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ABSTRACT To fulfil the commitments of the Paris Agreement, China will strive to achieve carbon peak (CP) by 2030. It is necessary to identify the evolution characteristics of China's carbon emissions and provide a scientific path prediction for the formulation of reasonable emission reduction policies and measures. This study summarises and predicts the pathway of China's carbon peak (CP) using carbon emission intensity (CEI) and the percentage of non‐fossil energy consumption (NEC) as indicators, and combining MSIH(3)‐AR(2) model and recurrent neural network. The results show that: (1) China's CEI experiences a ‘low decline regime’ (LDR), a ‘medium decline regime’ (MDR) and a ‘high decline regime’ (HDR), while the share of NEC goes through a ‘low fluctuation regime’ (LFR), a ‘medium growth regime’ (MGR) and a ‘high growth regime’ (HGR). (2) For CEI, the switching probability from MDR to the HDR is 74.88%, illustrating a substantial improvement. For NEC, the switching probability from MGR to HGR is 28.92%, but the probability of returning to MGR is 61.76%, indicating an adjustment. (3) By 2030, CEI will reach 0.9896 tons/100 million CNY, decreased by 66.35% compared with 2005. While the percentage of NEC will rise to 26.61%. Based on these, policy suggestions such as strengthening the top‐level design, upgrading energy mix and accelerating green technological changes are proposed to break the bottlenecks of reaching CP and further zero carbon goal. This study is expected to provide theoretical support and empirical evidence for the achievement CP in China, and to provide empirical references for promoting the ‘dual carbon’ process in other countries. [ABSTRACT FROM AUTHOR]

Assessing carbon emission reduction potential is vital for achieving carbon peak and neutrality in the maritime sector. In this study, we proposed a universal framework for assessing the effectiveness of different measures on carbon emission reduction from ships, including port and ship electrification (PSE), ship speed optimization (SSO), and clean fuel substitution (CFS). Firstly, the projection method of future ship traffic flows and activity levels relies on a neural network, and the ARIMA model was proposed. Then, the potential of various emission reduction measures was detailed and analyzed under different intensity scenarios. The proposed model was applied to Wuhan port, the results indicate that CFS is the most effective for long-term decarbonization, potentially achieving a carbon peak by 2025 under an aggressive scenario. For the short to medium term, PSE is favored due to technical maturity. SSO primarily delays emissions growth, making it a suitable auxiliary measure. These findings guide emission reduction strategies for ports, fostering green and sustainable shipping development. [ABSTRACT FROM AUTHOR]

Characterizing and quantifying livestock carbon emissions helps mitigate temperature rise and potential climate risks. Here, the spatial and temporal characteristics of China's carbon emissions of meat, egg, and milk are analyzed from the perspective of production and consumption. A driving factor decomposition model of carbon emissions of meat, egg, and milk production and consumption is established using the logarithmic mean Divisia index (LMDI). Using a static scenario analysis and dynamic Monte Carlo simulations (MCS), the evolution trajectory of carbon peak in meat, egg, and milk production and consumption in China during 2021–2030 is analyzed. China's carbon emissions from meat, egg, and milk production and consumption have risen in 2020, reaching 794.1 and 465.88 Mt, respectively. Moreover, western China has the highest carbon emissions in production (33.84%), which are concentrated in Sichuan, Inner Mongolia, and Xinjiang. For consumption, the carbon emissions are mainly concentrated in the eastern region (42.96%), and Guangdong is the primary source of carbon emissions in eastern China. The key drivers of carbon emissions for this production and consumption are the farmland output value and residential income effects, respectively. Conversely, reverse urbanization, agricultural industry structure, and food money purchasing power effects play significant suppressive roles. Under the business-as-usual scenario (BAU), China's carbon emissions from meat, egg, and milk production and consumption in 2030 will increase by 40.1% and 4.86% from 2020, respectively. The middle low-carbon scenario (Mid-LC) mitigates carbon emission growth by 24.51% and − 5.7%, respectively, for the production and consumption of meat, egg, and milk in 2030 compared to 2020. In the highly low-carbon scenario (Hig-LC), production and consumption will achieve a carbon peak by 2030. Ultimately, this study highlights the importance of reducing carbon emissions from livestock on production and consumption, and provides help for China's agricultural green development from the geospatial characteristics, drivers, and future trends of carbon emissions at both the production and consumption sides. [ABSTRACT FROM AUTHOR]

The Chinese government has introduced a carbon neutral policy to cope with the rapid changes in the global climate. It is not clear what impact this policy will have on wildlife. Therefore, this study analyzed the suitable habitat distribution of China's unique leopard subspecies in northern Shaanxi, and simulated the potential suitable habitat distribution under different carbon emission scenarios at two time points of future carbon peak and carbon neutralization. We found that in the future SSPs 126 scenario, the suitable habitat area and the number of suitable habitat patches of North China leopard will continue to increase. With the increase of carbon emissions, it is expected that the suitable habitat of North China leopard will continue to be fragmented and shifted. When the annual average temperature is lower than 8 °C, the precipitation seasonality is 80–90 mm and the precipitation of the warmest quarter is greater than 260 mm, the probability of occurrence of North China leopard is higher. The increase in carbon emissions will lead to the reduction, migration, and fragmentation of the suitable habitat distribution of the North China leopard. Carbon neutrality policies can protect suitable wild habitats. In the future, the impact of carbon neutrality policies on future wildlife habitat protection should be carried out in depth to effectively promote the construction of wildlife protection projects. [ABSTRACT FROM AUTHOR]

