[Objective] In the context of the marginal reduction effect of technological innovation, it is of great significance to investigate the carbon reduction potential of economic structural transformation to achieve the “dual carbon” goal. [Methods] Based on the input-output theory and structural decomposition analysis, this study constructed an explanatory framework to describe the carbon emission reduction driven by economic transformation. The multi-regional input-output table and corresponding carbon emission data of China from 2007 to 2017 were used for the analyses from the industrial and spatial dimensions respectively. The contribution of the dynamic adjustments of energy structure, input structure, intermediate production structure, consumption structure, investment structure, and export structure to carbon emission reduction was systematically analyzed, and discussed at the national, regional, and provincial levels respectively. [Results] (1) During the study period, the carbon emission reduction caused by structural changes was about 1.727 billion tons, and China’s economy realized the power transformation from technology-driven carbon reduction to structural change-driven emission reduction; (2) The optimization of intermediate production structure was the pillar of structural change-driven emission reduction, and the effect of industrial structure optimization among economic sectors is much greater than that of spatial structure optimization caused by inter-regional resource factor reallocation; (3) The carbon emission reduction effect of industrial structure optimization within each region was more significant, and the inland regions with inherent geographical disadvantages failed to realize the spatial allocation optimization under regional synergy. The carbon emission reduction effect of the eastern region, whether it is fully developed within the region or due to coordinated development between regions, took lead in the country. (4) Regional development level and economic structural change carbon emission reduction effect mainly showed the characteristics of “tail effect” and “scale effect”, in which the investment structure emission reduction had scale effect, but the factor input still faced structural imbalance, resulting in the increase of carbon emissions caused by the change of factor input structure in provinces with large populations and economic scale. [Conclusion] Economic structure transformation is an important path to achieving carbon emission reduction. Through the “two-wheel driving” effect of production side and demand side structure optimization on carbon emission reduction, China’s low-carbon transformation development will be continuously promoted.

The ocean has great potential as a carbon sink. Under the background of global climate change, marine carbon sink is an effective way to build ecological civilization and achieve carbon neutrality in the new era, and has received extensive attention from academia. As an efficient long-term carbon sink, the carbon sink mechanism, carbon sink effect, carbon sink technology, carbon sink accounting, and carbon sink trading market construction of the marine systems are becoming new topics that need to be explored in various disciplines. Based on the analysis of the origin of research and conceptual connotation of marine carbon sink and by examining carbon sinks and carbon sources, this study combined the relevant research literature of marine carbon sink in the China National Knowledge Infrastructure (CNKI) and the Web of Science (WOS) core databases, and used bibliometric tools to quantitatively compare and analyze the main characteristics, such as the number of publications, journals, authors, and institutions, of marine carbon sink research in China and internationally. Through keyword clustering and emergence and co-occurrence knowledge maps, the research hotspots, frontier fields at different stages, and evolution trends of themes were explored. The results show that the number of publications on marine carbon sink research in China and internationally has shown a fluctuating growth trend. Liu Jihua and Christian J. Sanders are the most influential authors in this field. Foreign countries have carried out extensive cooperation in this field, and Chinese researchers have also formed small-scale academic research teams. Research institutions are mainly universities and research institutes, focusing on coastal areas; the research directions are gradually diversified and the hotspots are clear. The key research directions of marine carbon sinks are examined, and the key contents that need to be paid attention to in future research are discussed: multidisciplinary studies should guide the research to promote the unified carbon sink market research of land and seas; studies should be based on the carbon sinks of coastal wetland and mariculture environment to realize new breakthroughs of marine carbon sink research; to build a marine carbon sink protection management system with a comprehensive ecological compensation mechanism as the guide; to explore marine carbon sink application models based on research on theories and technological innovations related to marine carbon sinks; and to explore blue carbon cooperation mechanisms in countries along the Maritime Silk Road with a focus on marine carbon sink cooperation research. This study examined the status of research of marine carbon sinks in China and internationally to promote the further scientific development of research in this field.

[Objective] Digital finance based on information technology provides a new opportunity for the construction of a water-saving society. Effectively release the dividend of water saving and emission reduction brought by the development of digital finance is an important issue for promoting the development of the Chinese-style modernization. [Methods] Based on panel data from 30 provinces in China from 2011 to 2020, this study empirically tested the relationship between digital finance development and water resource utilization using methods such as fixed effect and mediation effect models. [Results] (1) The development of digital finance has an inhibitory effect on water use intensity, which is mainly achieved by improving the coverage and depth of use of digital finance, and the result is still valid after robustness tests such as substitution of variables, instrumental variable method, and limited information maximum likelihood method. (2) From the perspective of transmission pathways, technological innovation and industrial structure adjustment have played a significant mediating role between digital finance and water use intensity, but the mediating role of industrial structure upgrading is not significant. (3) From the perspective of heterogeneity, digital finance has a positive impact on water use efficiency in the eastern region; Meanwhile, digital finance has a significant inhibitory effect on the water use intensity of the primary and secondary industries, but the impact on the water use intensity of the tertiary industry is not significant; Regions with favorable water endowments are more likely to reap the benefits of digital finance. [Conclusion] Therefore, it is necessary to strengthen the construction of digital finance, actively innovate financial services, and give full play to the enabling role of digital finance in resource utilization according to local conditions and production policies.

[Objective] During the concurrent development of the “dual carbon” goals and the digital economy, relying on digital power to promote environmental governance has become an important research focus. Exploring the impact of digital technology on the synergy of carbon reduction and pollution reduction and its mechanism have great significance. [Methods] Based on provincial-level panel data from 2011 to 2020 in China, this article uses benchmark regression models to explore the direct impact of digital technology on the synergy of carbon reduction and pollution reduction. By constructing threshold regression models, the nonlinear effects of digital technology on the synergy of carbon reduction and pollution reduction across the country, as well as in the eastern, central, and western regions, with industrial structure upgrading, energy utilization efficiency, production process innovation, and environmental regulation as constraint variables, were explored. [Results] (1) In the whole country, as well as in the eastern, central, and western regions, digital technology has a positive direct impact on the synergy of carbon reduction and pollution reduction, and shows a distribution characteristic of “central>western>eastern”. (2) Digital technology has a significant threshold effect on the synergy of carbon reduction and pollution reduction at the national level. When the industrial structure upgrading is above the threshold, energy utilization efficiency is above the second threshold, production process innovation is between the first and second threshold, and environmental regulation is above the threshold, the driving effect of digital technology is stronger. (3) The threshold effect tests were conducted on the eastern, central, and western regions, and all three regions showed significant nonlinear effects. Among them, except for when the environmental regulation in the western region exceed the threshold, digital technology has a negative nonlinear impact on the synergy of carbon reduction and pollution reduction; When the threshold variables are higher than the threshold, digital technology has a stronger positive effect on the synergy of carbon reduction and pollution reduction. [Conclusion] Digital technology is conducive to promoting the synergy of carbon reduction and pollution reduction and assisting China in promoting ecological civilization construction. Therefore, all regions should incorporate the whole-process governance into the collaborative work of carbon reduction, pollution reduction, and efficiency enhancement, formulate differentiated policies, and form a joint force of “digital + green” development.

