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Mitigating agricultural carbon emissions is pivotal for attaining the objectives of carbon peak and carbon neutrality. Utilizing a time-varying parametric Cobb-Douglas (C-D) production function, this study employs an enhanced Logarithmic Mean Divisia Index (LMDI) decomposition approach, the Tapio decoupling model, and Monte Carlo simulations to investigate the determinants and decoupling dynamics of agricultural carbon emissions within Sichuan Province from 2010 to 2020. The findings reveal that: (1) Factors such as carbon emission intensity, agricultural structure, labor inputs, and capital stock played a significant role in suppressing agricultural carbon emissions, collectively contributing to a reduction of 484.12 million tonnes. (2) The unstable decoupling of agricultural carbon emissions from economic development in Sichuan Province. Capital stock, alongside carbon emission intensity and agricultural structure, significantly contributed to this decoupling. To harmonize agricultural economic growth with carbon emission reduction, emphasis should be placed on manure management and resource utilization in livestock and poultry farming. Furthermore, leveraging technological advancements to enhance resource efficiency is crucial for reducing carbon emissions. Simultaneously, strategic management of fixed asset growth, focused on energy conservation, can catalyze the synergistic effects of economic development and technological spillovers. [ABSTRACT FROM AUTHOR]

The global climate change caused by carbon emissions presents obstacles to the sustainable development of villages around the globe. In China, the world’s greatest carbon emitter, the construction of villages generates substantial carbon emissions. This study employs quantitative and qualitative methods to evaluate the efficacy of future smart villages by developing a model under the “Carbon peaking and carbon neutrality” objective. Based on the indicators provided in the local government documents and normative documents at all levels and in conjunction with the “Carbon peaking and carbon neutrality” objective, this study establishes a system for evaluating the efficacy of the implementation of the future smart village construction using an analytical hierarchy process and fuzzy comprehensive evaluation method with 10 criteria levels and 60 program levels. The research team obtained the necessary information and data through questionnaires and in-depth interviews with local administrative cadres, pertinent professionals, and villagers. The results indicate that intelligent future village construction can reduce the village’s carbon emissions. The “Industry” indication is the most essential element. The term “Industry” is essential to the development of intelligent future villages as well as to the carbon reduction of villages. “Low carbon and energy” is the second factor. Industrial modernization, low-carbon development, and the use of renewable energy in the villages have significantly contributed to reducing carbon emissions and the viability of the villages. As the Future smart village is currently being implemented, the research indicates that there are few samples and data available. Consequently, future research must continue to increase sample size and data.” This research can scientifically and rationally evaluate the construction of the Future smart village and provide a strategy for optimizing the construction model for rural revitalization.

Under the background of "carbon peak and carbon neutrality", the interconnection of multiple regional integrated energy systems has become an important way to coordinate multiple energy sources and save energy and reduce emissions. This paper proposes a low-carbon economic dispatch model for multi-regional integrated energy systems considering the joint demand response mechanism; first, the concept and model of joint demand response are proposed, and on this basis, the energy conversion model between multiple energy forms in the multi-regional integrated energy system is studied; secondly, green certificate trading and carbon trading mechanisms are introduced, and green certificate trading and carbon trading are combined through the green certificate emission reduction mechanism; finally, a low-carbon economic dispatch model is proposed with the goal of minimizing the sum of system energy purchase cost, green certificate trading cost, carbon trading cost and joint demand response compensation cost. The example results show that the introduction of joint demand response mechanism and green certificatecarbon trading mechanism in the multi-regional integrated energy system reduces the total system cost and carbon emissions by 14.03% and 26.04% respectively. [ABSTRACT FROM AUTHOR]