Jiangsu Province is a region with a high concentration of economy and population in China, as well as a spatial unit with relatively concentrated carbon emissions. It is also the pioneer in achieving carbon peak. Analyzing the factors influencing carbon emissions and predicting the peak year of carbon emissions will help Jiangsu Province clarify the direction of carbon reduction and take the lead in achieving carbon peak. This article selects relevant data from Jiangsu Province from 2005 to 2020, uses the STIRPAT model to analyze the influencing factors of carbon emissions in Jiangsu Province, predicts the carbon emissions and peak times of 13 prefecture-level cities in four different scenarios, and constructs a carbon peak prediction model to calculate the carbon peak pressure, carbon emission reduction potential, and carbon peak driving force of each prefecture-level city. Research has found that the population size, wealth level, technological level, urbanization level, and industrial structure have significant impacts on carbon emissions in Jiangsu Province. The prediction results for carbon peak in 13 prefecture-level cities indicate that Nantong, Huai'an, Yancheng, Suzhou, Nanjing, and Wuxi can achieve carbon peak before 2030 in all four scenarios. Changzhou, Xuzhou, Yangzhou, Taizhou, Suqian, Lianyungang, and Zhenjiang are all able to achieve carbon peak between 2025 and 2029 under the low-growth, slow-consumption scenario (P2G2E1) and low-growth, fast-consumption scenario (P2G2E2), but they cannot achieve carbon peak before 2030 under the high-growth, slow-consumption scenario (P1G1E1) and high-growth, fast-consumption scenario (P1G1E2). Finally, based on the carbon peak prediction model, the prefecture-level cities are classified, and differentiated carbon peak implementation paths for different types of prefecture-level cities are proposed. [ABSTRACT FROM AUTHOR]

The standard of living has significantly risen along with ongoing economic progress, but CO2 emissions have also been rising. The reduction in CO2 resulting from the daily activities of residents has become a crucial priority for every province. A relevant study on the carbon emissions of Hebei Province residents was conducted for this publication, aiming to provide a theoretical basis for the sustainable development of Hebei Province. The first part of the article calculates the carbon emissions of Hebei Province people from 2005 to 2020 using the emission factor method and the Consumer Lifestyle Approach (CLA). Secondly, the Logarithmic Mean Divisia Index (LMDI) decomposition approach is used to assess the components that influence both direct and indirect carbon emissions. Finally, the scenario analysis approach is employed in conjunction with the LEAP model to establish baseline, low-carbon, and ultra-low-carbon scenarios to predict the trend of residents' carbon emissions in Hebei Province from 2021 to 2040. The results show that the total carbon emissions of residents in Hebei Province from 2005 to 2020 rose, from 77.45 million tons to 153.35 million tons. Income level, energy consumption intensity, and population scale are factors that contribute to the increase in direct carbon emissions, while consumption tendency factors have a mitigating effect on direct carbon emissions. Economic level, consumption structure, and population scale factors are factors that contribute to the increase in indirect carbon emissions, while energy consumption intensity and energy structure factors have a mitigating effect on indirect carbon emissions. The prediction results show that under the baseline scenario, the cumulative residents' carbon emissions in Hebei Province will not reach a zenith from 2021 to 2040. However, under the low-carbon situation, the carbon emissions of residents in Hebei Province will peak in 2029, with a peak of 174.69 million tons, whereas under the ultra-low-carbon scenario, it will peak in 2028, with a peak of 173.27 million tons. [ABSTRACT FROM AUTHOR]

[Introduction] With the proposal of the "carbon peaking and carbon neutrality" and the increasing scale of the carbon market, how to manage carbon assets and realize the preservation and appreciation of carbon assets has become an important issue facing the green and low-carbon development of large-scale energy enterprises. This paper summarizes and analyzes the situation faced by large-scale energy enterprises, the status quo of management mode and the construction method of management system, and puts forward relevant suggestions for large-scale energy enterprises in China on carbon asset management.[Method] This paper first analyzed the situation faced by energy enterprises under the background of the start of the national carbon market and the upcoming restart of the national certified voluntary emission reduction CCER, and then analyzed the cost difference between the current unified management mode and the decentralized management mode of enterprise carbon assets, and then put forward the principle of "four unification" of carbon asset management, the three-level system of "enterprise headquarters-carbon asset management company-control enterprise", and the five principles of "transaction risk control", an ecological chain of carbon asset management business was constructed by building a unified carbon asset information management platform for large energy enterprises, gradually deepening the three major business segments of data management and development, low-carbon analysis and consulting, market transactions and carbon finance.[Results] Through the analysis of the current situation, development status and policy requirements of energy enterprises, the optimization method of carbon asset management system and the future business development direction are clarified. [Conclusion] This paper summarizes the carbon asset management system and business structure of large energy enterprises under the background of carbon peaking and carbon neutrality. At present, there are still a series of problems brought by decentralized management in the management mode. It is necessary to gradually optimize the management from the top-level management, organization and implementation, capital guarantee, risk control management, talent guarantee, incentive assessment and other ways, so as to maximize the preservation and appreciation of carbon assets, and help the local region and even the whole country to carry out the "carbon peaking and carbon neutrality" work smoothly.

Rural energy plays an important role in realizing the goals of “carbon peak” and “carbon neutrality” in China. In this paper, the countryside was regarded as the research object, and the rural energy internet was constructed to study the impact of rural energy development on rural carbon emissions. The most advanced energy and informative technologies in the development of rural energy were introduced from three perspectives, including rural living, rural planting and rural breeding. The benefits of rural energy internet in practical application, including energy and carbon benefits, were presented through three application cases. In general, a low-carbon, digital and intelligent rural energy will be developed, and the goals of “carbon peak” and “carbon neutrality” will be achieved by constructing and applying of rural energy internet in China.

Abstract The Chinese government has introduced a carbon neutral policy to cope with the rapid changes in the global climate. It is not clear what impact this policy will have on wildlife. Therefore, this study analyzed the suitable habitat distribution of China’s unique leopard subspecies in northern Shaanxi, and simulated the potential suitable habitat distribution under different carbon emission scenarios at two time points of future carbon peak and carbon neutralization. We found that in the future SSPs 126 scenario, the suitable habitat area and the number of suitable habitat patches of North China leopard will continue to increase. With the increase of carbon emissions, it is expected that the suitable habitat of North China leopard will continue to be fragmented and shifted. When the annual average temperature is lower than 8 °C, the precipitation seasonality is 80–90 mm and the precipitation of the warmest quarter is greater than 260 mm, the probability of occurrence of North China leopard is higher. The increase in carbon emissions will lead to the reduction, migration, and fragmentation of the suitable habitat distribution of the North China leopard. Carbon neutrality policies can protect suitable wild habitats. In the future, the impact of carbon neutrality policies on future wildlife habitat protection should be carried out in depth to effectively promote the construction of wildlife protection projects.

