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China is the top emitter of greenhouse gases in the world. Pulp and paper industry is one of eight the strictly regulated industries about carbon emission in China. However, estimates of carbon emissions from China's pulp and paper industry have been suffered from remarkable uncertainty. It is summarized that is aroused by the inaccuracy of factors evaluating energy consumption, and the huge gap between the calculation standards for assessing energy consumption in the production process and the actual level recorded in the factories. This paper re-evaluated the carbon emission of China's pulp and paper industry from the perspective of life cycle assessment, and applied more accurate emission factors, taking account of the actual energy consumption of the production process in factories, to estimate the actual carbon emissions in maximum. It is found that the national standards about the energy consumption quota of China's pulp and paper industry is no longer applicable, and the actual energy consumption regulated in the production process is far better than the advanced level given by the national standards. The greenhouse gas emission have been seriously overestimated approximately 12.00%–56.17% by international organizations. • Life Cycle Analysis of the China's pulp and paper Industry is conducted thoroughly. • The pulp flow of China's pulp and paper Industry is analyzed. • Energy regulated in factory is far better than the national standards' required. • Carbon emissions of China's pulp and paper Industry are overestimated. [ABSTRACT FROM AUTHOR]

China's rapid urbanization has led to the development of integrated transport networks, which requires the transport sector to pay particular attention to the integrated transport comprehensive carrying capacity (ITCCC). Concurrently, global climate change has focused the world community's attention on greenhouse gas concentrations like CO2. This study establishes an ITCCC measurement model of urban agglomerations (UAs) and measures the comprehensive carrying capacity from four factors: socio-economic, basic resources, transport facilities, and traffic environment. In particular, this paper takes carbon emission as a critical indicator of the traffic environment when considering the impact factors of ITCCC. Based on the data of China's five major UAs, this study estimates carrying capacity levels with the ITCCC model and analyses regional characteristics using the spatial-temporal differentiation method. The results show that the traffic environment significantly impacts the ITCCC. Further low-carbon transport policies and measures are recommended to achieve sustainable development of integrated transport in UAs. [ABSTRACT FROM AUTHOR]

To reduce energy use and achieve a low carbon production in pulp and paper industry (PPI), it is essential to improve energy efficiency in pulp and paper production. In this study, the energy savings from the PPI were estimated based on a techno-economic analysis by EAGER tool for PPI at the factory level. The structure and implement procedure were introduced initially. Two typical pulp and paper mills from China were determined to estimate the impact of selected energy efficiency technologies (EETs) on energy savings as the cases in the base year. One Factory (A) only produced paper products (i.e. corrugated paper and Kraft linerboard) while the other Factory (B) also produced market pulp besides sack paper. In totally 22 selected EETs were applied to assess their saving potential in Factory A, and 29 measures were applied in Factory B. The results show that 2290 TJ and 1179 TJ of final energy could be saved annually in Factory A and B, corresponding to reduction of 29.4% and 13.6% total energy consumption respectively for the case factories. The CO 2 reduction potential was 32.3% for Factory A compared with that of 16.6% in Factory B. It suggests that the pulp and paper mills should encouraged to use this method estimating energy saving potential, and improve their energy efficiency with suggested measures in order to reduce energy consumption and related carbon emissions further in the coming years. • Energy savings of pulp and paper production were estimated at the factory level. • A techno-economic evaluation tool was applied to access the energy savings and carbon emission reductions. • Two typical pulp and paper factories from China were investigated to estimate their energy savings in the base year. • It is useful to assess energy savings and select feasible EETs in achieving energy saving and emission reduction targets. [ABSTRACT FROM AUTHOR]

The power sector is one of the major CO2-emitting industries in China. It is also the first key emissions control industry included in China's national carbon trading market established in 2021. Therefore, based on the data of 30 provinces and cities in China from 2015 to 2022, this study analyzes the impact of the national carbon market policy on the carbon emissions of the power industry based on the generalized Difference-in-Difference (DID) model. Based on the method of text analysis, this paper constructs the carbon market policy intensity index of each region and incorporates it into the DID model. Empirical analysis finds that the national carbon market policy can significantly inhibit the carbon emissions of the power industry. However, the heterogeneity analysis of 30 provinces and cities shows that the national carbon market policy has a significant impact on the regions that already have a carbon pilot, but not on the non-pilot regions. Therefore, this paper demonstrates the effectiveness of the national carbon market policy in the power industry emissions control, and also exposes the heterogeneity between regions, providing an important empirical basis for the inclusion of other energy-intensive industries. [ABSTRACT FROM AUTHOR]