[Objective] The digital economy is an important focus for realizing the transformation of China’s old and new development momentums, and its extensive integration and continuous development within various economic and social fields have given China a new power dynamic for the synergistic effect of pollution reduction and carbon reduction. In the critical window of promoting the construction of “Beautiful China” and realizing the “dual-carbon” climate commitment, the study of the impact of the development of the digital economy on the synergistic effect of pollution reduction and carbon reduction is an important proposition in the context of realizing green and high-quality development in China. [Methods] Based on the panel data of 277 prefecture-level and above cities, this study examined the impact of the digital economy on the synergistic effect of pollution reduction and carbon reduction and its mediation mechanism in multiple dimensions by using fixed effect and mediation effect models. [Results] The findings are as follows: (1) The development of the digital economy significantly contributes to the synergistic effect of pollution reduction and carbon reduction, and the conclusions still hold after endogeneity and robustness tests using the instrumental variable method and excluding the four provincial-level municipalities. (2) The “broadband China” strategy was chosen as an exogenous policy shock, and the multi-period difference-in-differences (DID) model was used to evaluate the impact of the digital economy on the synergistic effect of pollution reduction and carbon reduction. The regression results show that the “broadband China” strategy had a positive and significant impact on the synergistic effect of pollution reduction and carbon reduction. (3) The test results of the mechanism analysis show that the development of the digital economy can promote the synergistic effect of pollution reduction and carbon reduction by improving technologies, promoting industrial structure upgrading, and enhancing public environmental supervision. (4) The analysis of regional heterogeneity showed that the impact of the digital economy on the synergistic effect of pollution reduction and carbon reduction is more significant in the eastern region and non-resource-based cities, while the impact is not significant in the central and western regions and resource-based cities, which is mainly related to the uncoordinated level of digital economy development among regions. [Conclusion] We should vigorously develop the digital economy, accelerate the construction of new infrastructures, strengthen environmental awareness and action of the government, enterprises and the public, and fully unleash the potential of the digital economy based on the comparative advantages of the resources in each region, so as to realize synergies in reducing pollution and carbon emissions.

[Objective] Since the 1990s, cross-border mergers and acquisitions (M&A) have become an important part of the operation of economic globalization, providing an important driving force for the international flow and circulation of capital factors, it is necessary to analyze the formation mechanism of the global cross-border M&A networks. [Methods] This study constructed an analytical framework based on “endogenous structural effect-actor & relationship effect-exogenous network effect”, and used the global cross-border M&A data from 1997 to 2018 to explore the structural characteristics and formation mechanism of global cross-border M&A networks by using complex network methods and exponential random graph models. [Results] The study found that: (1) The spatial scope of the global cross-border M&A networks had expanded significantly and the overall trend was decentralization, but North America and Western Europe still occupied the core position of the networks. (2) The endogenous structural effect of the global cross-border M&A networks was reciprocal and transitive, which was manifested in the mutual M&A behavior between most countries (regions) in the networks, and tended to operate in a group structure. (3) In terms of actor & relationship effect, national (regional) economic development level was the key influencing factor for the formation of cross-border M&A networks, and countries (regions) with high economic development level or low economic development level tended to carry out M&A transactions with those of similar economic development levels to their own, and countries (regions) with medium economic development level both had foreign M&A tendencies and were easy to become destinations for global M&A parties to issue cross-border M&A contacts, and were active participants in cross-border M&A activities. (4) In terms of exogenous network effect, geographical proximity, linguistic proximity, and institutional proximity were the positive driving factors for the formation of cross-border M&A networks. [Conclusion] There is still much room for improvement in the tightness of the global cross-border M&A networks, and it is necessary to further promote the efficient flow of global knowledge and technology, and strengthen M&A cooperation between countries (regions).

[Objective] As the low-carbon advantage of high-speed railway is conducive to the early realisation of the strategic goal of “carbon neutrality and carbon peaking”, it is of great significance to explore the low-carbon emission reduction effect of high-speed railway construction and its influencing mechanism from a multi-dimensional heterogeneity perspective. [Methods] Based on the panel data of 281 prefecture-level and above cities in China from 2006 to 2020, this study considered the construction of high-speed railway as a quasi-natural experiment, and adopted the multi-period difference-in-differences method, spatial difference-in-differences method, and mediation effect model to systematically investigate the direct effect and spatial spillover effect of the construction of high-speed railway on the intensity of carbon emission in cities and mechanism. [Results] The study found that: (1) The construction of high-speed railway made a significant contribution to the reduction of urban carbon emission intensity, and there was a four-year delay period in this effect on average; (2) The emission reduction effect of high-speed railway was significant in western cities, growing and declining resource cities, and non-hub cities, but not in other regions and types of cities; (3) The results of mechanism test show that the construction of high-speed railway can reduce the carbon emission intensity of cities by increasing the level of urban economic agglomeration and scientific and technological innovation; (4) The results of spatial difference-in-differences analysis show that the negative “siphoning effect” of high-speed railway construction on the carbon emission intensity of neighboring cities was greater than the positive “diffusion effect”. [Conclusion] Therefore, for the construction of high-speed railway, the state should keep the existing stock and maintain the constant growth so that high-speed railway can continue to play a role in low-carbon development and emission reduction, and local governments should also take into account local conditions, formulate emission reduction policies reasonably, and promote the coordinated development of regions while realizing the carbon emission reduction target of cities.