Coalbed methane is released externally due to coal mining activities. Given its low concentration, which renders utilization challenging, China annually vents approximately 285 billion cubic meters of coalbed methane into the atmosphere, leading to significant energy waste and greenhouse gas emissions. To enhance the utilization rate of coalbed methane, mitigate these emissions, and promote a "green and low-carbon" energy supply, this article investigates pressure swing adsorption technology for purifying coalbed methane and analyzes the advantages, disadvantages, and application scopes of three processes: separation based on equilibrium effects, kinetic effects, and steric hindrance effects. The research findings reveal that equilibrium effect-based adsorption is particularly advantageous for purifying low-concentration coalbed methane, effectively capturing methane (CH4). Conversely, when dealing with medium- to high-concentration coalbed methane, methods leveraging kinetic effects prove more favorable. Within the context of equilibrium effects, activated carbon serves as a suitable adsorbent; however, achieving high-purity products entails substantial energy consumption. The methane saturation adsorption capacity of novel activated carbons has reached 2.57 mol/kg. Kinetic effect-based adsorbents, primarily carbon molecular sieves and zeolite molecular sieves, are characterized by lower energy demands. Currently, coal-based molecular sieves have achieved a CH4/N2 equilibrium separation factor of 4.21, and the amount of raw coal required to produce one ton of carbon molecular sieve has decreased to 2.63 tons. In light of the rapid advancement of intensive coal mining operations and the swift implementation of smart mine construction, there is an urgent need to intensify research on large-scale purification technologies for low-concentration coalbed methane. This will provide the technical foundation necessary for achieving "near-zero emission" of mine gas and facilitate the achievement of the goals of carbon peak and carbon neutrality. [ABSTRACT FROM AUTHOR]

In the context of the global implementation of the emission peak and carbonneutral strategic goal, guiding residents' low-carbon behavior is of great significance for the realization of the dual carbon goal. However, existing studies have paid less attention to the low-carbon behavior of college students. Based on the theory of planned behavior, this paper constructs a theoretical model of influencing factors of college students' low-carbon behavior. Combined with 612 questionnaires from Chinese colleges and universities, this study uses a structural equation model and multi-group analysis method to explore the motivation of college students' low-carbon behavior and guiding education strategies. The results show that low-carbon attitude, subjective norms, low-carbon values, and perceived behavior control have significant positive effects on low low-carbon behavior intention of college students, and influence their low-carbon behavior through low-carbon behavior intention. Further research found that gender and growth environment (urban vs. rural) presented heterogeneity in different influence paths, and the perceived cost had a significant negative moderating effect during the transition from low-carbon intention to low-carbon behavior. These research findings provide a theoretical basis and policy inspiration for explaining and guiding the low-carbon behavior of college students. [ABSTRACT FROM AUTHOR]

Carbon peaking and carbon neutrality goals have put forward new requirements for the development of sustainable energy. As an important part of the energy system, the power system plays an important role in achieving sustainable energy development. Future power systems will be sustainable, with a high proportion of renewable energy such as photovoltaic and wind power. With advancements in technology and the sustainable development of power systems, the construction costs of wind power, photovoltaics, and other renewable energy sources will continue to decline. At the same time, in order to cope with the uncertainty of renewable energy, more flexible resources need to be built. Under a high proportion of sustainable energy penetration, the utilization rate of flexible resources is low, which will lead to an increase in adjustment costs. Economic issues have an important impact on the development of new power systems, and power system construction will in turn affect social and economic development. Therefore, it is necessary to analyze changing trends in electricity prices in the process of power system sustainability from a quantitative perspective, so as to provide guidance for future planning. In view of the above problems, this paper takes Gansu Province as an example, predicts future power installation trends, by analyzing the power system form evolution, and uses production operation simulation technology to determine the power generation and consumption situation. On this basis, the costs of various power supplies and power grids are calculated, and trends in electricity prices in Gansu Province are forecast. [ABSTRACT FROM AUTHOR]

