: in the upstream of the YRB and YREB, CEI decreases by 0.1424% and 0.1956%, respectively, whereas in the midstream of the YRB, it decreases by 0.1298%, and in the downstream of the YREB, it increases by 0.0707%. We propose accelerating the development of the DE and constructing a green and modernized industrial system to achieve carbon reduction and emission mitigation goals.

Developing a comprehensive research framework that integrates the water–energy–carbon (WEC) system with economic development is crucial to fostering sustainable development. However, common evaluation indicators for sustainable development fail to cover the most up-to-date climate objectives and policies comprehensively and also lack a decoupling analysis between various subsystems and economic development. By incorporating the Tapio model and the coupling coordination degree model (CCDM), we introduce a novel water–energy–carbon–economy (WECE) framework to evaluate the sustainability of regional resources and the environment. Taking the Yangtze River Economic Belt (YREB) as an example, we have constructed a comprehensive water–energy–carbon (WEC) indicator system that aligns with China’s sustainable development objectives and its most recent carbon emission reduction strategies. Employing the indicator system, we conducted an assessment of the sustainable development within the YREB from 2010 to 2019. The results reveal that the YREB has yet to achieve full decoupling between water use, energy consumption, carbon emissions, and economic development, with a prevailing trend towards weak decoupling (WD). The WEC system within the YREB exhibited coordination from 2010 to 2019. Notably, only the WEC system in Sichuan attained good coordination in 2019, indicating the imperative for more extensive initiatives in resource and environmental development to realize sustainable objectives. Finally, we delve into the driving mechanism of the coupling coordination degree (CCD) of the WEC system. Our findings suggest that, from the perspective of system collaborative management, the integrated approach of the WEC system offers superior benefits compared to individual management components. Consequently, it is imperative to bolster collaboration and institute a comprehensive set of policies to ensure sustainable development within the region.

Carbon emission efficiency of land use in urban agglomerations of Yangtze River Economic Belt, China: Based on three-stage SBM-DEA model

This paper, using a comprehensive model to calculate the data collected from the 11 provinces along the Yangtze River Economic Belt, analyzed the 15-year dynamic changes in tourism carbon footprint in this region from 2004 to 2018. Our findings included: (1) Both total and per capita tourism carbon footprint of the 11 provinces along the Yangtze River Economic Belt tend to increase, bringing higher pressure on the environment except for the year of 2009 when the study of “low-carbon tourism” temporarily slowed down the regional carbon emissions. (2) In the lower basin of the region, Jiangsu claimed the highest in both total and per capita carbon footprint of tourism, while Shanghai saw an obvious effect in controlling carbon emissions through tourism. Jiangxi and Guizhou increased their tourism carbon footprint at the fastest paces in the middle and the upper basin, respectively. And (3) the per capita carbon footprint of tourism in the eastern, central, and western parts of the Yangtze River Economic Belt was 143.7kg/person, 97.9kg/person, and 104.8kg/person, respectively, showing that the east was greater than the west, which in turn was greater than the central part. The Yangtze River Economic Belt was meeting the dual challenges of economic development and carbon emission reduction with an obvious upward trend of carbon emissions through tourism. It had become one of the key tasks for the region to conserve energy, reduce carbon emissions, and develop low-carbon tourism.

Making coordinated efforts to reduce pollution and carbon emissions is not only an effective way to cope with climate change and solve the pollution problem but also the primary tool to promote comprehensive green transformation. Based on synergistic theory and the concept of green development， this study systematically considers the synergistic effects of various elements across economic， resource， and environmental dimensions. It constructs an Economic Resource-Pollution Reduction-Carbon Reduction index system to quantitatively assess the synergistic effects of pollution and carbon reduction in the Yangtze River Economic Belt. Utilizing empirical data from multiple levels， including the Belt as a whole， regions， and cities， the study analyzes the synergistic development of regional reduction of pollution and carbon emissions and proposes future paths and effective solutions for the synergistic development of pollution and carbon reduction. The results showed that： the process of synergistic development of pollution and carbon reductions in the Yangtze River Economic Belt started to show good development in 2017 and reached a medium level of synergism in 2020. The upper， middle， and lower reaches of the Yangtze River Basin have achieved significant progress in ecological protection and high-quality development， which was closely linked to national policies and regional strategies. At the urban level of the Yangtze River Economic Belt， the synergy of pollution and carbon reductions in each city from 2006 to 2021 generally exhibited a U-shaped development trend over time， showing a "high-low" two-gradient spatial distribution pattern from east to west. The practice of "ecological priority and green development" of the Yangtze River Economic Belt has demonstrated to the world that low-carbon development and green development can become a new engine for economic growth and ultimately achieve a win-win situation for the economy， society， and the environment.

Based on the panel data of 100 cities in China’s Yangtze River Economic Belt from 2010 to 2020 and the extended STIRPAT model, this paper uses SYS-GMM to empirically study the impact of green taxation on carbon emissions in the Yangtze River Economic Belt. Then, it explores the effect path of green taxation on regional carbon emissions using the intermediary effect model and analyzes the threshold characteristics of the influence of urban greening level on the regional carbon emissions of green taxation using the threshold effect model. The results show that, (1) from 2010 to 2020, the carbon emissions in China’s Yangtze River Economic Belt showed a slow rising trend, and carbon emissions in the lower reaches were significantly higher than those in the middle and upper reaches. (2) Green taxation can significantly suppress carbon emissions in the Yangtze River Economic Belt. However, green taxation has the weakest inhibitory effect on carbon emissions in the upstream region and is slightly stronger in the middle reaches, with the strongest inhibitory effect on carbon emission in the downstream region. (3) From the perspective of the action path, the level of green technology innovation has a significant partial mediating effect. Green taxation mainly realizes carbon emission reductions by improving the level of urban green technology innovation, and its intermediary effect accounts for 17.6% of the total effect of green taxation on regional carbon emissions and 15.6% of the total effect of green taxation on per capita carbon emission intensity. (4) Further research shows that the emission reduction effect of green taxation is also influenced by the level of urban greening, showing a single threshold effect. Before reaching the threshold value, the inhibition effect of green taxation on carbon emission levels is relatively strong, and after crossing the threshold value, the inhibition effect is weakened.