Residential buildings, the “last mile” sector in the global decarbonization, have become the most significant uncertain factor hindering carbon neutrality with increasing household energy demand. To track the operational carbon in buildings, this study investigates the carbon Kuznets curve (CKC) and the corresponding decoupling status of residential building operations at four emission scales by using the data of 30 countries from 2000 to 2019. The results show that (1) the CKC model can fit more than half of the samples. Most curves have an inverted U-shape, with 76% of emission per household and 82% of total emissions. (2) In the presence of the CKC, over four-fifths of global residential buildings peak regardless of any emission scale. The analysis denotes that the carbon emissions of developed countries reach their peaks earlier. In the total emissions, the samples’ peaking proportion is 20% and 25% with income per capita < 20,000 United States dollars (USD) and 20,000–40,000 USD, respectively. (3) The Tapio decoupling analysis and the threshold regression effectively verify the robustness and the heterogeneity of CKCs, respectively. Strong decoupling effects of CKCs in most countries are demonstrated at the scales of emission per floor space and the total emissions, and the heterogeneity proves the classic inverted U-shaped relationship between economy and emissions doesn't exist in all emitters. Overall, this study tracks the historical carbon emission trajectories of residential building operations at a global scale, providing reference for different economies to simulate the dynamic of building carbon emissions along with the economic booming.

Under the goal of carbon peak, carbon neutrality, the oil and gas production industry needs to strengthen negative carbon, zero carbon and low-carbon technological innovation to promote industrial transformation and upgrading under the premise of continuously increasing and stabilizing production and ensuring energy security. The research and development of new technologies, new processes and new materials have given new eonnotation to green and carbon enhanced oil recovery technology. Theoretical research and field practice show that CO2 flooding, CO2 fracturing, air (deoxygenated air or N2) flooding, biomass-based flooding, microbial based flooding technologies have obvious carbon emission reduction effects, providing a new path for low-carbon neutrality in enhanced oil recovery field. In the future, we will continue to optimize the green enhanced oil recovery technology path, build a new generation of green and low-carbon enhanced oil recovery engineering technology system, carry out research on the carbon emission reduction potential of the whole process and the whole life cycle, and explore quantitative characterization method of green and low-carbon enhanced oil recovery technology. [ABSTRACT FROM AUTHOR]

China is a world leading mandarin and tangerine producer, and the carbon emissions of mandarin and tangerine directly affect the characteristics and peak time of China’s agricultural carbon emissions. This study applied the life cycle assessment method to calculate the carbon emissions during the planting process of China’s mandarin and tangerine, and evaluated their carbon peak state and analyzed the planting advantages of different provinces based on the carbon economic efficiency (CEE) index. The results indicated that, the averaged carbon emissions per unit area (CA) and per yield (CY) of mandarin in 2020 were 13.9% and 15.8% lower than those in 2006, while CA and CY of tangerine in 2020 were 47.8% and 22.2% lower than those in 2006. Changes of carbon emissions from fertilizer production made great contributions to the decrease in carbon footprint (CF) on the time scale, and differences in CF across regions were mainly caused by fertilizer application. The CA and CY of mandarin were higher than those of tangerine, due to the higher application of nitrogen fertilizer in orchards. Zhejiang and Hubei reached their carbon emissions peaks mainly due to the decrease in agricultural input, while the state of whole China was still in a plateau period. Jiangxi and Zhejiang had significant planting advantages due to their lower CYs and higher CEEs. In conclusion, there are possibilities for low-carbon development of Chinese mandarin and tangerine through targeted mitigation measures such as variety improvement and precise fertilization. [ABSTRACT FROM AUTHOR]

The transportation sector plays a pivotal role in China's efforts to achieve CO2 reduction targets. As the capital of China, Beijing has the responsibility to lead the era's demand for low-carbon development and provide replicable and scalable low-carbon transportation development experience and knowledge for other cities in China. This study calculates the CO2 emissions of the transportation sector in Beijing from 1999 to 2019, constructs an extended STIRPAT model (population, affluence, technology, and efficiency), employs ridge regression to mitigate the effects of multicollinearity among the eight indicators, reveals the extent and direction of influence exerted by different indicators on CO2 emissions, and predicts the development trends, peak times, and quantities of transportation CO2 emissions in nine scenarios for Beijing from 2021 to 2035. Finally, adaptive low-carbon planning strategies are proposed for Beijing pertaining to population size and structure, industrial layout optimization, urban functional reorganization and adjustment, transportation infrastructure allocation, technological research and promotion, energy transition planning, and regional collaborative development. The results are as follows: (1) The total amount of CO2 emissions from Beijing's transportation sector exhibits a trend of gradually stabilizing in terms of growth, with a corresponding gradual deceleration in the rate of increase. Kerosene, gasoline, and diesel are the main sources of transportation CO2 emissions in Beijing, with an annual average proportion of 95.78%. (2) The degree of influence of the indicators on transportation CO2 emissions, in descending order, is energy intensity, per capita GDP, population size, GDP by transportation sector, total transportation turnover, public transportation efficiency, possession of private vehicles, and clean energy structure. Among them, the proportion of clean energy structure and public transportation efficiency are negatively correlated with transportation CO2 emissions, while the remaining indicators are positively correlated. (3) In the nine predicted scenarios, all scenarios, except scenario 2 and scenario 4, can achieve CO2 emission peaks by 2030, while scenarios 7 and 9 can reach the peak as early as 2025. (4) The significant advancement and application of green carbon reduction technologies have profound implications, as they can effectively offset the impacts of population, economy, and efficiency indicators under extensive development. Effective population control, sustainable economic development, and transportation efficiency improvement are viable means to help achieve carbon peaking and peak value in the transportation sector. [ABSTRACT FROM AUTHOR]