The Hetao Irrigation District in Inner Mongolia, a vital grain-producing region in northern China, faces growing environmental challenges. Studying net primary productivity (NPP) is essential for understanding spatiotemporal vegetation shifts and guiding locally adapted restoration and management efforts. Utilizing MOD17A3/NPP data, this study applies the Theil–Sen median trend, Mann–Kendall significance, and the Hurst index to scrutinize the spatiotemporal distribution patterns of NPP from 2001 to 2021 and forecast future changes in the area. The findings reveal cyclic temporal trends, forming a "∧" shape with initial increases followed by decreases, notably during the July to August period each year. The multi-year average NPP exhibits a slight upward fluctuation trend, averaging 172.40 gCm−2a−1. Peaks occur approximately every three years, reaching the highest average in 2012 at 218.96 gCm−2a−1. Spatially, NPP distribution stays consistent over the years, influenced by various land cover types, especially cropland, shaping the spatial patterns. Monthly and yearly NPP trends over the 21 years indicate a significant decrease in May and June, with other months mostly showing a non-significant increase. The Hurst index for monthly and yearly NPP changes over 21 years shows relatively high weak anti-persistence. In summary, over the past 21 years, the NPP trend in the study area has not significantly improved and is expected to decline in the future. This study offers data support and a scientific foundation for refining the carbon cycle model, quantifying vegetation carbon sequestration capacity, addressing climate change policies, and striving for carbon peak and neutrality in the Hetao Irrigation District. [ABSTRACT FROM AUTHOR]

Under the background of “carbon peak and carbon neutrality”, the interconnection of multiple regional integrated energy systems has become an important way to coordinate multiple energy sources and save energy and reduce emissions. This paper proposes a low-carbon economic dispatch model for multi-regional integrated energy systems considering the joint demand response mechanism; first, the concept and model of joint demand response are proposed, and on this basis, the energy conversion model between multiple energy forms in the multi-regional integrated energy system is studied; secondly, green certificate trading and carbon trading mechanisms are introduced, and green certificate trading and carbon trading are combined through the green certificate emission reduction mechanism; finally, a low-carbon economic dispatch model is proposed with the goal of minimizing the sum of system energy purchase cost, green certificate trading cost, carbon trading cost and joint demand response compensation cost. The example results show that the introduction of joint demand response mechanism and green certificate-carbon trading mechanism in the multi-regional integrated energy system reduces the total system cost and carbon emissions by 14.03% and 26.04% respectively.

Copyright of Pearl River is the property of Pearl River Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

China’s commitment to achieving the goal of carbon peak and carbon neutrality (CPCN) has attracted worldwide attention, and the efforts made by China are critical to realization of the 1.5 °C temperature control objective of the 2015 Paris Agreement. However, it is unclear whether long-term spatiotemporal changes in China’s carbon emissions and carbon sinks exhibit specific spatial patterns, such as the Hu Line, which might affect China’s future policymaking. Based on the emission factor, inventory, and eddy covariance methods, this study calculated China’s carbon emissions (2003–2018) and terrestrial carbon sinks (2003–2020). Results showed that the increase in carbon sinks is limited in comparison with the increase in carbon emissions, and that the carbon sequestration ratio remains deficient and generally maintained at around 10 %. The spatial pattern of carbon emissions and carbon sinks showed an unbalanced state across the Hu Line, mainly reflected in accelerated increase in both the carbon emission rankings and the proportion of emissions to China’s total carbon emissions of provinces on the northwestern side of the Hu Line. Despite this, the gross domestic product (GDP) rankings of those provinces have not improved substantially, whereas provinces on the southeastern side of the Hu Line have contributed most to China’s GDP and terrestrial carbon sinks. The findings of this study improve understanding of the spatiotemporal relationship between carbon emissions and terrestrial carbon sinks in China, and represent alternative insights that could support adjustment of carbon-related policies and promote realization of CPCN in China.