The land use, land-use change and forestry (LULUCF) sector, as a source and a sink of greenhouse gas (GHG) emissions, is critical for achieving carbon neutrality. Many academic journals have published papers on land use carbon emission or sink (LUCES), but LUCES reviews are relatively rare, which poses great challenges in accurately understanding the research progress and future prospects. This work analyzes the research characteristics, hotspots and future perspectives of LUCES research by using a bibliometric analysis (such as DDA, VOSviewer, CiteSpace software) and a review based on the data (6115 scientific papers) during 1991–2023 from the Web of Science (WoS) platform. We found that (1) over the past 33 years, it first presented a steady growth, then fluctuating growth, and finally a rapid growth trend in the yearly number of publications in LUCES research. The USA (17.31%), China (14.96%), and the UK (7.37%) occupy a dominant position in this research field. (2) The related LUCES research is interdisciplinary, which mainly cover science and technology, meteorology and atmospheric sciences, geology, and environmental sciences and ecology disciplines. (3) The research hotspot analysis on LUCES shows that these articles mostly covered the follow three aspects: ecosystem services, climate change, and carbon neutrality. (4) A review of the past LUCES literature suggests that it is mainly focused on exploring the forefront issues in terms of the definition and boundaries, evaluation method and influencing factors, etc. This work suggests that further research could explore the main scientific problems on quantification of land-based carbon neutrality, quantitative analysis of the impact mechanisms, as well as interdisciplinary research and collaborative governance needed for carbon neutrality. [ABSTRACT FROM AUTHOR]

The importance and urgency of domestic solid waste (DSW) source segregation in universities is self-evident. Although many universities have carried out waste management, however, a comprehensive summary for successful implementation work of DSW segregation is lacking. This study summarizes the mechanism of DSW segregation in Chinese university based on questionnaire survey, on-site inquiry and sampling analysis in a comprehensive university in Shanghai. Questionnaire survey show that it is critical for encouraging students to participate in waste segregation to build convenient segregation facilities and humanized segregation reward and punishment method. The strengthened publicity and education due to the advantages in environmental discipline, easy-operating waste dumping site/facility as well as personalized solutions for different functional areas (teaching building) were considerably important strategies for implementing efficient waste segregation. The recyclables that were collected by intelligent recycling device and mobile recycling enterprise were dominated by paper, and the amounts increased dramatically during the graduation season. Therefore, the university correspondingly increased the collection frequencies of waste and the number of segregation guiders in the period to decrease the potential risk of fire safety. The study could provide a valuable reference for efficient implementation of waste segregation on university/college in China. [ABSTRACT FROM AUTHOR]

An extended STIRPAT model was constructed to explore the impact of green consumption behaviors on carbon emission. Based on the panel data of 30 provinces in China from 2005 to 2019, this paper analyzed the effect of green consumption behaviors, regional population size, economic development level and technological level on carbon emission, and then forecasted the carbon emission in eastern, central and western China from 2020 to 2035. The results demonstrate that carbon emission increases with the expansion of population size; green consumption behaviors have a significant moderating effect on carbon emission and alleviate the pressure of population growth on carbon emission; instead of following the environmental Kuznets curve, the trend of carbon emission shows an inverted "N" curve with economic growth; There is a positive correlation between technological progress and carbon emission; the increase in the level of consumers' expenditure and the ratio of the secondary industry output value over the total GDP lead to an increase in carbon emission, while the improvement of the urbanization level reduces carbon emission. Policy implications and prospects are also discussed. [ABSTRACT FROM AUTHOR]