Cities constitute a critical component of the “dual carbon” strategy, highlighting the importance of examining the carbon emission trends within various city categories to formulate a low-carbon development path. In this paper, 21 cities (prefectures) in Sichuan province were divided into 4 categories (service-based cities, resource-based cities, industry-based cities, and other cities) through K-means clustering, and the differences in driving factors of carbon emissions in different types of cities were explored. At the same time, baseline scenarios, technological innovation scenarios, controlled development scenarios, and mandatory emission reduction scenarios were set up to dynamically simulate the evolution path of urban carbon emissions in the next 30 years from the bottom-up. The results show that: (1) Input scale is the main driving factor for carbon emission growth in Sichuan province, while input carbon intensity is the leading factor for carbon emission reduction. Environmental input and population scale have opposite effects on carbon emission of different urban types. (2) Resource-based cities face challenges in completing the phased goal of “carbon peaking” under both baseline scenarios and controlled development scenarios. These cities have gradually become the predominant city type of emission source in Sichuan province, surpassing service-based cities. (3) Except for the normal scenario, Sichuan province can achieve the target of “carbon peaking” in other scenarios, and is expected to achieve the target of 90 % greenhouse gas reduction by 2050. (4) Among the 81 development paths derived from the urban scenario combinations, the path labeled M−B−C−M exhibits the lowest economic-ecological comprehensive impact coefficient. The bottom-up carbon emission scenario analysis framework established in this paper offers a novel perspective for the study of “carbon peaking” and can provide theoretical support for policymakers in devising regional low-carbon development strategies.

China and the international community attach great importance to sustainable development goals such as peaking carbon emissions. As an important energy base in China, the Yellow River Basin has significant capacity for reducing carbon emissions and increasing carbon sinks. To accelerate the achievement of carbon peak targets, social and natural development data as well as carbon emission data of 56 cities along the Yellow River Basin from 2000 to 2021 were analyzed. Based on the evaluation indicators of the model, the PSO-XGBoost-RF model was selected from the comparative models to predict the carbon peak of cities in the Yellow River Basin under different paths. Under the current economic and social development, cities along the Yellow River Basin in China are facing huge pressure to reduce emissions. It is expected to achieve a carbon peak in 2033, with a peak of 2,051,320,000 tons, so the target of reaching the peak of carbon emissions before 2030 will not be accomplished. But through comprehensive optimization of the industrial structure and reduction of energy consumption, cities along the Yellow River Basin as a whole may achieve carbon peak by 2026, with a peak of 1,917,132,000 tons.

[Objective] The forest coverage rate of Fujian Province is as high as 66.8%, ranking first in China. To investigate the impact of land use changes on carbon storage in Fujian Province is the theoretical basis for exploring the balance between social development and ecological protection. [Methods] Based on the carbon storage module of PLUS model and InVEST model, relationship between the spatiotemporal change characteristics of carbon storage and land use types in Fujian province during 2000—2020 was revealed, and the spatial and temporal changes of carbon storage in Fujian Province during 2020—2030 were predicted from three scenarios: natural development, ecological protection and urban development. [Results] The total carbon reserves in the study area in 2000, 2010 and 2020 were 214.77×107, 214.51×107 and 212.93×107 t, respectively, indicating a downward trend year by years. The development and transformation of land by human activities was the dominant factor leading to changes in carbon stocks, and the conversion of large areas of cultivated land and forest land into urban areas was the primary reason for the decline in carbon stocks. The prediction results showed that compared with 2020, carbon storage under natural development, ecological protection and urban development in 2030 would decrease by 1.47×107 t, increase by 0.17×107 t, and decrease by 1.85×107 t, respectively. The ecological protection scenario was the only development scenario that reversed the decline in carbon stocks. Compared with 2020, the forest area had expanded by 1 900.87 km2 and the forest carbon storage had increased by 2.08 ×107 t, which could effectively protect the ecology and meet the land requirements for urban development. [Conclusion] Prioritizing forest land protection and controlling the expansion of construction land are crucial prerequisites for Fujian Province to achieve carbon peaking and carbon neutrality goals.

To address global warming, respond to international trade pressures (such as carbon tariffs) affecting China’s iron and steel industry, and help the steel industry achieve the goal of “carbon peak + carbon neutrality,” this paper examines the current carbon emissions landscape within China’s iron and steel industry and identifies the challenges encountered by steel enterprises in managing carbon emission. An innovative framework for leveraging digital technology to enhance the capabilities of the iron and steel industry is proposed. Drawing insights from notable instances of digital carbon management in the steel industry, key priorities at different stages of building a digital carbon management system are explored, and corresponding strategies are put forward. The framework of digital carbon emission management comprises four layers: infrastructure and data acquisition, data processing, business application, and user interface layers. The envisioned applications of digital carbon management in the steel industry encompass carbon accounting, carbon reporting, carbon mapping, carbon structure analysis, carbon comparisons, carbon trading, carbon consulting, energy–carbon synergy, low-carbon index, management of product carbon footprints along the supply chain, real-time tracking of product carbon footprints, digital carbon labeling, identification of energy-saving potential, and ecological design. By delving into representative case studies of digital carbon management within the steel industry, the potential for the application of digital carbon management technology in the steel industry is analyzed. A two-stage approach for implementing a digital carbon management system in China’s steel industry was proposed, contingent on whether the industry becomes part of the national carbon trading market. Government should play a leading role in guiding the development of the digital carbon management system. Simultaneously, we emphasize the need to enhance relevant standards and regulations in digital carbon management, invest in the training of professionals in this field, and establish strong connections with existing enterprise information systems. We advocate for a future trend of “six integration + multiplatform” digital carbon management within the steel industry, featuring a “one body + multiplatform” evaluation and certification system for low-carbon products. This vision for digital carbon management encompasses characteristics such as standardization, internationalization, integration, security, asset management, and localization. Integrating digital carbon management technology into the steel industry holds the potential to streamline carbon management processes, alleviate pain points experienced by enterprises, lower barriers to carbon management, increase operational efficiency, and safeguard carbon data during transmission.