Excessive carbon emissions will cause the greenhouse effect and global warming, which is not conducive to environmental protection and sustainable development. In order to realize the goal of "carbon peak and carbon neutrality" as soon as possible, this paper utilizes the methodology provided by the IPCC to measure the carbon emissions and carbon intensity of China's energy consumption. The classification method of carbon emission and the kernel density function method are used to explore the spatial and temporal evolution of regional carbon emissions. Based on the Log Mean Divided Index (LMDI) method, the drivers of China's energy carbon emissions are measured. Based on the Tapio index function and the catch-up decoupling model, the decoupling status of Chinese provinces and the development gap with the benchmark provinces are examined. The results show that (1) China's total energy carbon emissions show a "rising-declining-rising" trend from 2005 to 2021, and reach the first peak in 2013, totaling 1,484,984.406 million metric tons. China's Hebei, Shanxi, and Shandong provinces have the highest energy carbon emissions. (2) China's energy carbon emissions are influenced by multiple factors, and the contribution of each factor to energy carbon emissions is in the following order: economic development effect > energy intensity effect > energy structure effect > population size effect. (3) China's catch-up provinces develop their economies at the expense of the environment and energy consumption. [ABSTRACT FROM AUTHOR]

As a kind of clean energy which creates little carbon dioxide, natural gas will play a key role in the process of achieving “Peak Carbon Dioxide Emission” and “Carbon Neutrality”. The Long-range Energy Alternatives Planning System (LEAP) model was improved by using new parameters including comprehensive energy efficiency and terminal effective energy consumption. The Back Propagation (BP) Neural Network—LEAP model was proposed to predict key data such as total primary energy consumption, energy mix, carbon emissions from energy consumption, and natural gas consumption in China. Moreover, natural gas production in China was forecasted by the production composition method. Finally, based on the forecast results of natural gas supply and demand, suggestions were put forward on the development of China's natural gas industry under the background of “Dual Carbon Targets”. The research results indicate that under the background of carbon peak and carbon neutrality, China's primary energy consumption will peak (59.4×108 tce) around 2035, carbon emissions from energy consumption will peak (103.4×108 t) by 2025, and natural gas consumption will peak (6100×108 m3) around 2040, of which the largest increase will be contributed by the power sector and industrial sector. China's peak natural gas production is about (2800–3400)×108 m3, including (2100–2300)×108 m3 conventional gas (including tight gas), (600–1050)×108 m3 shale gas, and (150–220)×108 m3 coalbed methane. Under the background of carbon peak and carbon neutrality, the natural gas consumption and production of China will further increase, showing a great potential of the natural gas industry.

The Hetao Irrigation District in Inner Mongolia, a vital grain-producing region in northern China, faces growing environmental challenges. Studying net primary productivity (NPP) is essential for understanding spatiotemporal vegetation shifts and guiding locally adapted restoration and management efforts. Utilizing MOD17A3/NPP data, this study applies the Theil–Sen median trend, Mann–Kendall significance, and the Hurst index to scrutinize the spatiotemporal distribution patterns of NPP from 2001 to 2021 and forecast future changes in the area. The findings reveal cyclic temporal trends, forming a “∧” shape with initial increases followed by decreases, notably during the July to August period each year. The multi-year average NPP exhibits a slight upward fluctuation trend, averaging 172.40 gCm−2a−1. Peaks occur approximately every three years, reaching the highest average in 2012 at 218.96 gCm−2a−1. Spatially, NPP distribution stays consistent over the years, influenced by various land cover types, especially cropland, shaping the spatial patterns. Monthly and yearly NPP trends over the 21 years indicate a significant decrease in May and June, with other months mostly showing a non-significant increase. The Hurst index for monthly and yearly NPP changes over 21 years shows relatively high weak anti-persistence. In summary, over the past 21 years, the NPP trend in the study area has not significantly improved and is expected to decline in the future. This study offers data support and a scientific foundation for refining the carbon cycle model, quantifying vegetation carbon sequestration capacity, addressing climate change policies, and striving for carbon peak and neutrality in the Hetao Irrigation District.