Reasonably and effectively formulating the best route for urban waste transportation vehicle is particularly important for realizing low carbon and environmental protection of Green China construction concept. However, the current path planning method has shortcomings such as local optimization. In order to solve this problem, this paper aims at low carbon and environmental protection construction needs and proposes a routing optimization method of waste transportation vehicles based on improved ant colony algorithm. Firstly, the mathematical model of Vehicle Routing Problem (VRP) is constructed by considering transportation distance and carbon emissions cost. Then, network parameters in traditional ant colony algorithm are combined and optimized to realize self-adaptive update in the whole cycle. Furthermore, the neighborhood algorithm is used to iteratively optimize improved algorithm to avoid the defects of local optimization when solving VRP problem. Finally, the simulation results based on an actual dataset in North China show that the proposed method can achieve efficient and accurate optimal routing optimization for complex samples, and its solution stability index Pbest is 0.87 and the average deviation Var is 0.011, the lowest distribution cost after optimization is about 3,080 yuan, which are better than the comparison methods. [ABSTRACT FROM AUTHOR]

Transportation is the key carbon emission source after energy supply and industrial production. Under the vision of carbon peak and carbon neutralization, the pressure of reducing carbon emissions in transportation will be greater in the future. This paper constructs a model that takes transportation carbon emission as the main target and freight transportation utility value as the auxiliary target. The constructed model satisfies the constraints of freight turnover in the whole society, freight economic and social benefits, and the ecological constraints of the freight system. With MATLAB, the freight turnover of roadways, railways, and waterways (excluding ocean transportation) in 2030 is solved by using the adaptive genetic algorithm. The results indicate that (I) compared with the current freight structure of China, the roadway freight sharing rate in 2030 will decrease by 8.07%, and the railway freight sharing rate and the waterway freight sharing rate (excluding ocean transportation) will increase by 0.93% and 7.13%, respectively. (II) After optimization, the energy consumption and carbon emission are reduced by 42,471,500 tons (10.3%) and 91,379,400 tons (10.2%) of standard coal, respectively. (III) The adaptive genetic algorithm outperforms the traditional genetic algorithm in terms of convergence speed and accuracy. (IV) As the weight coefficient of carbon emission increases, the utility value of freight transportation consistently decreases, and the sensitivity increases. Meanwhile, as the carbon emission weight coefficient increases, carbon emission keeps decreasing, and the sensitivity decreases. [ABSTRACT FROM AUTHOR]

As the digital economy grows rapidly around the world, how would it impact carbon emissions? This paper discusses this issue from the perspective of heterogeneous innovation. Based on the panel data of 284 cities in China from 2011 to 2020, this paper empirically examines the impact of the digital economy on carbon emissions as well as the mediating and threshold effects of different innovation modes. The study finds that the digital economy can significantly reduce carbon emissions; this conclusion holds after a series of robustness tests. Independent innovation and imitative innovation are important channels through which the digital economy affects carbon emissions, but technological introduction is not an effective way. For regions with high levels of financial investment in science and innovative talents, the reduction in carbon emissions from the digital economy is more significant. Further research shows that the effect of the digital economy on carbon emissions has a threshold feature, with an inverted U-shaped relationship between the two, and that an increase in autonomous innovation and imitation innovation can enhance the digital economy's carbon reduction effect. Therefore, it is necessary to strengthen the capacity of independent innovation and imitation innovation to exploit the carbon-cutting effect of the digital economy. [ABSTRACT FROM AUTHOR]

In the context of carbon neutralization and carbon peak, carbon reduction in key industries has become a central topic in our country. As an important part of technological progress, it is necessary to study the effect of technology import on carbon emission reduction in key industries. Based on the panel data of 30 provinces. from 2011 to 2020, this paper used the fixed-effect model to analyze the emission reduction effect in key industries on the development status of technology import. The spatial econometric model was used to analyze the spatial characteristics of carbon emissions of technology import and key industries. Then, the mediating effect model was used to bring industrial technological innovations into the research category to analyze the mediating role of technology imports on the carbon emissions of key industries. Finally, a robustness test proved the reliability of the model. The findings were as follows: (1) Technology import significantly promoted carbon emission reduction in key industries; (2) In terms of the spatial relationship, technology import and carbon dioxide emissions had significant spillover effects, and there were trends of high and high aggregation and low and low aggregation, with the impact of technology import on carbon dioxide emissions having a siphon effect; (3) Industrial technological innovation played an intermediary role in this path, but it was a negative role, which was not, in general, conducive to the reduction of carbon emissions of key industries. On this basis, the paper puts forward several policy suggestions. [ABSTRACT FROM AUTHOR]