[Objective] Accountability audit of natural resource is an institutional arrangement to strengthen China’s ecological civilization construction. Analyzing the mechanism and empirical evidence of accountability audit of natural resource on environmental quality from China’s political economic and social background is of great significance. [Methods] This study used the difference-in-differences model and took 303 cities at the prefecture level and above in China from 2015 to 2020 as the research object to investigate the policy effect of accountability audit of natural resource during the national promotion period. Based on the heterogeneity of natural resources endowment, resource-based cities were taken as the treatment group, and non-resource-based cities were regarded as the control group. [Results] (1) The study found that with the normalization of the accountability audit of natural resource system, the environmental quality of resource-based cities has been significantly improved in comparison to non-resource-based cities, embodying reduction in industrial pollution discharge. (2) The results of mechanism tests demonstrate that the pressure of resource succession and environmental performance can boost the improved level of environmental quality in resource-based cities. Local officials who have been promoted to a higher position after leaving office showed a better environmental performance during their term of office. This result supports the theoretical proposition of this policy to advance pollution control by completing the performance assessment and the accountability mechanism. (3) The path test result indicates that an increase in environmental protection investment is a possible way to step up the upgrading of the environmental quality in resource-based cities. [Conclusion] Accountability audit of natural resource is in accord with China’s actual condition, which has long-term and universal effectiveness. It is necessary to strengthen the application of audit results, improve the construction of supporting systems, and promote the full coverage of environmental responsibility audits.

[Objective] Digital transformation provides an opportunity for manufacturing enterprises to save energy and reduce pollution emissions. Clarifying the impact of digital transformation on manufacturing enterprise pollution emissions and its mechanism provide important policy implications for high-quality economic development. [Methods] In this study, we used the fixed effect model, moderating effect model, and instrumental variable method to examine the impact of digital transformation on manufacturing enterprise pollution emissions and its mechanism based on the matching data of the China Industrial Enterprises Database, China Industrial Enterprises Pollution Emissions Database, and the World Input-Output Database. [Results] (1) The empirical results show that digital transformation can significantly inhibit the pollution emissions of manufacturing enterprises, and this inhibitory effect has heterogeneity across different industries, regions, and types of firm ownership. Specifically, the impact is greater in high-tech industries, eastern and northeastern regions, foreign investment firms, and export-oriented firms. (2) Further mechanism test results show that this inhibitory effect is achieved by the front-end control to improve productivity and promote energy consumption structure transformation, and back-end governance to improve pollution treatment capacity. [Conclusion] Digital transformation is conducive to optimizing enterprise environmental performance and helping advance ecological civilization. It is necessary to promote digital technology to empower the green transformation of manufacturing enterprises, form a virtuous cycle of digitalization and greening, and lead the formation of new economic growth points.

[Objective] Aiming to clarify the specific emission reduction mechanism of carbon tax, give full play to its emission reduction function, and promote the construction of carbon emission reduction policy system. [Methods] A coupled model of computable general equilibrium (CGE) and structural path decomposition (SPD) was developed to identify the key emission reduction paths of carbon taxes, and the drivers promoting emission reduction on each path were decomposed and analyzed. [Results] The results show that the indirect emission reduction triggered by the industrial chain accounts for 80.77% of the total emission reduction from the carbon tax, and the emission reduction effect of the carbon tax will gradually diminish with the increase of the production level. The energy efficiency effect is the most important driver of carbon tax for emission reduction, and the role of different drivers varies across production levels and on different emission reduction paths. The key industries such as heavy industry, thermal power industry and coal industry providing the main carbon reduction contribution. Fixed capital formation contributes the most to carbon reduction and mainly achieves carbon emission reduction through the path of influencing the construction industry’s demand for upstream energy-intensive industries. [Conclusion] Therefore, the driving force mechanism of each key factor on carbon emission reduction at different production levels and paths of carbon tax should be fully grasped and utilized, the emission reduction potential of key links in the industrial chain should also be fully explored, and targeted measures should be taken to promote synergistic emission reduction among industries.

[Objective] Human activities change the nature of the underlying surface, which in turn has a significant impact on the spatiotemporal changes in air pollutant concentrations. Exploring the response relationship between air pollutant concentrations and land use area is beneficial for understanding and controlling air pollution from the perspective of land resource management. [Methods] Based on the generalized additive model (GAM), this study investigated the nonlinear response relationship between the proportion of land use areas in 10 km × 10 km grids and the annual average concentrations of four main air pollutants (PM_2.5, PM₁₀, O₃, and NO₂) in 2020 in the six regions of China. The study used the air pollution effect contribution index (APECI) to identify contributions contrasting different land use types to the air pollutants in different pollutant concentration ranges. [Results] (1) In 2020, the highest regional annual average concentrations of PM_2.5 and PM₁₀ occurred in Northwest China and the lowest in Southwest China; NO₂ and O₃ had the highest regional annual average concentrations in East China, which were 25.23 μg/m³ and 102.60 μg/m³, respectively. (2) Air pollutant concentrations showed a nonlinear response relationship with the proportion of grid-based land use area. Generally, the increase in the proportion of the grid areas of farmland, construction land, and unused land led to an upward trend in the air pollutant concentration, while forest land and grassland often showed the opposite. (3) With regard to the differences in APECI, forest land and grassland showed a high APECI in the low air pollutant concentration ranges, while farmland and construction land showed a high APECI in the high air pollutant concentration ranges, but the APECI of water area and unused land varied in different regions. [Conclusion] This study proposed the possible overall effect of gridded land use area proportion on air pollution based on regional differences across China, providing a reference for regional joint prevention and control of air pollution and territorial spatial planning.