The building sector contributes significantly to carbon emissions, impeding China's progress toward its 2030 carbon emissions peak target due to the limited utilization of renewable energy sources. This study aims to forecast the peak and timing of carbon emissions in China's construction industry to chart a low-carbon roadmap for the sector's future. Initially, an extended logarithmic mean divisia index (LMDI) decomposition model, based on the Kaya identity, is proposed to gauge the contribution levels of driving factors affecting building carbon intensity. Subsequently, a hybrid prediction model (IGA-BP) is constructed, employing an optimized two-hidden-layer neural network via a genetic algorithm, to forecast building carbon emissions and intensity. Additionally, four scenarios are outlined, each defining pathways to simulate emissions peak, carbon peak timing, and intensity within the Chinese building sector from 2020 to 2050. The research findings reveal: (1) The final emission factor of buildings primarily drives the surge in building carbon intensity, while the industrial structure stands as the most significant limiting factor. (2) Compared to alternative models, the proposed hybrid prediction model more effectively captures the evolution pattern of carbon emissions. (3) The prediction results indicate that China's building carbon intensity has reached its peak. Pathway 12 closely aligns with the sector's carbon emissions peak, projecting a peak value of 5.609 billion tons in 2029. To attain this pathway, China needs to develop more precise and feasible emission reduction strategies for its buildings. Overall, the research outcomes furnish robust references for decision-making in future efforts aimed at reducing building emissions. [ABSTRACT FROM AUTHOR]

The building operation sector in China represents 22% of the national energy consumption and 22% of the carbon emission, of which urban residential buildings accounted for 24% in 2019. Such figures for the housing sector are projected to increase sharply in the near future, while China aims to peak CO2 emissions by 2030 and reach neutrality before 2060. To reduce the impacts of the urban housing sector and address the energy use and waste generated by large-scale demolition and reconstruction, the central government started promoting the energy retrofit of urban residential buildings, raising such policies to the national strategic level. Jiangsu Province is one of the most urbanised, with a rapid growth in the energy consumption of residential buildings. The Multi-Danyuan and Single-Danyuan Apartment built in 1980–1999 are the most representative residential types in its urban areas. While still adequate functionally, they were designed and built to low energy standards and show significant potential for energy retrofit. Nonetheless, their current performance and energy-saving potential are under-researched, while more detailed and reliable data would be critical to support retrofit design and policy making. This study investigates and characterises the typical use and energy performance of the two building types. Additionally, seven measures and six retrofit scenarios were identified based on the optimal energy reductions and regulations from selected countries. The simulations indicate that, without intervention, the energy consumption of the typical urban residential buildings can reach 122 kWh/m2 under the typical high-energy user scenario. By selecting a set of effective energy-saving measures, the operational energy use for heating and cooling can be reduced by up to 52.4%. Current local standards prove cost-efficient, although less effective in reducing energy use compared to international best practices, indicating potential improvements to the contribution of building retrofit towards achieving the national carbon reduction goals. [ABSTRACT FROM AUTHOR]

Based on the 2030 carbon peak target, this paper studies the top-down provincial carbon quota allocation in China's iron and steel industry. Considering the principles of fairness, efficiency, sustainability and development, three provincial carbon quota allocation schemes are constructed based on entropy method, three-stage DEA and ZSG-DEA model respectively, which make up for the gap of carbon quota allocation scheme with the total amount of carbon peak target of the iron and steel industry. The allocation results show that the allocation based on the entropy method can roughly solve the problem of uneven distribution of carbon quota of the steel industry in various provinces, and the carbon quota in the steel industry decreases from the eastern region to the western region. Considering the two environmental indicators of local government competition and urbanization level, the initial carbon quota allocation scheme can be effectively adjusted, which is conducive to promote the enthusiasm of some underdeveloped areas. The allocation scheme, which combines the entropy method with the ZSG-DEA model, can enhance the efficiency of carbon quota allocation among provinces while ensuring fairness. However, this fairness is limited and more advantageous to economically developed regions. [ABSTRACT FROM AUTHOR]

Copyright of Acta Materiae Compositae Sinica is the property of Acta Materiea Compositae Sinica Editorial Department 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 Acta Scientiarum Naturalium Universitatis Pekinensis is the property of Editorial Office of Acta Scientiarum Naturalium Universitatis Pekinensis 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.)

Decomposition analysis and forecasting of carbon emissions in manufacturing are crucial for setting sustainable carbon-reduction targets. Given the varied carbon-emission efficiencies across sectors, this study applied the Logarithmic Mean Divisia Index (LMDI) decomposition method to analyze the drivers of carbon emissions in Gansu's manufacturing sector, encompassing high, medium, and low-efficiency industries, and it identified vital factors affecting carbon emissions. A localized Long-range Energy Alternatives Planning System (LEAP) model for Gansu was also developed. This model includes six developmental scenarios to project future carbon emissions. The study results are as follows: (1) LMDI decomposition indicates that increased carbon emissions in the manufacturing industry primarily result from economic growth in less efficient sectors and the dominance of moderately efficient ones. (2) Under Optimization Scenario 6, a 50.82 × 104 ton reduction in carbon emissions is projected for Gansu's manufacturing sector by 2030 compared to 2020, marking the carbon peak. These outcomes provide valuable insights for policy reforms in Gansu's manufacturing industry, aiming for carbon peaking by 2030. [ABSTRACT FROM AUTHOR]

In the context of global climate change, countries around the world are actively implementing carbon peak and carbon neutrality goals. In-depth research on carbon peak can help improve environmental conditions and achieve a harmonious coexistence between economic development and environmental protection. However, a comprehensive review of the current status of research in this area is scarce. Therefore, this article explores the current research evolution and hotspots of "carbon peak" with the help of CiteSpace visualization software, predicts the future development trends, and builds a knowledge network framework. A comprehensive analysis of the research on carbon peak from multiple perspectives is presented. The results show that the number of papers published on carbon peak is increasing every year, and that carbon peak has become a widely participated research area. Publications from various institutions and journals have also attracted widespread attention. The research hotspots of carbon peak have constantly changed with time, resulting in many theoretical and technological innovations. The knowledge framework of the field is constructed on this basis, which gives readers a clearer understanding of the development and trends in the field and provides some reference and help for future researchers. [ABSTRACT FROM AUTHOR]