As the largest energy consumer, China's control of carbon emissions from energy consumption plays a pivotal role in world climate governance. However, few studies have been conducted to explore the emission reduction pathways that promote a high level of synergy between China's economic growth and the " carbon peaking and carbon neutrality " goal from the perspective of energy consumption. Based on the measurement of energy consumption carbon emissions, this paper reveals the spatial and temporal distribution and evolution trends of carbon emissions in China at the national-provincial level. The multi-dimensional socio-economic factors such as R&D and urbanization are taken into account, and the LMDI model is used to decompose the driving effects of energy consumption carbon emissions at the national-provincial levels. Further, this paper combines the Tapio decoupling index with the LMDI model to decompose the decoupling states of China year by year and at the provincial level in four periods to explore the reasons for the change of carbon decoupling states. The results show that: (1) China's energy consumption carbon emissions grew at a high rate before 2013, and slowed down after that. There are significant differences in the scale and growth rate of carbon emissions among provinces, which can be classified into four types accordingly. (2) The R&D scale effect, urbanization effect, and population scale effect are the factors driving the growth of China's carbon emissions; while the energy structure effect, energy consumption industry structure effect, energy intensity effect, and R&D efficiency effect inhibit the growth of China's carbon emissions. (3) Weak decoupling is the most dominant decoupling state in China from 2003 to 2020, and the decoupling state varies significantly among provinces. According to the conclusions, this paper proposes targeted policy recommendations based on China's energy endowment. [ABSTRACT FROM AUTHOR]

To achieve the goals of "carbon peaking and carbon neutrality", this paper puts forward the connotation and measurement method for the carbon emission intensity of urban industrial land and conducts an empirical study with the Yangtze River Economic Belt (YREB) as an example. We defined the carbon intensity of urban industrial land as the industrial carbon emissions per unit area of land, which is a spatial mapping of urban industrial economic development and carbon spillover and a key indicator for urban and territorial spatial planning oriented towards the "dual carbon" goal. Findings: The carbon emission density of industrial land in the YREB varied greatly between cities and exhibited significant positive spatial autocorrelation. In addition, the geographical pattern and spatio-temporal evolution model of the urban industrial land carbon emission density had a very complex driving mechanism, and different factors had significant synergistic effects. Therefore, it is suggested that while striving towards the goal of "dual carbon", the government should incorporate the carbon emission density indicator of urban industrial land into the urban and territorial spatial planning system, and based on the threshold of the medium suitable density, they should design differentiated management policies according to concrete urban policies and encourage cooperation among cities to jointly promote carbon emission management of urban industrial land. In policy design, emphasis should also be placed on highlighting the interactive effects of foreign direct investment, fiscal expenditure, and the number of patent authorizations as well as constructing a combination of policies centered around them to better leverage the impacts of globalization, government intervention, and innovation. [ABSTRACT FROM AUTHOR]

Many regions or countries seek to transition to a low-carbon economy, but there is ambiguity about how carbon emissions change with economic growth. This paper captures characteristics of carbon emissions in China using the Tapio Method. To detect driving factors of carbon emissions in economic growth, we adopt the Log-Mean Divisia Index decomposition method. The results of the paper are as follows: (1) Economic growth in most regions of China has outpaced the growth rate of carbon emissions, showing the characteristics of decoupling. (2) Metropolitan cities have a greater impact on the level of decoupling in neighboring provinces and municipalities. (3) The decoupling of carbon emissions from economic growth is caused by declining energy intensity in China. (4) The energy mix and industrial structure have little impact on the growth rate of carbon emissions. In addition, some policy implications are summarized according to the findings of this paper. [ABSTRACT FROM AUTHOR]

As governments of various countries attach importance to green transportation, governments have focused their attention to understanding how they can shift the cargo shipping in coastal areas from land to water. Motivated by this, this paper establishes a green policy design model for coastal transportation systems. The model aims to minimise the comprehensive cost (i.e. the sum of the transportation cost and carbon emission tax) in the research area and optimise the government's shipping network design scheme and waterway freight rate control scheme under the established subsidy level. An active set algorithm is designed that can explore the local optimal solution of the model. Taking the Bohai Rim region of China as the research area, sensitivity analyses of different subsidy scales and origin-destination demand scales are carried out. The results show that the government's policy schemes will lead to a significant shift in the mode of transportation used for cargo. [ABSTRACT FROM AUTHOR]