[Objective] Northeast China, with its unique resources advantages, provides one-third of China’s commodity grain, making it a crucial part of national food security. Analyzing the spatial distribution, spatiotemporal evolution, and driving forces of grain crop cover types and cropping patterns in Northeast China is crucial for preserving the region’s “black soil granary”. [Methods] Based on Google Earth Engine (GEE), this study integrated existing crop cover type product from 2017 to 2019 with remote sensing extraction results of major grain crops from 2019 to 2021, analyzed the spatiotemporal change characteristics of grain crop planting types and cropping patterns, then revealed the driving forces by using geodetector. [Results] (1) Using phenological information, a multi-feature random forest classification method was employed to effectively extract three major grain crops: maize, soybean, and rice. In 2019, a high Kappa coefficient of 0.908 was achieved, indicating high classification accuracy and consistency in terms of area. (2) In the past five years, the shifting of grain crops from soybeans to maize has been the dominant trend in Northeast China. The shift types include soybean to maize to maize, soybean to soybean to maize, and maize to maize to soybean, accounting for 29.4%, 24.9%, and 19.1% of the total transition area, respectively. The cropping patterns of grain crops in Northeast China exhibit high spatial heterogeneity, with the maize continuous cropping pattern, rice continuous cropping pattern, and soybean-maize continuous-preference rotation pattern accounted for 46.2 %, 23.5 %, and 13.2 % of the total cropping patterns area, respectively. (3) The spatiotemporal dynamics of cropping patterns was significantly driven by natural and anthropogenic factors. Elevation, topographic wetness index, slope, rice price fluctuation, and soybean price fluctuation were important single factors that explain the spatiotemporal changes of cropping patterns. The interactive explanatory power of elevation, active accumulated temperature slope, and economic policy factors was high, and in descending order from elevation∩soybean subsidy variation, elevation∩active accumulated temperature slope, elevation∩fertilization cost variation, elevation∩rice subsidy variation, to elevation∩maize price variation. [Conclusion] During the period from 2017 to 2021, there was a notable shift in the major grain crop cover types in Northeast China, characterized by a transition from soybean to maize, while rice cultivation remained consistent. The spatial distribution of different cropping patterns was influenced by a combination of factors including topography, economy, and policy.

[Objective] Facing the global issue of “carbon peak and carbon neutrality”, this study aimed to predict and simulate carbon emissions from energy consumption, explore the feasibility of carbon peaking and carbon neutrality time, and provide theoretical basis for promoting emission reduction. [Methods] In this study, the carbon emission coefficient method was used to calculate the carbon emissions from energy consumption in China from 1986 to 2019. Considering factors from the five aspects of economy, society, environment, energy, and technology, an indicator system including 18 variables was established, and five main factors were screened out by Lasso regression. Based on three machine learning methods and Lasso regression, six carbon emission prediction models including support vector regression (SVR), random forest (RF), back propagation neural network (BP), Lasso-SVR, Lasso-RF, and Lasso-BP were constructed. The models were evaluated based on the mean squared error (MSE) and mean average error (MAE). Combined with the scenario analysis method to set four scenarios of new normalization, green low-carbon, 2 ℃ target, and 1.5 ℃ target, the best prediction model was selected to simulate and analyze China’s energy consumption carbon emissions from 2020 to 2060 under the four scenarios. [Results] Under the four scenarios, with the intensification of emission reduction efforts, China’s carbon peaking platform period is shortened. The time points of carbon peak during the platform period in China are 2035, 2030, 2026, and 2025 respectively, and the peak values are 9.580, 7.448, 6.723 and 6.523 Gt CO₂e. Under the 2 ℃ and 1.5 ℃ scenarios, China can achieve carbon neutrality as scheduled. Under all four scenarios China may achieve the 2 ℃ temperature rise target, but under the first two scenarios China will not achieve the 1.5 ℃ target. [Conclusion] Under the four scenarios, the peak value and peak time of China’s energy consumption carbon emissions are different, and the possibility of achieving carbon neutrality is also different. In order to achieve the goals of carbon peak and carbon neutrality as soon as possible, China must promote the optimization of industrial structure and energy system structure, increase investment in green assets, and help the development of emission reduction with technological progress.

[Objective] Facing the target constraints of “carbon peak and carbon neutrality”, this paper discusses the impact of different carbon trading policy tools on the effect of pollution reduction and carbon reduction, and provides theoretical basis for the green and low-carbon transformation of regional economy. [Methods] Based on the data of 30 provinces in China’s mainland from 2003 to 2021, this study constructed a coupling coordination model incorporating CO₂ and SO₂, and applied a two-way fixed-effects difference-in-differences model to analyze the pollution reduction and carbon emission reduction effects of carbon trading policies and their mechanisms. Furthermore, we explored the pollution reduction and carbon emission reduction effects of carbon market policy tools. [Results] The results show that: First, carbon trading policies significantly reduced the coupling and coordination degree between carbon emissions and environmental pollution, resulting in pollution reduction and carbon emission reduction, and gradually tended towards a collaborative relationship of “high-level coupling and high-quality coordination”. Second, the results of heterogeneity test show that the impact of carbon trading policy on the coupling degree and coordination degree of carbon emissions and pollution in Beijing, Shanghai, and Guangdong was greater than that in Tianjin, Hubei, Chongqing, and Fujian, and the impact on the coupling degree and coordination degree of carbon emissions and pollution in areas with relatively low carbon emissions was more significant. Meanwhile, the carbon reduction effect of carbon market policy was higher than that of pollution reduction. Finally, the pollution reduction and carbon emission reduction effects of carbon trading policies were mainly realized by carbon prices, carbon market activity, carbon market size, and punishment tools through the impact of industrial structure, energy structure, and technological progress. Various policy tools also had the effect of optimizing industrial structure, as well as reducing differences between industries, but they did not significantly improve the cleanliness level of energy structure and promote the level of green technology innovation. [Conclusion] In order to achieve a win-win situation of synergetic control of environmental pollution and carbon emissions, it is necessary to take the following measures: Establishing and improving a collaborative control system for carbon emissions and environmental pollution, improving green low-carbon technologies and pollution control technologies, achieving industrial structure upgrading and energy structure transformation, expanding the carbon market scale, and improving carbon market policy tools.

[Objective] Enhancing economic resilience of cities is key to achieving sustainable urban development. With the increasing differentiation in urban population growth, exploring the mechanisms of impact of population growth and shrinkage on urban economic resilience is crucial for strengthening urban resilience and addressing uncertain risks. [Methods] Based on the panel data of 280 prefecture-level and above cities in China from 2008 to 2019, this study employed fixed effect models and moderating effect models to empirically test the mechanisms of impact of population growth and shrinkage on urban economic resilience. [Results] The study found that: (1) Population growth and shrinkage have a significant impact on urban economic resilience, with a greater effect on the cities’ ability to withstand risks than on their economic recovery capabilities. (2) Mechanism analysis result indicates that industrial structure and human capital level played a positive moderating role in the impact of population growth and shrinkage on urban economic resilience. (3) The effects of industrial structure upgrading and human capital varied with city size and resource endowment, with the industrial structure upgrading effect more pronounced in large cities and non-resource-based economic regions. [Conclusion] Improving the level of human capital and accelerating industrial agglomeration and upgrading are important strategies to enhance urban economic resilience in the context of population growth differentiation. The findings of this study can provide important references for different regions to formulate sustainable development paths adapted to population growth or shrinkage.