Offshore wind energy resource is a key support for the "carbon peak and carbon neutrality". However, offshore wind energy development still faces the international bottleneck of reasonable energy classification, which is urgently needed in the overall arrangement and accurate site selection. Firstly, this study systematically reviewed the research progress of offshore wind energy classification scheme at home and abroad, and analyzed the six aspects that need to be improved in the traditional energy classification scheme: without comprehensive consideration of resource characteristics, environmental risks and cost-effectiveness, without significant regional difference of energy classification, unable to meet the needs of diversified tasks, not applicable in some months, insufficient estimation of future energy classification, inconsistent with the mechanism. To deal with the above difficulties, the concept of wind energy classification which is all-factor, all-time, all-sea, and dynamic and adaptive is proposed. And it is also necessary to draw a dynamic map of wind energy classification, to solve the problems of overall strategic layout, accurate site selection, and long-term scientific planning for resource development, to accelerate the industrialization, scale, and independent high-quality construction, thus to contribute to the "carbon peak and carbon neutrality". [ABSTRACT FROM AUTHOR]

Copyright of Clean Coal Technology is the property of Clean Coal Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Natural Gas Industry is the property of Natural Gas Industry Journal Agency and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Energy transition targets and pathway planning are more important since the declare of carbon peak and carbon neutrality in China. Energy transition is highly relevant with economic and social development, as well as industrial transformation and technological innovation. However, existing studies have rarely conducted energy transition and CO2 emissions analysis from the macro targets of economic development and climate change as well as micro pathway of different sectors. In this study, we propose an energy transition framework to present an energy transition mechanism driven by various impact factors. First, a sectional energy consumption module is presented to analyse energy consumption transition linking economic development, technology progress, and low-carbon policy effect. Then, the energy conversion and supply module is proposed, tracing back energy flows from demand to supply to provide an overview of the energy transition. Subsequently, empirical scenario analysis of Sichuan Province is conducted, followed by whole perspective and targets of energy transition as well as CO2 emission mitigation trajectory. The results indicate that: (1) Sichuan's Carbon peak and carbon neutrality will be achieved in 2028 and 2058 under the Energy Transition Scenario; (2) Clean electrification transition would result in an insufficient renewable power supply for outer-region demand from 2030 to 2050, and Sichuan Province would not be able to meet its carbon peak and carbon neutrality goals if natural gas is added to generate more electricity to ensure the export volume; (3) Energy efficiency improvement, energy mix optimization and the increase of penetration of renewable power can reduce CO2 emission by 13.3 Mt, 87.8 Mt, and 5.4 Mt in 2050 in Energy Transition Scenario. The model extends the modelling methodology of energy-economy-environment system and provides an effective scenario analysis and path selection tool, which can provide a scientific and quantitative reference basis for policy makers in the context of energy regulation and energy network governance and can be applied to the study of energy transition paths in other regions.

Revealing the long-term development trajectory and peak scenarios of the urban residential building sector is crucial for formulating targeted emission reduction strategies and contributing to achieving the "Dual carbon" target. Given that, significant variables affecting carbon emissions from urban residential buildings (URBCE) at both macro and end-use building levels are identified in this study. Furthermore, an innovative dynamic simulation model is developed by integrating the Monte Carlo simulation model with the Kaya identity model, taking into account the uncertainties of the variables. Subsequently, the long-term evolution trajectories, potential emission peaks, and peak time of the URBCE close to 2060 in China's hot summer and cold winter (HSCW) zone are simulated. Results indicate that URBCE is expected to reach its peak of 272.43 Mt CO 2 in 2040 under the baseline scenario. Through the dynamic simulation, the probable peak time of energy consumption in the HSCW zone is 2044 (±1.85), with a peak of 145.42 (±6.91) Mtce, and the possible peak time of carbon emissions is probably 2039 (±1.60), with a peak of 271.93 (±13.40) Mt CO 2. According to dynamic sensitivity analysis, carbon emission factor, per capita residential space, and heating energy intensity can promote the peak size and timing. These findings lay a robust foundation for the formulation of regionally specific carbon reduction targets and initiatives. Dynamic simulation results of peaking time and peak value of URBEC and URBCE. [Display omitted] [ABSTRACT FROM AUTHOR]