In order to explore the evolution process of regional vegetable circulation efficiency and its influencing factors, this paper uses Super-SBM model considering unexpected output and GML index to calculate the vegetable circulation efficiency of 13 provinces (cities) in Central China and its surrounding areas from 2015 to 2019, then conducts spatial autocorrelation analysis on the vegetable circulation efficiency in this region through Moran index. Finally, SPDM model is constructed to explore the spatial effect of the influencing factors on the vegetable circulation efficiency in this region. The results show that (1) the vegetable circulation efficiency of most provinces (cities) in this region is low. (2) The Global Moran's I of the vegetable circulation efficiency in this region is positive, that is, the vegetable circulation efficiency in this region shows a certain degree of spatial agglomeration effect. (3) The level of scientific and technological innovation and the degree of government support have significant positive direct and indirect effects on the efficiency of vegetable circulation in the region, the quality of workers has significant positive indirect effects, and the level of economic development and industrial structure have significant negative indirect effects. [ABSTRACT FROM AUTHOR]

It has been a crucial challenge for countries worldwide to reduce carbon dioxide (CO2) emissions. China is developing policies among various industries to peak CO2 emissions as soon as possible and expects the reduction of CO2 emissions through financial development. This paper explores the influencing mechanism of financial development on CO2 emissions based on panel data from provinces in China, considering constraints of technological innovation and fossil energy dependence among provinces and periods. Empirical results consistently indicate that the effect of China's financial development on CO2 emissions per capita is significantly negative, and it also presents an inverted U-shaped pattern. In those provinces or periods witnessing lower technological innovation and higher fossil energy dependence, the financial development has more significant effect on carbon emission reduction. This result suggests that regions with deficiencies in the development of technology industries, lower proportions of the tertiary industry, and a higher percentage of the secondary industry need to focus more on the value of financial development. [ABSTRACT FROM AUTHOR]

By decomposing the changes of carbon emissions into effects of economic growth, industrial structural change, technological change and energy structure change, the paper firstly discusses the contribution of each effect to China's carbon emission changes between 2020 and 2030, and forecasts China's total carbon emissions in 2030. In particular, the paper strengthens that a decrease in population and a significant slowdown in urbanization will significantly reduce the construction demand, the main driver for high growth of carbon emissions in China, and provide a relatively favorable economic environment for China to achieve carbon peaking by 2030. The paper then discusses on how to achieve the "dual carbon" goals with the lowest possible economic cost by relying on market and price mechanisms. [ABSTRACT FROM AUTHOR]

The steel industry is a major source of CO2 emissions, and thus, the mitigation of carbon emissions is the most pressing challenge in this sector. In this paper, international environmental governance in the steel industry is reviewed, and the current state of development of low‐carbon technologies is discussed. Additionally, low‐carbon pathways for the steel industry at the current time are proposed, emphasizing prevention and treatment strategies. Furthermore, the prospects of low‐carbon technologies are explored from the perspective of transitioning the energy structure to a "carbon–electricity–hydrogen" relationship. Overall, steel enterprises should adopt hydrogen‐rich metallurgical technologies that are compatible with current needs and process flows in the short term, based on the carbon substitution with hydrogen (prevention) and the CCU (CO2 capture and utilization) concepts (treatment). Additionally, the capture and utilization of CO2 for steelmaking, which can assist in achieving short‐term emission reduction targets but is not a long‐term solution, is discussed. In conclusion, in the long term, the carbon metallurgical process should be gradually supplanted by a hydrogen–electric synergistic approach, thus transforming the energy structure of existing steelmaking processes and attaining near‐zero carbon emission steelmaking technology. [ABSTRACT FROM AUTHOR]

