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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., (© 2024. The Author(s).)

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., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

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., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

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., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Scientific assessment of the historical carbon peak situation of provincial buildings in China is the premise and basis for understanding the country's development trends and formulating carbon peak goals. The population size, urbanization stages, economic development levels, natural resources endowment, and energy structure characteristics vary significantly for the different provinces in China, resulting in significant differences in the peaking situation of building carbon emissions (BCE). The differences require more attention given the current environmental status. Based on the judgment function of carbon peaking conditions and the statistical Mann-Kendall (MK) trend test method, this study evaluates the historical peak situation of building carbon emissions at the provincial level in China. The peaking sequence of BCE, building carbon emissions per capita (BCEP), and carbon emissions per unit floor area (BCEA) were analyzed, and the driving factors that cause different carbon peak situations were discussed. Further, with reference to the experience of the United States, a peak strategy for building carbon emissions in China was proposed. The research results showed that BCE in Beijing and Yunnan have peaked, and the three provinces of Shanghai, Sichuan, and Hubei have plateaued. The most important factors that cause different peaking situations for BCE are the floor area per capita and carbon emissions per unit of energy consumption. In addition, the peak order of building carbon emissions was BCEA, BCEP, and BCE. A strategy that should be adopted in the promotion of buildings' carbon peak in China is to formulate phased peak goals for BCE, BCEP, and BCEA at a national level and differentiated echelon peak goals at a provincial level considering interprovincial differences. This study provides a scientific basis and decision-making reference for formulating a path to buildings' carbon peak at a provincial level in China., Competing Interests: Declaration of competing interest 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., (Copyright © 2023. Published by Elsevier Ltd.)

Achieving the "double carbon" goal is a major task and challenge facing China. The emission reduction actions in typical urban agglomerations are of great significance. Based on the consideration of the impact of regional coordinated development, this study analyzed influencing factors and conducted prediction of carbon emissions from terminal energy consumption in the Beijing-Tianjin-Hebei (BTH) region. Firstly, the factors affecting carbon emissions were screened through the STIRPAT model. Then, the paper designs different scenarios and finally uses the genetic algorithm extreme learning machine (GA-ELM) algorithm to predict the carbon emissions of the BTH region, with and without considering the impact of the coordinated development strategy. The research shows that the increase in energy intensity and the improvement of energy consumption structure have the largest promotion effect on carbon emission reduction. At the same time, the significant role of the coordinated development strategy in promoting regional carbon emission reduction was verified. Therefore, the BTH region should adhere to the path of coordinated development, innovate low-carbon technology, and deepen the concept of green consumption to promote the realization of regional carbon emission reduction goals., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The debate over the role of fiscal decentralization and industrial structure upgrading in China's environmental governance has received increasing attention. Based on China's provincial panel data from 2003 to 2019, this paper investigates the impact of fiscal decentralization and industrial structure upgrading on carbon emissions to provide empirical evidence for the above theoretical argument. The results show that fiscal decentralization and industrial structure upgrading are negatively correlated with carbon emissions, while the interaction term for fiscal decentralization with industrial structure upgrading presents a facilitating effect on carbon emissions. Besides, fiscal decentralization, industrial structure upgrading, and the interaction term have significant regional heterogeneity on carbon emissions. When fiscal decentralization and industrial structure upgrading are taken as threshold variables, the effects of industrial structure upgrading and fiscal decentralization are significantly nonlinear. Moreover, environmental regulation, transportation infrastructure, and carbon emissions are positively correlated. There exists an inverted U-shaped relationship between carbon emissions and economic growth, which proves environmental Kuznets curve theorem. However, FDI and urbanization have no significant effect on carbon emissions. According to the above conclusions, it is necessary to strengthen the positive interaction between fiscal decentralization and industrial structure upgrading in mitigating carbon emissions, promoting the green and low-carbon transformation of China's economy, thus realizing the goals of "carbon peak" and "carbon neutrality.", (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Industrial ecological efficiency is regarded as an urgent challenge that affects the development of ecological civilization and environmental governance. Here, we propose a data-driven approach to measure and promote regional industrial ecological efficiency. We collected data related to regional industrial development and used the Data Envelopment Analysis-Banker Charnes and Cooper (DEA-BCC) model to measure regional industrial ecological efficiency from a static perspective. The Malmquist index model was then used to measure regional industrial ecological efficiency from a dynamic perspective. In addition, we used a Tobit regression model to identify the factors affecting regional industrial ecological efficiency. Through a case study of regional industrial ecological efficiency, we demonstrate the specific application of the proposed data-driven approach. This study provides a new and effective tool for improving industrial ecological efficiency at a regional scale. This method can help enterprises and local governments improve industrial ecological efficiency, coordinate the relationship between industrial economic growth and the ecological environment, and boost regional efforts to achieve carbon peaking and carbon neutralization goals., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The digital economy is of great significant for countries to achieve carbon neutrality and carbon peak. Using country-level panel data from 2008 to 2018, this study empirically examined the impact of the development of the digital economy on carbon emissions and the associated transmission mechanisms by using the intermediary effect model. Our main findings are as follows. (1) The level of digital economy development varies greatly between countries, and the difference between "hyper-digitalized countries" and "under-connected countries" is increasingly obvious. (2) Development of the digital economy significantly reduces the carbon emission intensity, but promotes increases in the per capita carbon emissions. (3) Analysis shows that economic growth, financial development, and industrial structure upgrading play mediating roles between the digital economy and carbon emissions. Our study not only advances the study on digital economy and carbon emissions, but also provides a significant reference for policy makers to achieve carbon peak and carbon neutrality., Competing Interests: Declaration of competing interest 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., (Copyright © 2022 Elsevier B.V. All rights reserved.)