In the current context of " carbon peak and carbon neutrality", rare earth companies are formulating low-carbon plans. However, they have no digital concept of the potential of carbon reduction measures, lack of quantitative evaluation methods, and lack of scientific data support. A method for applying life cycle assessment (LCA) provides scientific methods and tools for solving these problems. A "from cradle to gate" LCA is used to do environmental impact assessment on Baotou Steel' s rare earth products, such as rare earth polishing powder, neodymium iron boron magnetic material, hydrogen storage alloy powder, etc. The allocation method of the byproducts in the r are earth production process is proposed. The composition of th e life cycle carbon emissions of rare earth products and the distribution of each process are analyzed, so that the largest influencing factors of carbon emissions in the entire product process can be found, so as toformulate scientific carbon reduction strategies. The application of life cycle assessment methods can systematically and quantitatively make low-carbon planning for rare earth enterprises. [ABSTRACT FROM AUTHOR]

In the context of the global implementation of the emission peak and carbon-neutral strategic goal, guiding residents' low-carbon behavior is of great significance for the realization of the dual carbon goal. However, existing studies have paid less attention to the low-carbon behavior of college students. Based on the theory of planned behavior, this paper constructs a theoretical model of influencing factors of college students' low-carbon behavior. Combined with 612 questionnaires from Chinese colleges and universities, this study uses a structural equation model and multi-group analysis method to explore the motivation of college students' low-carbon behavior and guiding education strategies. The results show that low-carbon attitude, subjective norms, low-carbon values, and perceived behavior control have significant positive effects on low low-carbon behavior intention of college students, and influence their low-carbon behavior through low-carbon behavior intention. Further research found that gender and growth environment (urban vs. rural) presented heterogeneity in different influence paths, and the perceived cost had a significant negative moderating effect during the transition from low-carbon intention to low-carbon behavior. These research findings provide a theoretical basis and policy inspiration for explaining and guiding the low-carbon behavior of college students., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Ren, Liu and Chen.)

• The increase in carbon sinks is limited compared to the increase in carbon emissions. • The carbon sequestration ratio remains deficient and generally maintained around 10%. • The Hu Line spatial pattern of carbon emission and sink showed an unbalanced state. • The Hu Line's southeast side contributed the most GDP and terrestrial carbon sink. China's commitment to achieving the goal of carbon peak and carbon neutrality (CPCN) has attracted worldwide attention, and the efforts made by China are critical to realization of the 1.5 °C temperature control objective of the 2015 Paris Agreement. However, it is unclear whether long-term spatiotemporal changes in China's carbon emissions and carbon sinks exhibit specific spatial patterns, such as the Hu Line, which might affect China's future policymaking. Based on the emission factor, inventory, and eddy covariance methods, this study calculated China's carbon emissions (2003–2018) and terrestrial carbon sinks (2003–2020). Results showed that the increase in carbon sinks is limited in comparison with the increase in carbon emissions, and that the carbon sequestration ratio remains deficient and generally maintained at around 10 %. The spatial pattern of carbon emissions and carbon sinks showed an unbalanced state across the Hu Line, mainly reflected in accelerated increase in both the carbon emission rankings and the proportion of emissions to China's total carbon emissions of provinces on the northwestern side of the Hu Line. Despite this, the gross domestic product (GDP) rankings of those provinces have not improved substantially, whereas provinces on the southeastern side of the Hu Line have contributed most to China's GDP and terrestrial carbon sinks. The findings of this study improve understanding of the spatiotemporal relationship between carbon emissions and terrestrial carbon sinks in China, and represent alternative insights that could support adjustment of carbon-related policies and promote realization of CPCN in China. [ABSTRACT FROM AUTHOR]

Green innovation is pivotal for global sustainability, with state-owned capital playing a significant role, especially in the Chinese corporate landscape. This study, spanning 2008 to 2020 and leveraging a comprehensive dataset of listed companies, explores the intricate relationship between state-owned capital and the quality of green innovation in Chinese private enterprises. Motivated by the imperative to address crucial issues in green innovation quality in China, this research utilizes empirical data to uncover the mechanisms through which state-owned capital fosters green innovation. The study reveals how state-owned capital optimizes internal governance structures and reinforces environmental consciousness within private firms. Findings underscore the crucial role of state-owned capital in enhancing the quality of green innovation in private enterprises, operating through two primary mechanisms. Firstly, state-owned capital cultivates a heightened inclination towards green innovation within these firms. Secondly, it facilitates the adoption of enhanced internal governance practices, catalyzing the development of high-quality green innovation projects. A battery of mechanism tests provides robust evidence that state-owned capital enhances environmental awareness, restrains self-serving behaviors among major shareholders, mitigates financing constraints, and amplifies the motivation and capability of private enterprises for green innovation. This multifaceted approach ultimately fosters high-quality green innovation within companies. The study reveals the subtle interplay between state capital and private sector green innovation, highlighting its relevance to policymaking and practical considerations. It provides valuable insights into the ongoing pursuit of sustainability and the integration of green practices into the corporate world., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