The main form of ground source heat pump is rock-soil source heat pump system. To find out the causes for the poor operation effect of the system when applied in karst area, the heat transfer test and engineering research are conducted. It is considered that the unfavorable formation lithology and hydrogeological conditions may restrict the sustainable development and utilization of the system to some extent, and the problems existing in the air pressure down-the-hole (DTH) hammer technology and construction may also cause abnormal running of the system. Thus, the paper put forwards some suggestions and countermeasures on strengthening basic geological and hydrogeological survey, geophysical prospecting, drilling technology promotion and process management. [ABSTRACT FROM AUTHOR]

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Summary: Chinese cities need independent but synergetic dual-carbon abatement roadmaps to mitigate climate change and achieve carbon neutrality. Using source-level data, we develop a time-series, full-scale emission inventory for all Chinese cities from 2005 to 2020, exploring associated heterogeneous and homogeneous patterns. We find that 31% of cities have had a significant carbon emission peak, with the main driver being carbon intensity reductions through efficiency gains and structural improvements. Despite discrepant emission levels and socioeconomic determinants, a uniform trajectory in emission changes exists across cities via four emission phases: growth of 8%–9% annually (95% confidence interval) before peaking; plateau and decline by 9%–13% for 5–7 years; and plain with slower declines. We project that if cities follow their early-peaked counterparts’ mitigation pathways, China will reach a carbon peak in 2026 at 13 Gt and carbon neutrality during 2051–2058, revealing the feasibility of Chinese climate goals and the importance of long-reaching, city-targeted planning. Science for society: China established its dual-carbon goals to achieve a carbon peak before 2030 and carbon neutrality by 2060. It is important for cities to identify their distinctive patterns and define individual dual-carbon roadmaps to achieve carbon neutrality in China. In this study, we conduct a carbon inventory for all Chinese cities from 2005 to 2020 to quantitatively define the emission phases in the process of carbon peak. We find that 31% of cities have had a significant carbon emission peak, with the main driver being carbon intensity reductions. A uniform trajectory in emission changes exists across cities, despite significant differences in emission levels and socioeconomic determinants. We project that if cities follow their early-peaked counterparts’ mitigation pathways, China could achieve its climate change goals ahead of the policy deadlines.

To measure and reduce carbon emissions in the urban power sector, a method for measuring carbon emissions in the urban power sector and a carbon reduction path are proposed. First, a carbon emission measurement model for the urban power sector is established based on the data of local power generation and net inward power. Then, carbon reduction measures for the urban power sector are proposed from the generation side, grid side, load side and energy storage side. After that, an evaluation model for the effect of the carbon reduction measures is established. Finally, taking a typical city F in the Pearl River Delta as an example, the proposed carbon emission calculation model is used to calculate the carbon emissions of power sector of the city, and the effectiveness of carbon reduction in 2030 carbon peak scenario of the city is evaluated based on the carbon reduction measures. The results show that the proposed model can accurately measure the carbon emissions of the urban power sector, and by utilizing carbon reduction measures, carbon emissions of the city can be reduced by at least 10.6 million tons in 2030.

Assessing carbon emission reduction potential is vital for achieving carbon peak and neutrality in the maritime sector. In this study, we proposed a universal framework for assessing the effectiveness of different measures on carbon emission reduction from ships, including port and ship electrification (PSE), ship speed optimization (SSO), and clean fuel substitution (CFS). Firstly, the projection method of future ship traffic flows and activity levels relies on a neural network, and the ARIMA model was proposed. Then, the potential of various emission reduction measures was detailed and analyzed under different intensity scenarios. The proposed model was applied to Wuhan port, the results indicate that CFS is the most effective for long-term decarbonization, potentially achieving a carbon peak by 2025 under an aggressive scenario. For the short to medium term, PSE is favored due to technical maturity. SSO primarily delays emissions growth, making it a suitable auxiliary measure. These findings guide emission reduction strategies for ports, fostering green and sustainable shipping development.

This study presents a comprehensive analysis of vehicle ownership, energy consumption, and carbon emissions in Guangdong Province, China, from 2020 to 2035 under different scenarios. Key findings highlight the province's pursuit of carbon peak goals and provide valuable insights into strategies to achieve them. Vehicle ownership in Guangdong is projected to exceed 48 million by 2035, which represents a doubling from 2020. Under both scenarios, internal combustion engine vehicle ownership will peak around 2030 and then gradually decline, while under the enhanced scenario, electric vehicle ownership will exceed 40% by 2035. Enhanced vehicle energy efficiency and reduced annual mileage will lead to a 17% reduction in gasoline and diesel consumption by 2035 in both scenarios. At the same time, there will be a substantial five- to six-fold increase in electricity consumption for vehicles compared to 2020. Both scenarios peak in carbon emissions before 2030, with the enhanced scenario achieving this peak a year earlier. The enhanced scenario outperforms the baseline, reducing carbon emissions by about 21.2% from the peak and 8% relative to 2020. Pure electric vehicles exhibit a significant advantage in reducing carbon emissions per vehicle compared to their internal combustion engine counterparts. Encouraging new energy vehicles, especially pure electric ones, accelerates the carbon emissions peak and lowers overall peak emissions. Accelerating the adoption of electric vehicles, reducing per-vehicle fuel consumption and annual average mileage, and optimizing transportation modes are crucial for carbon peaking from the vehicle fuel cycle. Policy recommendations focus on promoting new energy vehicles, optimizing transportation, and advancing research and technology. [ABSTRACT FROM AUTHOR]