[Objective] As an important part of the energy system, renewable energy is one of the key driving forces to build the low-cost, clean and low-carbon, safe, and efficient new energy system. Exploring the regional differences, distribution dynamics, and convergence of China’s renewable energy development level will help to deeply understand the current situation and evolution trend of China’s renewable energy development level, and provide policy guidance for China to further promote the energy revolution, build a new energy system, and achieve the dual carbon goals. [Methods] Based on China’s provincial panel data from 2006 to 2019, Dagum Gini coefficient, Kernel density, σ convergence, and spatial β convergence were used to analyze the detailed characteristics of China’s renewable energy development level. [Results] (1) The renewable energy development level in China and the four regions of eastern, central, western, and northeastern China exhibited a steady rising trend, and the average annual growth rate in the Northeast was the highest; (2) The intraregional differences in the whole country and the four regions gradually decreased. The interregional imbalance was the main source of the overall difference, and its impact on the overall difference was increasing. (3) With regard to the distribution dynamics, the development level of renewable energy in China exhibited a significant spatial correlation. Polarization occurred in the four regions, but gradually weakened. (4) On the convergence side, the renewable energy development level of China as a whole and the four regions all showed the characteristics of σ convergence and β convergence, which was the strongest in the Northeast and the weakest in western China. [Conclusion] The development level of renewable energy in China possesses great potential for further improvement, and exhibited obvious regional differences and spatial spillover effects. Therefore, the Chinese government should attach importance to the development of renewable energy, and different regions should formulate differentiated incentive policies according to local conditions. The regions should strengthen regional exchanges and cooperation, promote mutual interaction, and jointly contribute to the realization of the dual carbon goals.

[Objective] The issue of carbon emission efficiency is of great significance to the realization of the “dual carbon” goal. To reveal the impact of land resource misallocation on carbon emission efficiency, and to explore its path, it provides a scientific basis for promoting regional green and low-carbon development from the perspective of land resource allocation. [Methods] Based on the theory that land resource misallocation affects carbon emission efficiency, and using the spatial Durbin model and mediation effect model, this study examined the spatial effect of land resource misallocation on carbon emission efficiency and mechanism of 108 cities in the Yangtze River Economic Belt from 2004 to 2020. [Results] (1) The indirect effect of land resource misallocation on carbon emission efficiency is far greater than the direct effect, and the preferential allocation of land will do more harm by the negative externalities of neighboring cities. (2) For different locations and cities of different sizes, land resource misallocations and their spatial effects vary greatly. (3) Land resource misallocation has a complex mechanism for affecting carbon emission efficiency, which can reduce regional carbon emission efficiency through inhibiting innovation ability development, slowing industrial structure upgrading, and blocking new-type urbanization. [Conclusion] In order to improve regional carbon emission efficiency, the Chinese government should accelerate the market-oriented reform of land factor allocation, strengthen the concept of regional cooperation and win-win cooperation and collaborative governance capacity. Based on these results, we argued that increasing the support for technological innovation, optimizing the industrial structure, and actively and orderly promoting new-type urbanization are the effective ways to increase carbon emission efficiency in the future.

[Objective] Low-carbon transition is an international consensus, accelerating low-carbon development is the focus of the work of all countries in the world, therefore it is necessary to explore the impact of geopolitical risks, a major risk-causing factor, on the process of low-carbon transition in countries. [Methods] Based on a systematic elaboration of the impact of geopolitical risks on the low-carbon transition process of each country, this study empirically examined the impact of geopolitical risks on countries’ low-carbon transition and regulatory role based on the national panel data and geopolitical risk index from 2010 to 2020, and the moderating effect model. [Results] (1) Geopolitical risks can significantly slow down the process of national low-carbon transition, and this result still holds after sample truncation, replacement of explanatory variables and explained variables, and placebo test; (2) The negative moderating effects of financing constraints and trade barriers are significant, exacerbating the disincentive effect of geopolitical risk on countries’ low-carbon transitions, while green technology R&D capacity positively moderates the relationship between geopolitical risk and countries’ low-carbon transitions; (3) Optimizing the industrial structure and the green technology development capacity is the most important mechanism for the low-carbon transition of countries; (4) In regions with a high level of geopolitical actions and threats, the inhibition of geopolitical risks on the process of their low-carbon transition is more pronounced, and this adverse impact is more obvious in developing countries than in developed countries. [Conclusion] Countries should pay attention to the adverse impact of geopolitical risks in the process of national low-carbon transition, pay attention to financing constraints, and actively optimize industrial structure and improve renewable energy production capacity, so as to hedge the negative impact of geopolitical risks and accelerate the process of low-carbon transition.

[Objective] Revealing the determining factors of the spatiotemporal differentiation of non-grain conversion of cultivated land under the participation of multiple stakeholders is of great significance for alleviating the conflict between food production and economic benefits. [Methods] Using GIS spatial analysis tools and the theory of tripartite evolutionary game, this study conducted numerical simulations of the strategies of various stakeholders under different spatial zoning of non-grain cultivation, and the determining factors of the temporal and spatial differentiation of non-grain cultivation on arable land were obtained in Liaoning Province. [Results] The results show that: (1) From 2000 to 2020, the curves of non-grain rate and non-grain area of cultivated land in Liaoning Province fluctuated periodically, showing a downward trend as a whole, and the non-grain rate showed the distribution characteristics of ‘high in the north and low in the south, high in the west and low in the east’ in space, and the area of high value area decreased significantly. (2) Policy implementation level, policy subsidies provided by local governments and farmer income were the determining factors for the tripartite evolutionary game of stakeholders in cultivated land non-grain conversion in Liaoning Province. (3) Among the three equilibrium scenarios of the tripartite game of multiple stakeholders, policy implementation level of local governments played a leading role in strategy selection of the three types of stakeholder, and the strategy choice of industrial and commercial capital had a critical impact on the implementation of policies to prevent cultivated land non-grain conversion. [Conclusion] The non-grain production use of cultivated land was a result of the complex interaction of multiple stakeholders with different interests, and the strategies and determining factors for different stakeholders varied significantly across different spatial zones.