The clean and low-carbon transition of China's power sector is of great importance to the achievement of dual carbon targets and the control of global warming. This paper first estimates the remaining carbon budget of the power sector under a 1.5 °C temperature control target and on this basis constructs 1.5 °C and 2 °C power transition scenarios, examining key boundary conditions such as economic development and changes in the cost of power generation technologies. Second, the Genetic Algorithm-Extreme Learning Machine (GA-ELM) model is used to forecast the electricity demand for the next forty years. Finally, with the objective of minimising the total planning cost, a pathway optimisation model of the power system is constructed to explore the optimal transition path for the power system using the dual carbon target, carbon budget and electricity demand as the main constraints. The results of the study show that the carbon budget of the Chinese power sector is approximately 7.1 × 10 10 t CO2 for a 1.5 °C temperature control target. The electricity demand tends to saturate after 2050 and reaches 1.58 × 10 13 kWh in 2060. The time of the carbon peak and carbon neutralisation in the power sector is 5 years ahead of the double carbon target. By 2060, the power system will be dominated by new energy sources, with the proportion of installed non-fossil energy capacity at over 90% and the proportion of non-fossil energy generation at over 85%. Compared to that under the 2 °C temperature control target, the power sector under the 1.5 °C temperature control target needs to accelerate the pace of the low-carbon transition of electricity and deal with key issues such as the orderly withdrawal of coal power, the construction of a diversified clean energy system and the application of carbon capture devices. This study recommends that the process of building a zero-emissions power sector requires a good pace of the construction of new power systems at a suitable pace, increased efforts to tackle key technologies and improved relevant market mechanisms. China's carbon-neutral pathway in the power sector also has implications for other countries' clean, low-carbon transitions of their power systems., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Since the Chinese government proclaimed the "double carbon" goal in 2020, carbon emissions reduction has become an important task for the Chinese government. Cities generate more than 60% of carbon emissions. There are many challenges in achieving the "double carbon" goal for the cities of China. Science and technology innovation (STI) provides a feasible path, and the mechanism of STI influencing carbon emissions is analyzed. The STI factors, economic factors, energy factors, and population factors are studied based on the generalized Divisia index method. According to the decomposing results, science and technology innovation investment is the most important increasing factor in carbon emissions, and technology innovation investment efficiency is the most important decreasing factor, respectively. Three scenarios are set up and simulated with Monte Carlo technology evaluating the city of Xi'an in China. Under the baseline development scenario, it cannot achieve the carbon peak goal, and the uncertainty of carbon emissions increases. Under the green development scenario, it will peak in 2051, with a 95% confidence interval of 6668.47-7756.90 × 10 4 tons. Under the technology breakthrough scenario, the lower and median boundaries of carbon emissions peak at 4703.94 × 10 4 tons and 4852.39 × 10 4 tons in 2026, and the upper boundary peaks at 5042.15 × 10 4 tons in 2030. According to the Environmental Kuznets Curve theory, it will peak between 2028 and 2029 with a GDP per capita of CNY 153,223.85. However, it will fail to achieve the carbon neutrality goal by 2060, and should rely on the national carbon trading market of China to achieve the goal with a trading volume of 2524.61-3007.01 × 10 4 tons., Competing Interests: The authors declare no conflict of interest.