China is the largest CO2 emitter in the world and announced that carbon peak and neutral targets will be achieved before 2030 and 2060, respectively. A retrospective analysis of past CO2 emissions and their drivers is important for the actions of peaking CO2 emissions before 2030 in China. CO2 emissions from energy use (coal, oil, and natural gas) and cement production from 2000 to 2020 were calculated first, and their drivers were decomposed into economic and population growth, energy intensity, and emission coefficient by logarithmic mean Divisa index (LMDI) analysis in this study. China's CO2 emissions increased nearly threefold from 3385 in 2000 to 10,788 million tonnes (Mt) in 2020, with a decline from 2013 to 2016. Coal was the major emission sector contributing more than 70% in most years, while natural gas emissions increased nearly 13 times from 53 to 723 Mt in the two decades, although its contribution only accounted for 6.7% in 2020. Economic growth was the major positive driver, while energy intensity reduction was the major negative driver of the emission increments by year and by the Five Year Plan (FYP). Emission coefficient reduction gradually became important due to its negative effect, especially in the 13th FYP, which offset ~ 30% of the emissions induced by economic growth. The projections of CO2 emissions in 2025, 2030, and 2035 could be 11,596 ± 582, 11,774 ± 621, and 11,401 ± 672 Mt, respectively, suggesting that China's carbon emissions could peak around 2030 with an increment of ~ 1000 Mt on the 2020 levels. Under the sustainable growth of the economy and population, it is possible to reduce the carbon peak value or achieve peak time earlier through the additional reduction of energy intensity and emission coefficient by technological progress and energy alternatives such as non-fossil fuels. [ABSTRACT FROM AUTHOR]

Coordinating and controlling carbon and atmospheric pollutant emissions in industrial cities poses challenges, making it difficult to formulate effective environmental governance strategies in China. This study used the Community Multiscale Air Quality (CMAQ) and Long-range Energy Alternatives Planning (LEAP) models, with a typical industrial city in the Sichuan Basin as the case study. Five emission reduction scenarios, one integration scenario, and one baseline scenario were set to quantitatively analyze the synergistic effect between carbon emissions and atmospheric pollutant emissions. The results indicate a high synergy between sulfur dioxide and greenhouse gases. For every one-point decrease in the Air Quality Composite Index (AQCI), the Industrial Restructuring Scenario (IR), Other Source Management Scenario (OSM), Transportation Energy Efficiency Improvement Scenario (TEEI), Industrial Energy Efficiency Improvement Scenario (IEEI), and Transportation Restructuring (TR) scenarios would require a reduction in carbon emissions by 56,492.79 kilotons, 39,850.45 kilotons, 34,027.5 kilotons, 22,356.58 kilotons, and 3243.33 kilotons, respectively. The results indicate that governance measures, such as improving transportation structure and upgrading industrial technologies, provide stronger support for simultaneous carbon emissions reductions and air quality improvement. [ABSTRACT FROM AUTHOR]

China has pledged to peak its CO2 emissions by 2030 and achieve carbon neutrality by 2060. To meet these goals, China needs to accelerate the electrification of passenger vehicles. However, the rapid development of electric vehicles may impact the supply of critical raw materials, which may hinder the low-carbon transition. Therefore, the impact of vehicle electrification on CO2 emissions and the corresponding bottlenecks in the supply of critical raw materials should be systematically considered. In this study, we developed the China Automotive Fleet CO2 Model (CAFCM) to simulate a mixed-technology passenger vehicle fleet evolution. We further assessed the impact of energy and CO2 emissions and evaluated the demand for critical battery materials. We designed three scenarios with different powertrain type penetration rates to depict the potential uncertainty. The results showed that (1) the CO2 emissions of passenger vehicles in both the operation stage and the fuel cycle can peak before 2030; (2) achieving the dual carbon goals will lead to a rapid increase in the demand for critical raw materials for batteries and lead to potential supply risks, especially for cobalt, with the cumulative demand for cobalt for new energy passenger vehicles in China being 5.7 to 7.3 times larger than China's total cobalt reserves; and (3) the potential amount of critical material recycled from retired power batteries will rapidly increase but will not be able to substantially alleviate the demand for critical materials before 2035. China's new energy vehicle promotion policies and key resource supply risks must be systematically coordinated under the dual carbon goals. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Shanghai Jiao Tong University (1006-2467) is the property of Journal of Shanghai Jiao Tong University 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.)

This article discusses the changes in carbon productivity and economic growth patterns in China. We calculated carbon productivity using panel data from BRICS and G7 countries between 2001 and 2019 and developed a methodology to estimate economic growth patterns by combining carbon productivity and economic growth. As the world's top carbon emitter, China can combat global climate change by increasing carbon productivity. We show that (i) China has a high growth rate of carbon productivity; however, the carbon productivity level only accounts for about 20% of developed countries. (ii) When determining economic growth patterns from a low-carbon perspective, China has transitioned from high-carbon type II to low-carbon type III. However, low-carbon economic growth is common in developed countries, and (iii) it can improve carbon productivity by reducing energy-averaged carbon emission factors. It assists the government in determining how to implement low-carbon economic development policies by examining economic growth from a low-carbon perspective. [ABSTRACT FROM AUTHOR]

This study estimates the environmental impacts of Bitcoin mining. Employing a top-down measurement approach, this paper assesses the carbon footprint of Bitcoin mining in China from 2017 to 2021. The findings reveal that mining activities during this period contributed to a total of 77.84 million tons of carbon dioxide emissions in China. By utilizing data at the provincial level, we find that the seasonal migration of Bitcoin mining pools will lead to regional power demand shocks in China. Additionally, this study predicts future carbon emissions from Bitcoin mining in China, projecting cumulative carbon dioxide emissions of 76.40 million tons and 722.18 million tons by 2030 and 2060 respectively, in the absence of any policy interventions. Based on these findings, this paper posits that governments worldwide should make efforts to restrict the carbon emissions from Bitcoin mining and opt for environmentally friendly technological methods to fundamentally alleviate Bitcoin's reliance on energy. The implication for central banks is that carbon emission should be taken into consideration when designing the central bank digital currencies (CBDCs). [ABSTRACT FROM AUTHOR]