[Objective] The Yellow River Basin has a large number of resource-based cities, and promoting the transformation of resource-based cities is of great significance for the high-quality development of the Yellow River Basin economy. Clarifying the progress and characteristics of industrial transformation in resource-based cities in the Yellow River Basin will help to formulate development policies in a more targeted manner. [Methods] In order to analyze the progress and characteristics of industrial transformation of resource-based cities in the Yellow River Basin, this study established a metric indicator system for the level of resource-based cities’ industrial transformation, quantitatively analyzed the spatiotemporal characteristics of the industrial transformation of 20 resource-based cities in the basin, and divided the industrial transformation of resource-based cities into four types by the level of transformation, the share of the output value of the mining industry, and the development of the substituting industries, and summarized and analyzed the paths and modes of industrial transformation of different types. [Results] The study found that: (1) As an important national energy and heavy chemical industry base, the overall process of industrial transformation of the 20 resource-based cities in the Yellow River Basin is relatively slow. Most of the resource-based cities are characterized by a single structure of industrial sectors, a high proportion of the output value of the mining industry, a low proportion of the production value of foreign and Hong Kong, Macao, and Taiwan investment enterprises, a small scale of the output value of the substitution industries, and unbalanced distribution of the sectors, and the overall level of industrial transformation is characterized by a spatial feature of “low in the middle and upper reaches and high in the lower reaches”. (2) Resource-based cities in the middle and upper reaches of the basin are mostly in the growth or maturity period, the type of industrial transformation is dominated by deepening transformation and slow transformation, and the transformation mode is mainly to mineral resources processing industry, which has the characteristics of path extension and dependence; Resource-based cities in the upper and lower reaches of the basin are mostly in the period of decline or regeneration, the type of industrial transformation is dominated by synergistic transformation and transitional transformation, the transformation mode is mainly to non-resource-processing substitution industries, and in addition to having the characteristics of path extension, the transformation is also path implantation, path creation, and path diversification. [Conclusion] Continuously promoting the transformation of resource-based cities in the Yellow River Basin and improving the resilience of the industrial economy is an important guarantee for realizing the high-quality development of the Yellow River Basin economy. Resource-based cities in the upstream and downstream areas should make full use of the conditions of transportation location, industrial foundation, and natural environment, and expand and strengthen the substitution industries according to local conditions; resource-based cities in the middle reaches should efficiently develop and utilize resources, improve the level of deep processing of resources, and promote the diversification of substitution industry development.

[Objective] Intensive use of cultivated land serves as an effective approach to ensure the efficient supply of agricultural products and sustainable use of cultivated land. Scientific knowledge of the spatial and temporal differentiation characteristics of unbalanced and inadequate intensive use of cultivated land as well as a precise understanding of the existing shortcomings of the intensive use of cultivated land, is crucial for unlocking the potential of land resources and enhancing the comprehensive capacity of agricultural production. [Methods] This research measured the level of intensive use of cultivated land in China and its four main regions from 2000 to 2020 across four dimensions: input intensity, utilization degree, output efficiency, and sustainability. The Dagum Gini coefficient was used to investigate the spatial imbalance of intensive use of cultivated land and its structural sources. The quantile normalization approach was used to investigate inadequate utilization of cultivated land and its mechanism. [Results] The results indicate that: (1) There were considerable variations in the level of intensive use of cultivated land throughout the nation and the four regions, although the general trend was continually growing. The provinces with low levels of intensive use of cultivated land saw a catch-up effect. (2) The imbalance of intensive use of cultivated land showed a declining tendency at the national level. More than 70% of the spatial imbalance of intensive use of cultivated land was caused by the imbalance between regions. (3) A declining trend was visible in the inadequacy index of intensive use of cultivated land for all regions and nationwide, with an order of western region (80.94), Northeast (74.33), nationwide (68.14), central region (60.16), and eastern region (55.72). (4) The sustainability of land use emerged as a key factor in the imbalance and inadequacy of intensive land use nationally and in the eastern and central regions. Input intensity significantly impacted the imbalance and inadequacy of intensive use of cultivated land in the Northeast, while in the western region, all four dimensions were highly significant. Additionally, there was a trend toward an inward convergence in the change of the primary influencing factors in each region. [Conclusion] In China, the unbalanced and inadequate intensive use of cultivated land have somewhat improved over the past 20 years, but there is still a sizable regional imbalance and insufficiency. To increase the overall agricultural production capacity, it is critical to increase the intensive use of cultivated land in accordance with the current and local conditions and to establish a systematic, coordinated pattern of such usage.

[Objective] In the new economic development era, actively integrating into regional innovation networks has become an important way for cities to obtain external innovation resources and enhance their independent innovation capabilities. This study aimed to reveal the spatiotemporal patterns and mechanisms of change of collaborative innovation in the Yangtze River Delta region from a network perspective, and put forward policy recommendations for regional innovation space optimization and high-quality development. [Methods] Based on the co-application data of invention patents, the intercity collaborative innovation networks of 41 cities in the Yangtze River Delta region were constructed for six periods from 2010 to 2020. The characteristics of change of the regional collaborative innovation networks were further investigated through network descriptive analysis and the underlying endogenous and exogenous driving forces were explored through the temporal exponential random graph models. [Results] (1) The intercity collaborative innovation networks in the Yangtze River Delta presented the co-existence of hierarchical structures and clustering structures, as well as remote trans-local linkages and proximate local linkages. Shanghai, Hangzhou, and Nanjing were always the top three in terms of innovation collaboration, and the innovation corridor along Shanghai, Nanjing, Hangzhou, Hefei, and Ningbo became evident. Regional collaboration clusters were highly coupled with administrative divisions and gradually evolved into three communities bounded with provincial boundaries and centered on the cities with high administrative levels, i.e., Jiangsu-Shanghai community, Zhejiang local community, and Anhui local community. Except for Hefei, the development of cities in Anhui Province was more localized and marginalized. (2) The scale and strength of networks increased gradually while the overall change of the networks was stable. The overall structural similarity between the current network and its previous network exceeded 80%. The hierarchical structure tended to converge whereas clustering structures were continuously strengthened, thus the networks were developing towards a balanced and clustering pattern with dense collaboration among multiple cores. (3) In addition to the urban innovation endowments, network change was mainly driven by time dependence, structure dependence, provincial boundary effect, and geographical proximity. [Conclusion] There is still much room for the improvement of regional collaborative innovation in the Yangtze River Delta region. It is necessary to further enhance the efficient flow of innovation resources, promote the development of regional integration with high-density and small-scale cooperation, and strengthen the exploration and encouragement of new modes and mechanisms of intercity technology collaboration, so as to break the path dependence, administrative hierarchy and regional barriers to innovation collaboration.