Whether renewable energy consumption is beneficial to reducing CO 2 emission intensity and carbon emissions in the context of the goal of "carbon peak and carbon neutrality" in China. To prove this conjecture, considering the spatial spillover effect of carbon dioxide, this paper adopts the spatial Dubin model for empirical analysis based on the panel data of China's 30 provinces over the period 2002–2019. This study explores the CO 2 intensity mitigation effect of China's renewable energy consumption and further investigates the mediation role of technological innovation, industrial structure upgrading and optimization, and energy efficiency in the nexus between renewable energy consumption and carbon intensity. The main findings present that: (1) China's carbon emission intensity is characterized by significant spatial correlation; (2) Renewable energy consumption can significantly reduce carbon intensity and per capita carbon emissions; (3) The mediation effect of renewable energy consumption in reducing carbon emission intensity is to promote technological innovation and industrial structure upgrading, as well as improve energy efficiency. Based on the conclusions, this paper offers several policy implications for governments to reduce CO 2 emission intensity. • The impact of renewable energy consumption on CO 2 emission intensity is explored. • Renewable energy consumption can reduce carbon emission intensity and per capita carbon emissions. • Renewable energy consumption reduces CO 2 intensity through the spatial mediation effect. [ABSTRACT FROM AUTHOR]

Over hundreds of years, the global coal mining has created 24.236 billion cubic meters of underground goaf, which not only wastes billions of square meters of land resources but also poses significant safety hazards and environmental risks. Combining the treatment of mined-out areas with carbon dioxide (CO 2) storage can provide the new idea for solving the above problems in a low-carbon way. Therefore, based on an analysis of the status of mined-out areas and CO 2 storage principles, this paper proposes a method of using high-water materials to solidify supercritical CO 2 and fill mined-out areas. The feasible, safety and carbon fixing capacity of using high-water materials to solidify CO 2 and fill mined-out areas has been proved by theoretical analysis and indoor experiment. Combining the estimated underground mined-out area space of major coal-producing countries globally, proving that solidifying and sealing CO 2 in mined-out areas has significant application prospects. Finally, the issues and technical difficulties faced in promoting the use of high-water material to solidify supercritical CO 2 and fill mined-out areas are pointed out. The research results have important significance for major coal-producing countries worldwide to achieve "carbon peak and carbon neutrality". [ABSTRACT FROM AUTHOR]

Carbon mitigation effectiveness in the building sector profoundly determines the achievement of the "Dual carbon" target. However, the timetable and roadmap for the building sector to achieve such a target are still lacking. This study constructs a STIRPAT-PLS model framework to clarify the impact of the key factors from various dimensions on building carbon emissions across sub-sectors. Then, a dynamic scenario simulation model is established and applied in China to explore the dynamic evolutionary paths, and the timetable and roadmap are ultimately formulated. The results show that building sector will probably peak at 2.99 (± 0.09) Gt CO 2 in 2036 (± 1). Rural residential buildings will peak earliest in 2026 (± 1), followed by urban residential and commercial buildings: in 2036 (± 2) and 2038 (± 1). Achieving carbon neutrality will require the building sector to peak its carbon emissions in 2026 with 2.16–2.40 Gt CO 2. The remaining 0.56–0.81 Gt CO 2 by 2060 will be offset by negative carbon technologies. Dynamic sensitivity analysis shows that building floor space per capita and energy intensity significantly promote the emission peaks, and population and building floor space per capita markedly impact the peaking times. This study can promote the development of the theory and model for carbon emissions prediction. It can also offer a scientific basis for governments to set effective carbon-reduction targets and paths. [Display omitted] • Constructing a STIRPAT-PLS model to clarify the impact of critical factors on building carbon emissions. • Establishing a dynamic scenario simulation model by combining the Monte Carlo simulation and scenario analysis. • Building sector will probably peak at 2.99 (± 0.09) Gt CO 2 in 2036 (± 1). • Achieving carbon neutrality requires the building sector to peak its carbon emissions in 2026 with 2.16–2.40 Gt CO 2. • Building floor space per capita and energy intensity significantly promote the emission peaks. [ABSTRACT FROM AUTHOR]