Financial development (FD) is pioneered to solve the problem of vital capital supporting for carbon neutrality. Detecting the effect of FD on carbon emissions (CE) plays an important role in accurately planning FD, and guiding carbon neutrality in China. To clarify the influence of FD on CE and the underlying pathways concerning scale effect, structural effect, and technological effect, this paper use China’s 285 city-level data spanning 2003–2016 and fixed effect (FE) models and instrumental variable (IV) methods to test the effect of FD on carbon neutrality in China. The findings show that (1) the development of financial deepening, financial interrelation ratio, and financial intermediary all prompt carbon emissions at the national level. (2) Regional heterogeneity indicates that FD benefits carbon neutrality in mid-Western cities but fails in eastern cities. (3) FD increases carbon emissions by boosting electricity consumption but decreases carbon emissions by promoting structural optimization and technological progress. (4) Environmental regulations partially curb the carbon emissions effect of FD. This paper proposes some suggestions to reduce CE and gain carbon neutrality in China by greening FD, optimizing industrial structure, promoting technologi)cal innovation and strengthening environmental regulation. [ABSTRACT FROM AUTHOR]

To reduce industrial carbon emissions, various industries have been seeking ways to reduce their own emissions. Implementing carbon trading system measures is one way to effectively control industrial carbon emissions. However, in different industrial sectors, carbon trading systems have different impact. The 14-year provincial panel data (2005–2019) were analyzed by using the propensity score matching and the difference-in-difference model to evaluate the role of the emission trading system (ETS) in reducing emissions from different industries. According to the study, ETS has reduced carbon emissions from the agricultural production sector by 1.6876%. Secondly, it also had a significant inhibitory effect on the manufacturing sector, about 24.0489. Mining, electricity production, wholesale and other industrial sectors are insignificant disincentives, and construction and transportation are insignificant facilitators. China's ETS, therefore, mainly acts as an inhibitory force for different industries, which can effectively reduce their carbon emissions. [ABSTRACT FROM AUTHOR]

The massive use of energy has caused a rapid increase in global carbon dioxide emissions, resulting in a series of environmental problems such as climate warming. Investment in the energy industry can guide funds into green and clean production, reduce carbon emissions in the energy industry, and promote the green development of the energy industry. This paper considers the energy, the environment, the economy, and other factors and focuses on energy consumption and investment structure. Taking 30 provinces in China as research samples, a dynamic spatial Durbin model is established. The results show that the first-order term of carbon emissions has a driving force of 0.5068% for current carbon emissions at a significance level of 1% and that the increase in current carbon emissions will lead to a continued increase in carbon emissions in the next period. The increase in the carbon emissions of neighbouring provinces will increase their carbon emissions through the spatial spillover effect. Whether in the short term or long term, the increase in energy investment and the optimization of the energy investment structure can reduce carbon emissions. The above conclusions can provide a reference for the formulation of government environmental policies. [ABSTRACT FROM AUTHOR]

China's automotive industry has been dedicated to a series of carbon-reduction efforts and has strived for comprehensive green and low-carbon transformation in order to achieve carbon peaking and carbon neutrality goals. On the basis of automobiles' whole life-cycle (WLC) carbon emission accounting, this paper calculates life-cycle carbon emissions per vehicle, proposes green and low-carbon development path for China's automotive industry, quantifies and analyzes implicated carbon-reduction potential, and puts forth suggestions for high-quality green and low-carbon development of China's automotive industry. The first is to establish a sound standard and data management system; the second is to promote research, development and application of low-carbon materials and low-carbon technologies; the third is to accelerate the pace of fostering a new consumption model in the automotive industry. The research results can further support national policy-making regarding carbon emissions, promote corporations' research, development and application of low-carbon technologies, encourage green and low-carbon consumption, and lead the automotive industry to achieve WLC neutrality. [ABSTRACT FROM AUTHOR]

Wind power generation does not emit greenhouse gases or pollutants, but there are some carbon emissions from the manufacturing, transportation, operation, and waste disposal of wind turbines. Directly driven permanent magnet and doubly fed asynchronous wind turbines currently have the largest market share in China, but few Chinese studies have compared their differences in carbon reduction potential. This paper uses life cycle assessment (LCA) to quantitatively analyze the full life cycle carbon emissions of the two wind turbines to determine which type of wind turbine has greater carbon reduction potential, obtaining the following results. (1) The full life cycle greenhouse gas emissions of 2.5 MW directly driven permanent magnet and doubly fed asynchronous wind turbines are 8.48 and 10.43 g CO2/kWh, respectively. The direct‐driven permanent magnet wind turbine is superior in terms of carbon reduction. (2) The stage with the greatest impact and the greatest difference between the two wind turbines in the full life cycle is the production stage, during which the carbon emissions of the directly driven permanent magnet and doubly fed asynchronous wind turbines are 1.045 × 106 and 1.210 × 106 kg, respectively. (3) According to sensitivity analysis, proper waste disposal and transportation can reduce carbon emissions from wind turbines. These research findings can be used to help achieve carbon peaking and neutrality goals, as well as the technological development of wind power enterprises. [ABSTRACT FROM AUTHOR]