[Objective] Cultivated land resources are the main material basis for food production. Analyzing the characteristics of the spatial and temporal changes of cultivated land resources in the typical black soil region has important reference value for optimizing the allocation of cultivated land resources. [Methods] Based on the land use data of four periods from 1986 to 2020 in the typical black soil region of Northeast China, the quantitative change of cultivated land resources characterized by the increase and decrease of cultivated land area were revealed. Taking the change of cultivated land spatial pattern as the breakthrough point, the characteristics of cultivated land resource quality change represented by site conditions were analyzed. On this basis, the driving factors of spatial and temporal changes of cultivated land resources were analyzed. [Results] (1) From 1986 to 2020, the area of cultivated land in the typical black soil region in Northeast China had been increasing, with a net increase of 2.51 × 10⁴ km², of which the largest increase occurred from 1986 to 2000, and the areas with more dramatic changes in cultivated land were concentrated in the southern foot of the Greater Xing’an Mountains, the Sanjiang Plain, and the areas surrounding the three provincial capital cities of the region; (2) For more than 30 years, due to the continuous movement of the center of gravity of the cultivated land to the northeast, the average temperature of the cultivated land area in the typical black soil region decreased by 0.20℃, the average humidity increased by 0.12%, and the average slope showed the change characteristics of first increasing and then decreasing; Compared with the transferred-out farmland, the temperature condition of the farmland that was transferred in was always poor, the humidity condition was generally superior, the slope condition was poor at the beginning, and better than the transferred-out farmland at a later stage; (3) In areas with low temperature (-1℃-2℃), high humidity (67%-71%), and high slope (15°-79°), cultivated land was frequently transferred in and out, with dramatic changes. [Conclusion] From 1986 to 2020, the area of cultivated land in the black soil region continued to increase, and the center of gravity continued to move northward and eastward, making the overall temperature conditions of cultivated land area worse, the humidity conditions better, and the terrain conditions basically stable. This result provides a reference for accurately judging the grain production capacity of the black soil area and scientifically utilizing and protecting the black soil.

[Objective] Northeast black soil cultivated land (BSCL) is crucial for the country’s food and ecological security. Defining its concept and grasping the spatiotemporal dynamics is vital for sustainable resource use and regional development. [Methods] This article, based on the theory of critical zone of the Earth, redefined BSCL and combined regional soil data with land use data in 1980, 2000, and 2020. It used methods of overlay analysis and spatiotemporal analysis of land use to reveal BSCL evolution patterns and drivers over 40 years. [Results] (1) BSCL refers to cultivated land with black soil types, primarily located in the temperate zone of Northeast China, with elevation mostly below 500 m and soil predominantly composed of meadow soil. (2) Due to the impacts of climate, economic, policy and institutional factors, the area of BSCL increased by 4.12 million hm² over 40 years. However, due to policy interventions, the increase has significantly decreased since 2000. (3) Spatially, due to the transfer of population and economic center of gravity, the overall spatial pattern of BSCL in Northeast China showed northward expansion and southward contraction. The gravity center of BSCL has been continuously moving northward, but the speed of migration has slowed down after 2000. (4) Forest and construction land were the main destinations for the transition of BSCL, while forests and grasslands are the principal sources contributing to the increase in BSCL. Influenced by policies and institutional interventions, the dynamic conversions of BSCL have undergone frequent since 2000. [Conclusion] Influenced by natural and socio-economic factors, the area of BSCL in Northeast China has significantly expanded over the past 40 years, continuously spreading northward. However, there is a obvious decreasing tendency in both the scope and speed of this expansion. This study can provide a methodological reference for the analysis of BSCL and a scientific basis for the conservation and sustainable utilization of BSCL.

[Objective] The construction of high-quality low-carbon cities is an important measure to address climate change issues, implement the concept of low-carbon development, and achieve the “dual carbon” goals, Therefore,the significance of examining the carbon emission reduction effect of low-carbon pilot cities policy is prominent. [Methods] Based on the panel data of 216 cities in China from 2006 to 2019, this study used the second and third batch cities of the low-carbon city construction pilot program for a quasi-natural experiment. Using the propensity score matching and difference-in-differences (PSM-DID) method and based on the robustness test results, this study analyzed the impact of low-carbon city construction on urban carbon emissions in multiple dimensions, and it used an mediation effect model to investigate the mechanism of impact of the low-carbon pilot program. [Results] (1) Compared with non-pilot cities, low-carbon pilot program participating cities significantly reduced urban carbon emissions, which remained significant after the inclusion of parallel trends and placebo robustness tests. (2) The low-carbon city pilot program can play a role in carbon reduction by improving the level of urban green technology innovation, adjusting industrial structure, and reducing energy consumption. (3) The carbon emission reduction effect of the low-carbon city pilot program had significant heterogeneity. The carbon emission reduction effect in eastern and central cities and non-resource-based cities was stronger than that in western cities and resource-based cities. The effect of the low-carbon city pilot program on carbon emission reduction was more obvious in the cities to the south of the Hu Huanyong Line than in cities to the northwest of the line. [Conclusion] This study evaluated the phased effect of carbon emission reduction of the second and third batch cities of the low-carbon city construction pilot program from a multi-dimensional perspective, which will help deepen the understanding and explore the path of low-carbon development, and provide references for more cities to systematically build low-carbon cities in the future. Under the new situation, the construction of low-carbon cities should follow the local conditions and change with time, develop differentiated and precise pathways to promote green development, and lay the foundation for the realization of the “30·60” carbon peak and carbon neutrality goals.