In the context of rapid urbanization and limited land amount, it is essential to scientifically evaluate the urban land green use efficiency (ULGUE) to promote regional sustainable development. Current studies are of great value for enriching the theoretical system and application research of ULGUE. Still, most of them only consider industrial pollution but ignore carbon emission as an essential environmental influencing indicator. This paper introduced carbon emissions into the input-output indicator system, measured ULGUE of 57 cities in the Yellow River Basin (YRB) over the 2004-2017 periods using the super-efficiency slacked-based measure (Super-SBM) model, analyzed its spatio-temporal patterns with the kernel density estimation (KDE) model and spatial autocorrelation model, and then identified the influencing factors with the Spatial Durbin model (SDM). As shown by the results, firstly, the ULGUE in the YRB over the 2004-2017 periods showed a trend of first decreasing and then increasing. Secondly, the ULGUE exhibited spatio-temporal imbalance characteristics across the YRB. Thirdly, ULGUE was the interaction of multiple indicators, and its influencing factors had spatial spillover effects. All in all, this paper is fundamental to the high-quality development of cities in the background of the Chinese policy of "carbon peak, carbon neutralization".

When and how to achieve a carbon peak is a concern for provincial regions within China under the context of achieving carbon neutrality in 2060. This study investigates the overall carbon peak environmental and resource impacts under current national targets and Shanghai's latest more aggressive carbon peak policy by using a dynamic multiple-region computable general equilibrium (CGE) model for the year 2030. Results show that (1) the national carbon peak and the more aggressive regional policy in Shanghai will result in energy consumption and carbon emissions decreases when compared to the business-as-usual scenario in most provinces; (2) although some cobenefits in water use reduction may occur in most provinces under the carbon policy scenarios, the results show positive and negative variations; (3) provincial level environmental and resources in transport, electricity, metal smelting and pressing, and agricultural production sectors are most influenced by Shanghai's aggressive carbon peak policy; and (4) the outsourced environmental and resource impacts from Shanghai to other provinces are very significant under Shanghai's aggressive carbon policy. These relevant results provide insights to facilitate broader governance decision-making for environmental resource nexuses while seeking an improved understanding of global sustainable development and climate governance.

To mitigate global warming, China, the world's largest greenhouse gas emitter, has set the goals of achieving carbon peak by 2030 and carbon neutrality by 2060, and financial measures could play an important role. To avoid unnecessary costs, China could learn from the experience of other countries to better understand the potential role of financial measures in achieving carbon emission reduction goals. Hence, this article adopts a SWOT analysis to compare the financial measures taken by Britain, Japan and the United States in the process of carbon emission reduction in the last twenty years. This article finds that government funds and financial innovation have contributed markedly to carbon emission reduction in those three countries. With the help of the SWOT analysis, we recommend that China take financial measures to help achieve carbon peaking and carbon neutrality goals from four aspects: formulating proper policy, regulating carbon trading market, strengthening international cooperation, and promoting innovation.

Under environmental governance constraints, in order to explore the quantitative contribution of green innovation efficiency to carbon peak and carbon neutralization at the urban level, this paper uses the unexpected Super-SBM model to measure the green innovation efficiency of each prefecture-level city based on the panel data of 40 prefecture-level cities in the Yangtze River Delta from 2010 to 2019. Furthermore, the panel fixed effect model is constructed, and the two-stage least squares estimation method is used for empirical research. It is found that green innovation efficiency can significantly reduce carbon emissions in the Yangtze River Delta, promote carbon emissions in the Yangtze River Delta to reach an early peak, and achieve the long-term goal of carbon neutrality as soon as possible. This conclusion is still stable after solving the endogenous problem and the influence of outliers. The results of regional heterogeneity analysis show that green innovation efficiency has remarkable effects on carbon emission reduction in Anhui and Zhejiang Provinces, and the emission reduction effect in Zhejiang Province is greater than that in Anhui Province. In addition, there exists obvious heterogeneity between different quantiles for the impact of green innovation efficiency on carbon emissions, showing an "inverted U" shape, and its intensity in the context of medium carbon emissions is greater than that of low carbon and high carbon emissions.