Carbon control in the thermal power generation industry is crucial for achieving the overall carbon peak target. How to predict, evaluate, and balance the allocation of inter provincial carbon emissions has a significant impact on the decision-making of reasonable allocation of inter provincial carbon emissions in the target year. Therefore, this paper uses Monte Carlo-ARIMA-BP neural network and ZSG-DEA model to conduct temporal trend prediction and carbon emission quota allocation research. We propose the "intra provincial and inter provincial" framework for carbon emissions trading in thermal power plants, which aims to break through the barriers in carbon emission rights exchange among provinces. The conclusions are as follows: (1) the growth trend of carbon emissions from thermal power is gradually slowing down and is expected to peak before 2030. (2) Inner Mongolia, Jiangsu, and Shandong have high input–output efficiency, and are all the main output provinces for carbon emission quota allocation. After being adjusted using the ZSG-DEA model, they can still be at the forefront of efficiency. (3) The "intra provincial and inter provincial" framework for carbon emissions trading can effectively predict and allocate the carbon emission demand of each province from time and space dimensions, balance the carbon emission rights and interests of each province, and provide forward-looking planning suggestions for inter provincial carbon emission rights exchange. [ABSTRACT FROM AUTHOR]

Combined with the characteristics of concrete, this paper puts forward the low-carbon concrete development ideas from the concrete production stage, concrete service stage and concrete abandonment stage respectively, specifically including the development of low-carbon cementitious materials, promoting the development of mineral admixture technology, optimizing concrete aggregate quality, enhancing the durability of concrete, attaching importance to the extension of the concrete's service life, and increasing the recycling of waste concrete. It also investigated the related research and standardization of concrete carbon emission calculation methods at home and abroad, providing reference for the formulation of related standards and specifications. [ABSTRACT FROM AUTHOR]

China has paid considerable attention to developing and implementing a carbon labeling system in response to increasing environmental issues such as global warming. This paper aims to provide a theoretical basis for formulating and implementing a carbon labeling system in China through a study of consumer acceptance behavior and its influencing factors. This paper constructed an extended model of consumers’ acceptance behavior of carbon neutral labels based on the theories and methods of Unified Theory of Acceptance and Use of Technology (UTAUT) and analyzed the effects of five factors (carbon label cognition, performance expectancy, effort expectancy, social influence, and facilitating factors) on consumer carbon neutral label acceptance and adoption. The structural equation model analysis revealed that carbon label cognition, performance expectancy, social influence, and facilitating factors significantly, and positively impact consumers’ acceptance of carbon neutral labels. Moreover, carbon label cognition, performance expectancy, and facilitating factors significantly, and positively affect consumers’ carbon neutral label adoption behavior. Meanwhile, carbon label cognition, and effort expectancy have no significant impact on consumers’ willingness to accept carbon neutral labels, which in turn significantly impacts consumers’ carbon neutral label adoption behavior. According to the research findings, increasing the promotion of carbon labeling and improving the practical strategies and management recommendations for carbon label design are proposed.

In order to solve the problem of early peak of carbon emissions the Beijing-Tianjin-Hebei Region，taking Hebei Province as an example, the realization path of peaking carbon emissions in the region was studied, and the future carbon emissions in the region were predicted and analyzed, the STIRPAT carbon emission prediction expansion model based on carbon emission data in Hebei Province from 2004 to 2021 was established. Six scenarios were set up to simulate the carbon emission trend from 2022 to 2040 under different scenarios by comprehensively considering the change rates of six data such as population size, per capita GDP, urbanization rate, industrial structure, energy intensity and energy structure, and to predict the carbon peak time and carbon emission peak of Beijing, Tianjin and Hebei. The results show that: Except for the clean development scenario, which peaks in 2030, the other scenarios of Beijing will reach the peak in 2035. Except for the economic slowdown scenario, which is to peak in 2030, the remaining scenarios of Tianjin were to achieve carbon peak in 2035. In Hebei Province, except for the baseline scenario, which is to reach the peak in 2035, the remaining scenarios are to reach the peak in 2030.The proposed carbon emission forecast expansion model, considering multi-scenario analysis, puts forward relevant suggestions on how to control and reduce carbon emissions in the Beijing-Tianjin-Hebei Region, and provides certain reference for the development of low-carbon economy in the Beijing-Tianjin-Hebei Region.

In September 2020, the Chinese government proposed the goals to reach carbon dioxide emissions peak by 2030 and achieve carbon neutrality by 2060 (“two-carbon goals”). This brings opportunities to the development and application of CO2-enhanced gas recovery (CO2-EGR) in China. To obtain an overall understanding of the development of CO2-EGR under the two-carbon goals, this paper analyzes the significance, potential, status quo and challenges of CO2-EGR, and makes suggestions on the development of CO2-EGR in China. The research results are obtained as follows. First, the development of CO2-EGR plays a crucial role in ensuring China's energy security, accelerating the construction of the clean energy system to promote energy transition and realizing the two-carbon goals as early as possible. Second, China should clarify a path for CO2-EGR development, build a spatial layout of CO2-EGR, and promote digital inclusion in CO2-EGR, enhance the emission reduction role of CO2-EGR in the multi-energy complementary system, boost large scale application of renewable energy and deep decarbonization in the traditional coal industry, which is difficult to reduce carbon emissions. Third, China should draw lessons from European and American tax credit and innovation funds policies to accelerate the construction of a CO2-EGR policy support system. Fourth, China should carry out research on key CO2-EGR technologies to accelerate the construction of a CO2-EGR methodology and standard system and promote rapid and standardized development of the CO2-EGR industry. It is suggested to establish a CO2-EGR demonstration area in the Sichuan Basin and popularize it across China, so as to improve comprehensive economic benefits through the establishment of large-scale industrial clusters. It is concluded that the two-carbon goals bring opportunities to the development of CO2-EGR in China, which will promote gas production and demonstration of CO2 sequestration in gas reservoirs and have positive significance in ensuring energy security and realizing carbon peak and carbon neutrality in China.