[Objective] A comprehensive assessment of soil erosion in the black soil region of Northeast China is essential for deepening our understanding of issues such as the control of regional water and soil losses, anti-degeneration of black soil, preservation of land fertility, and safeguard of national food security. [Methods] Based on the Revised Universal Soil Loss Equation (RUSLE) and the Revised Wind Erosion Equation (RWEQ) models, this study comprehensively assessed the water and wind erosion on farmland in the black soil region of Northeast China from 2000 to 2020 and analyzed the current situation, the spatial and temporal change of soil erosion, and the influence of changes in land use. [Results] The results suggest that: (1) The degree of soil erosion on farmland in the black soil region of Northeast China was mainly slight, and water erosion was more severe than wind erosion. The Changbai Mountains region and the Liao River Plain have undergone relatively intensive water erosion, while the wind erosion in the Liao River Plain, the Greater Kinggan Mountains region, and the Songnen Plain was more intensive than in other sub-regions. (2) Water erosion showed a decreasing trend in the past 20 years, especially in the Liao River Plain. It increased firstly and then decreased in the two decades, and the second decade (2010-2020) has seen a certain extent of alleviation compared with the first decade (2000-2010). (3) Wind erosion showed a slowing trend in the past 20 years. The wind erosion in the Liao River Plain and the wind erosion region decreased more obviously. Wind erosion showed a significant interannual decrease first and then a small increase. (4) There were differences in the effects of cropland change on water erosion and wind erosion changes in the black soil region of Northeast China over the 20 years. Water erosion was mitigated in the areas of fallowing and reclamation, and increased in the areas of paddy and other cropland conversion; fallowing and urban expansion had a positive effect on mitigating wind erosion. The effects of cropland change on water and wind erosion changes were more obvious in the first decade than that in the second decade. [Conclusion] Soil erosion is caused by multiple factors, such as climate, topography, soil type, and human activities. This study provides some reference for soil erosion control and management in Northeast China. In the regions with severe erosion, we can adopt methods like zero tillage, cross ridge tillage, and straw mulching according to the local characteristics of soil erosion to slow down the process.

[Objective] The purpose of this study was to explore the spatiotemporal responses of cultivated land conversion to different driving factors and their interactions in southern Shaanxi Province, to gain a more scientific and objective understanding of cultivated land non-grain conversion, which provides references for the formulation of food security policy and the guidance of appropriate non-grain conversion of cultivated land. [Methods] Based on the county-scale data of non-grain conversion of cultivated land of southern Shaanxi Province from 2005 to 2020, this study analyzed 30139 valid samples through a spatiotemporal variability model and the geographical detector model to explore the spatiotemporal evolution and driving factors of non-grain conversion. [Results] The results are as follows: (1) Temporally, the rate of non-grain conversion of cultivated land in southern Shaanxi showed a general upward trend, with obvious differences among cities. The spatial pattern of cultivated land conversion changed from high-low to low-high from west to east in southern Shaanxi, with Chenggu County in Hanzhong City in the west and Shangnan County and Luonan County in Shangluo City in the east as the centers, and areas with the medium-high and high conversion rates were concentrated at the periphery of the Hanzhong, Ankang, and Shangdan Basins. Generally, the spatiotemporal variation rate of non-grain conversion was high in the peripheral areas of Ankang and Shangdan Basins and low in others. (2) The temporal process of driving factors was highly dynamic, and its internal spatiotemporal interaction has neutralization effects on driving forces. The overall explanatory power of socioeconomic factors was stronger, and annual precipitation and GDP were the natural and socioeconomic factors with the highest explanatory power for the spatiotemporal variability of regional non-grain conversion of cultivated land. (3) The interactions of factors showed bivariate enhancement and non-linear enhancement effects, and there was no independent situation after the interaction. Moreover, the spatiotemporal dynamics of non-grain conversion were significantly influenced by the interaction of socioeconomic factors, and natural factors increased the driving effect of human factors. [Conclusion] We recommend that measures should be taken to address the issue of cultivated land non-grain conversion, by strengthening the construction of farmland water conservancy facilities, scientifically defining the bottom line of farmland non-grain conversion, balancing urban and rural resource investment, and creating strict land-use control institutions.

[Objective] As an innovative way of regulating territorial space, the planning of flexible space is of great significance for improving the scientific quality and effectiveness of spatial planning, and reducing the disturbance and impact of uncertain factors. This study aimed to explore the delineation of land use layout flexible space under uncertain conditions. [Methods] The study took Xuzhou City, a typical resource-based city, as an example. First, an interval optimization model was used to obtain the flexible quantity interval of various land use types. Then, the upper and lower limits of the interval served as the quantity demand to import the PLUS model to simulate the spatial layout of various land use types, and the difference between the two simulated layouts was designated as flexible space. [Results] The results show that: (1) There are differences in the size of the flexible quantity interval of each land use type, among which land use types that contribute more to addressing future uncertainty are rural residential land, farmland, water, urban industrial and mining land, while the smaller ones are grassland and bare land. (2) The flexible space distribution of various land use types shows a certain pattern, and the flexible space of farmland is concentrated in the hotspots of land use change around urban and rural areas, the flexible space of garden plot and woodland is distributed in suitable growth areas such as river banks and low hills, and the flexible space of urban industrial and mining land and rural residential land is mainly distributed in the outer edge areas of their original scope. (3) Based on the flexible space of each land use type, the land types were merged according to the zoning function of the planning, and the conflicting parts of the flexible space were processed according to the suitability to obtain the flexible space of different spatial planning zones. Among them, the flexible space areas of agricultural production zones, ecological protection zones, urban construction zones, and rural development zones account for 1.74%, 0.20%, 1.09%, and 3.31% of the total area, respectively. [Conclusion] The probability distribution of possible conflicts in land use space is the prerequisite for the delineation of flexible space. It is necessary to delineate flexible space of land use layout from an uncertain perspective. Based on interval optimization and PLUS model, the delineation method of flexible space proposed in this study seems feasible, which can provide support for planning decisions.

[Objective] Building a new type of electric system based on renewable energies, such as wind power and photovoltaic power, is an important measure to achieve carbon neutrality. China has a vast land area with significant differences in energy resource endowment, energy production structure, economic development level, and regional specialization for energy production. To achieve the “dual carbon” goals at a national scale, it is necessary to implement regionally differentiated action plans. [Methods] Starting from the analysis of the seven major power grid regions in China, using the methods of life cycle assessment and GIS-MCDA model, combined with the future electricity demand and proportion of each province, to quantify the environmental impact of energy and power system transformation on the Chinese region. [Results] The results of this study show that: (1) From 2015 to 2020, the environmental pressure on China and each of its seven regions continuously increased, with the East China and North China regions being the main emitting areas. (2) From 2025 to 2060, building an energy system based on new energy sources can greatly reduce the environmental pressure, except for the non-biomass exhaustion potential. (3) Overall, coal-based power generation has a higher environmental impact than other energy types (except for non-biomass exhaustion potential), and hydroelectric power generation has the smallest environmental impact among the five selected energy types. [Conclusion] The research results can provide a scientific basis for China to achieve the “dual carbon” goals through energy transformation, and also have some reference value for the government to make improved policy decisions.