Exploring the low-carbon energy transformation pathway is vital to coordinate economic growth and environmental improvement for achieving China's carbon peak target. Three energy-target scenarios are developed in this paper, considering the targets of energy structure, electrification rate, and carbon mitigation towards 2030 announced by the Chinese government. A dynamic multi-sectoral computable general equilibrium model, CHINAGEM, is employed to examine the economic and environmental effects under different pathways of long-term low-carbon transformation. It detects that China's energy structure would substantially transfer to the low-carbon and clean one, whereas CO 2 , SO 2 , and NO X emissions in 2020-2030 would vastly abate along with all three energy-target scenarios. Different pathways would produce varying positive impacts on China's macro-economy and achieve the different extent of double dividend effects. It is highly conceivable for China to peak its carbon emission at 12.4 GtCO 2 by 2028 if it serves the comparatively more stringent low-carbon transformation pathways., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Carbon emissions from tourism are an important indicator to measure the impact of tourism on environmental quality. As the world's largest industry, tourism has many related industries and is a strong driver of energy consumption. The emission reductions it can achieve will directly determine whether China's overall carbon emission reduction target can be met. This paper analyzes the drivers of the evolution of carbon emissions from the tourism industry in China over the period 2000-2017 as a research sample using the Generalized Dividing Index Method (GDIM), and on this basis, it uses scenario analysis and Monte Carlo simulation to predict the carbon peak in tourism for the first time. The research results show that the scale of industry and energy consumption are the key factors leading to increased tourism carbon emissions, and the carbon intensity of tourism industry, energy consumption carbon intensity, investment efficiency, and energy intensity are the main factors leading to reduced carbon emissions from tourism. The scale of investment and the carbon intensity of investment have a dual effect; the scenario analysis and Monte Carlo simulation used to predict peak carbon in China's tourism industry show that the peak carbon will occur approximately in 2030. The government needs to further guide and encourage the tourism industry to increase investment activities targeting energy conservation and emission reduction. Under the conditions of strictly implementing energy conservation and emission reduction measures and vigorous promotion of the transformation and upgrading of tourism development methods, the tourism industry will have considerable potential to reduce carbon emissions., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

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]

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]

Copyright of Power Generation Technology is the property of Power Generation Technology 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.)

Carbon emissions are a global issue, especially among manufacturers, and China is facing many problems to lower such pollutants due to its goal of attaining carbon neutrality. This research applies a mathematical model to achieve the desired goal of decreasing CO 2 with the innovation of carbon neutrality tools and by moving towards high quality under the load capacity factor (LCF). We adopt a simulation-based optimization approach at different carbon peaks and manipulate various scenarios in order to find the best decisions for carbon neutrality tools. The results indicate that the green innovation fund, CO 2 emission tax, and CO 2 emission cap have significant roles in maximizing LCF. First, the green innovation fund plays a crucial part in reducing carbon emissions. Second, a CO 2 emission tax allows manufacturers to produce less than the green innovation fund and CO 2 emission cap. Third, the CO 2 emission cap strategy conversely allows manufacturers to produce more than the CO 2 emission tax strategy. This study provides reference for policymakers to achieve carbon neutrality and for the government to determine the best carbon-neutral tools under carbon peak. Lastly, the findings help manufacturers maximize LCF and profit and clean up the environment. [ABSTRACT FROM AUTHOR]