Energy transition targets and pathway planning are more important since the declare of carbon peak and carbon neutrality in China. Energy transition is highly relevant with economic and social development, as well as industrial transformation and technological innovation. However, existing studies have rarely conducted energy transition and CO 2 emissions analysis from the macro targets of economic development and climate change as well as micro pathway of different sectors. In this study, we propose an energy transition framework to present an energy transition mechanism driven by various impact factors. First, a sectional energy consumption module is presented to analyse energy consumption transition linking economic development, technology progress, and low-carbon policy effect. Then, the energy conversion and supply module is proposed, tracing back energy flows from demand to supply to provide an overview of the energy transition. Subsequently, empirical scenario analysis of Sichuan Province is conducted, followed by whole perspective and targets of energy transition as well as CO 2 emission mitigation trajectory. The results indicate that: (1) Sichuan's Carbon peak and carbon neutrality will be achieved in 2028 and 2058 under the Energy Transition Scenario; (2) Clean electrification transition would result in an insufficient renewable power supply for outer-region demand from 2030 to 2050, and Sichuan Province would not be able to meet its carbon peak and carbon neutrality goals if natural gas is added to generate more electricity to ensure the export volume; (3) Energy efficiency improvement, energy mix optimization and the increase of penetration of renewable power can reduce CO 2 emission by 13.3 Mt, 87.8 Mt, and 5.4 Mt in 2050 in Energy Transition Scenario. The model extends the modelling methodology of energy-economy-environment system and provides an effective scenario analysis and path selection tool, which can provide a scientific and quantitative reference basis for policy makers in the context of energy regulation and energy network governance and can be applied to the study of energy transition paths in other regions. • An Energy transition analysis model is proposed for Sichuan Province. • Coal and natural gas will be utilized in a concentrated way to secure export. • Clean electrification transition would result in an insufficient renewable power supply. • Sichuan's carbon emissions will peak in 2028 and achieve neutrality in 2058. [ABSTRACT FROM AUTHOR]

Nowadays, driven by green and low-carbon development, accelerating the innovation of joint prevention and control system of air pollution and collaborating to reduce greenhouse gases has become the focus of China's air pollution prevention and control during the "Fourteenth Five-Year Plan" period (2021-2025). In this paper, the air quality index (AQI) data of 48 cities in three major urban agglomerations of Beijing-Tianjin-Hebei, Pearl River Delta and Yangtze River Delta, were selected as samples. Firstly, the air pollution spatial correlation weighted networks of three urban agglomerations are constructed and the overall characteristics of the networks are analyzed. Secondly, an influential nodes identification method, local-and-global-influence for weighted network (W_LGI), is proposed to identify the influential cities in relatively central positions in the networks. Then, the study area is further focused to include influential cities. This paper builds the air pollution spatial correlation weighted network within an influential city to excavate influential nodes in the city network. It is found that these influential nodes are most closely associated with the other nodes in terms of spatial pollution, and have a certain ability to transmit pollutants to the surrounding nodes. Finally, this paper puts forward policy suggestions for the prevention and control of air pollution from the perspective of the spatial linkage of air pollution. These will improve the efficiency and effectiveness of air pollution prevention and control, jointly achieve green development and help achieve the "carbon peak and carbon neutrality" goals.