Based on historical land use for eight periods from 1980 to 2020 and the projected land use under seven Shared Socioeconomic Pathways (SSPs: SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP4-3.4, SSP4-6.0, and SSP5-8.5) from 2021 to 2100, we conducted a study on past and future land use changes in the Qinghai-Tibet Plateau (QTP). This work aims to reveal the land use changes during the carbon peak (2021–2040) and carbon neutrality (2051–2070) periods and at the end of the 21st century (2081–2100). The results show that: (1) in the historical period (1980–2020), the land use types in the QTP were grassland (1475×103 km2, 58.2%), barren land (685×103 km2, 27.0%), forest land (243×103 km2, 9.6%), water (114×103 km2, 4.5%), cropland (18.6×103 km2, 0.7%) and urban land (0.3×103 km2, 0.01%). (2) Relative to the baseline period (1995–2014), the area of grassland is projected to decrease by 0.7% (SSP4-6.0)–5.4% (SSP2-4.5) (0.5–3.9% of the total area of the QTP), 2.8% (SSP4-6.0)–12.5% (SSP3-7.0) (2.1–9.4% of the total area of the QTP) and 6.1% (SSP4-6.0)–21.7% (SSP4-3.4) (4.6–16.4% of the total area of the QTP) in the future three periods. In contrast, the forest land area is projected to increase, by approximately 2.5% (SSP4-6.0) to 30.1% (SSP3-7.0) (0.3–4.3% of the total area of the QTP), 9.2% (SSP4-6.0) to 56.5% (SSP2-4.5) (1.3–8.0% of the total area of the QTP), and 21.2% (SSP4-6.0) to 72.8% (SSP2-4.5) (3.0–10.2% of the total area of the QTP) in the future three periods, respectively. (3) Approximately 0.4 (SSP4-6.0) to 6.9% (SSP5-8.5), 0.9 (SSP4-6.0) to 2.7% (SSP4-3.4), and 0.04 (SSP5-8.5) to 3.5% (SSP1-1.9) of land is expected to convert from grassland to forest land in the future three periods, respectively. The shift from grassland to forest land area is likely to enhance the carbon sink potential of the QTP in the future period. [ABSTRACT FROM AUTHOR]

As the world's largest carbon emitter, China is facing great pressure to reduce emissions. With the country's proposed timeline for carbon peaking and carbon neutralization, a new goal has been established for China's low-carbon development. Based on the improved equal proportion allocation method, this paper allocates the overall carbon emission control goal for 2025 among 30 provinces and cities, based on 2015 figures, and measures and studies the country's carbon emission allocation efficiency on this basis. The results show that Beijing, Tianjin, Hebei, Shandong, Zhejiang, Shanghai, Jiangsu, Guangdong and Inner Mongolia need to increase their emission reduction capacity, while Jiangxi, Guizhou, Gansu, Qinghai, Hainan and Guangxi have relatively low emission reduction targets. Based on this allocation scheme, more provinces can reduce carbon emissions by increasing their efficiency with up-to-date technology, and a new vision for national allocation that is more easily accepted by all provinces and regions can be developed. Based on the research results of this paper, each province and region can choose its own low-carbon economic development path within the constraints of China's carbon intensity emission reduction targets, without compromising its own economic development characteristics. [ABSTRACT FROM AUTHOR]

• The net carbon emissions in china are forecasted under 15 scenarios during 2020–2150. • Doubling the pilot area can advance the achievement of dual-carbon target by 5 years. • A method to identify rooftop photovoltaic hotspots around the world is proposed. • 25 % of the world's hotspots can achieve the global 2050 carbon neutral target. Rooftop solar photovoltaics (RSPV) plays an important role in energy transition and climate goals. However, the contribution of RSPV to the dual carbon targets (DCTs) has not yet been quantitatively investigated at the national or global scale. Here, we investigate this contribution with an improved Stochastic Impacts by Regression on the Population, Affluence, and Technology (STIRPAT) model. We find out the time-advance effect of China's pilot RSPV program, i.e., doubling expansion of the current pilot area helps that the DCTs will be achieved 5 years ahead of schedule; a full expansion plan from merely six identified key provinces can be enough to guarantee that China will achieve carbon peak and carbon neutrality 5 and 4 years ahead of their respective time schedules. This effect implies global RSPV development; about 25 % of the world's buildable rooftops for RSPV installation will help reduce 1.4 billion tons of carbon emissions per year and thus achieve global carbon neutrality by 2050. The results will attract a widespread new energy community interested in expanding RSPV and helping governments formulate carbon reduction policies. [ABSTRACT FROM AUTHOR]

Existing practices have primarily focused on the accessibility and per capita indices of public service facilities (PSFs) in decision-making processes aimed at promoting social equity. However, the national commitment to achieving a carbon peak may induce additional considerations into the planning and policy decisions of PSFs for local governments. By conducting a two-stage simulation of carbon emissions (CEs) and correlation analysis, we identified uncertainties and confirmed the nonnegligible impact of land use structure, particularly PSF distribution, on achieving the urban transport-related carbon peak. Subsequently, we elaborated on the imperative of optimizing PSF distribution for carbon reduction, rather than solely depending on transport management strategies, through a case study of individual medical care travel characteristics. Moreover, a further discussion on the potential trade-offs and synergies between current and low-carbon-oriented PSF planning and policy decisions underscores the necessity of collaboration among decision-makers across pertinent administrative sectors. • Identified the uncertainties in reaching carbon peak through a two-stage simulation. • Revealed the necessity of optimizing public facility distribution towards carbon peak. • Investigated the underlying reasons of high-carbon trips. • Discussed the trade-offs and synergies between current and low-carbon oriented planning and policy decisions. [ABSTRACT FROM AUTHOR]

Copyright of Journal of South China Normal University (Natural Science Edition) / Huanan Shifan Daxue Xuebao (Ziran Kexue Ban) is the property of Journal of South China Normal University (Natural Science Edition) 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.)

The speedy raise of residential buildings' carbon emissions is a hindrance to achieving China's 2030 carbon peak goal. This study constructs an assessment framework for comprehensive consideration of 30 Chinese provinces' socioeconomic circumstances, energy demand, and emissions reduction technology to meet the consistent coupling degree of equity and efficiency (CDEE). This study is the first to propose an allocation scheme for equilibrating provincial carbon increments for rural and urban residential buildings in 2030 under carbon peaking constraints. The relevant results are fourfold. (1) Residential building's floor area per capita and energy carbon emissions coefficients are the soliddest drivers to facilitate and inhibit the raise of carbon emissions during 2010–2020. (2) Through dynamic Monte Carlo simulation from 2021 to 2030, we demonstrate that provinces with the most gamey carbon emissions in urban and rural areas include Shandong, at 121.52 (± 5.50) Mt. and Hebei, at 61.34 (± 3.08) Mt. in 2030, respectively. (3) A CDEE of 52.3% (biased equity) in urban areas and 34.5% (biased efficiency) in rural areas indicates equilibrated allocation of provincial carbon increment. (4) In the final 2030 allocation scheme, the greatest carbon mitigation pressures are in Beijing (11.34 Mt) and Heilongjiang (3.23 Mt), and the provinces with the largest carbon increment in urban areas include Hebei, Henan, and Guangdong, while the largest carbon increments in rural areas are in Hebei, Henan, and Guangdong. Overall, this study furnishes a targeted and valuable decision making reference for the government to determine provincial carbon peak goals for Chinese residential buildings. Theoretical framework of this study and provincial-level allocation outcomes of residential buildings' carbon emissions in China. [Display omitted] • A carbon emission forecasting model combining static and dynamic scenarios was built. • The coupling degree of equity and efficiency at the provincial scale was measured. • An incremental allocation scheme for provincial carbon emissions was ascertained. • The causes leading the difference of the provincial carbon increments were discussed. [ABSTRACT FROM AUTHOR]

China's road transport sector is pursuing an early carbon peak and ensuing significant carbon reductions. By combining a comprehensive bottom-up model with Monte Carlo simulation, this study evaluates the achievement probabilities of carbon peak goals of China's road transport. The results indicate that without policy intervention, realizing carbon peaking before 2028 is likely to occur, whereas achieving a 20% of carbon reduction by 2035 is difficult, with a probability of approximately 15%. Delivering current policy targets is of no effect on bringing forward carbon peak time or expanding emission reductions, mainly due to the insufficiency of electrification rate targets. This study suggests increasing the electrification rate targets and employing real-world fuel efficiency values as the base for measuring policy compliance. Further actions are recommended, such as proposing a sales ban on high fuel consumption vehicles, imposing carbon taxes, and strengthening emphasis on the truck sector. [Display omitted] [ABSTRACT FROM AUTHOR]

As the climate is warming up and climate disasters occur more frequently, China's carbon peak and carbon neutrality targets are gaining attention, with provinces starting to set carbon peak targets and constantly exploring low carbon economic development opportunities. However, the existing evaluation index system mainly focuses on low carbon cities and green cities, and there is no evaluation index system for carbon peak and carbon neutrality. This study adopts a combination of theoretical and empirical research and draws on domestic and international research results to construct the first index system for evaluating China's provincial carbon peak and carbon neutrality. The evaluation index system includes 18 indicators from three dimensions: climate ambition, low carbon status, and emissions trends. Using this index system, we calculated the carbon peak and carbon neutrality indices of 30 Chinese provinces. Further, the 30 provinces were classified into six categories, and corresponding policy recommendations for achieving the "Dual carbon" targets were put forward. The evaluation index system constructed in this paper can provide a reference for future carbon peak and carbon neutrality assessments. By disclosing the integrated index of each province, we hope to effectively curb the increasing local carbon emissions; avert inaction in areas with good natural endowments; and motivate the advancement of the latter, to boost the implementation of the "Dual carbon" targets coherently for the whole country. [Display omitted] • An integrated evaluation system on China's Provincial "Dual carbon" was proposed. • 30 provinces in mainland China were ranked based on the integrated index. • 6 groups were classified to show provincial differences on dual carbon performance. • Policy recommendations to fulfill China's climate commitment were put forward. [ABSTRACT FROM AUTHOR]

• Reveal the complex mechanism in coupling developing CCUS and renewable energy. • Assess the economic effects of CCUS and renewable energy penetration by a CGE model. • Identify the optimal policy intensity to deploy CCUS and renewable energy in power sector. • Explore the impact of CCUS application on carbon peak in China's new power system. • Building a green energy dominated power system is harder than the carbon peak target. Carbon capture, utilization, and storage (CCUS) is identified as a critical decarbonization technology that is expected to be applied globally on a large scale, especially in a thermal power-dominated power system. To achieve a carbon peak in the power sector, assessing the environmental and economic effects, including the costs of CCUS application and the decarbonization efficiency, is essential for making a reasonable CCUS policy. However, there is still a research gap in identifying the proper CCUS application intensity considering the dynamic changing renewable energy percentage and power quantity. Therefore, this study constructs a "dynamic system- computable general equilibrium" (SD-CGE) model to reveal the industrial and macro impacts of CCUS application policies by comprehensively evaluating the social, economic, and environmental effects of CCUS application scenarios where different policy intensities are set. Using China as a typical case, the results show that, first, the policy of applying CCUS combined with renewable energy penetration will contribute to reaching the power sector's carbon peak, however, building a new power system dominated by green power is a more challenging goal. Second, regarding the CCUS application intensity combined with renewable power penetration rate, it is proper to suggest setting the policy intensity as "medium-medium" for the optimal environmental and economic effects. Consequently, the power sector's carbon peak year will be 2025, while green power will dominate the power supply in 2030. Third, through the model's validation check, the models and results in this study are shown to be accurate and robust. This study provides policy support for constructing China's new power system, is conducive to achieving the national carbon peak goal, and provides other countries with theoretical tools to study similar problems. [ABSTRACT FROM AUTHOR]

Due to large energy consumption and carbon emissions (ECCE) in the building sector, there is huge potential for carbon emission reduction, and this will strongly influence peak carbon emissions and carbon neutrality in the future. To get a better sense of the current research situation and future trends and to provide a valuable reference and guidance for subsequent research, this study presents a summary of carbon peak and carbon neutrality (CPCN) in buildings using a bibliometric approach. Three areas are addressed in the review through the analysis of 364 articles published from 1990–2021: (1) Which countries, institutions, and individuals have conducted extensive and in-depth research on CPCN in buildings, and what is the status quo of their collaboration and contributions? (2) What subjects and topics have aroused wide interest and enthusiasm among scholars, and what are their time trajectories? (3) What journals and authors have grabbed the attention of many scholars, and what are the research directions related to them? Moreover, we propose future research directions. Filling these gaps will enrich the research body of CPCN and overcome current limitations by developing more methods and exploring other practical applications. [ABSTRACT FROM AUTHOR]