Due to the emission of carbon dioxide and other greenhouse gases, the global climate is warming. As the world's biggest emitter of carbon emissions, China faces a more severe challenge in reducing carbon emissions than developed countries. A reasonable prediction of the carbon peak in China will help the government to formulate effective emission reduction paths. This paper analyzes the changes in carbon emissions in China from 2004 to 2020, uses the STIRPAT model and scenario analysis method to predict carbon emissions from 2021 to 2030, and then calculates the carbon efficiency during carbon peaking to select the most effective carbon peak path for China. The results show that China's carbon emissions increased year by year from 2004 to 2020. Under the baseline scenario, China is unlikely to reach its carbon peak before 2030. Under the regulatory scenarios, China can reach its carbon peak before 2030. The peak values from high to low are seen with the rapid development-weak carbon control scenario, rapid development-intensified carbon control scenario, slow development-weak carbon control scenario and slow development-intensified carbon control scenario, respectively. Correspondingly, China will peak its carbon emissions in 2029, 2028, 2028 and 2028, respectively, according to these scenarios. The carbon efficiency under the rapid development-weak carbon control scenario is the highest, which means that accelerating the growth rate of population, GDP and urbanization while moderately carrying out the transformation of industrial structure and energy structure is an effective way to achieve the goal of "carbon peak by 2030". [ABSTRACT FROM AUTHOR]

Based on the relationship between industrial agglomeration, green finance development, and carbon emissions, some relevant theoretical hypotheses are proposed, and this paper employs the combination of spatial Durbin model and panel threshold model to empirically test data from 30 provincial regions in China from 2006 to 2019. The results show that the agglomeration of high energy-consuming industries has an inverse U-curve relationship with carbon emission intensity, and the development of green finance will inhibit the growth of carbon emission intensity. There are significant spatial characteristics of high energy-consuming industrial agglomeration, green financial development, and carbon emissions. And the intensity of local carbon emissions will be influenced by the agglomeration of high energy-consuming industrial agglomeration and green financial development in local and neighboring areas. Moreover, green financial development plays a moderating role in the relationship between high energy-consuming industrial agglomeration and carbon emissions, and the role of high energy-consuming industrial agglomeration and green financial development on carbon emissions has a threshold effect due to the mismatch between the two developments. Under different levels of green financial development, the influence of high energy-consuming industrial agglomeration on carbon emissions varies widely, and green financial development helps to suppress the negative impact of high energy-consuming industrial agglomeration on carbon emissions. Accordingly, we argue that inter-regional joint prevention and control mechanism should be established for pollution control. And China should build more effective high energy-consuming industrial clusters to make them play an active role in reducing emissions. At the same time, China should accelerate the construction of green finance, strengthen the disclosure and transparency of green financial information, and establish a joint mechanism for the development of inter-regional green finance, so that it can contribute to regional industrial transformation and pollution control. [ABSTRACT FROM AUTHOR]

The operation of the national carbon emission trading market has brought new pressure to coal power plants in China. How to control the carbon emissions of the plants and ensure their power generation has become an important issue. This paper proposed a new production profit model based on risk constraint to explore a decision-making method for the plant's carbon emission and production. A branch-and-cut algorithm is applied in the optimization solver to achieve a large-scale constraint linear programming, where the conditional value-at-risk is evaluated by Monte Carlo simulation. Results from the numerical analyses of the coal plant of 4520 MW capacity show that, the carbon emission according to our method is reduced by 3.94%, while the annual profit is increased by 1.25% and the overall cost is decreased by 1.06%. The proposed approach is helpful for the coal plants to manage their carbon emissions and optimize their power production. [ABSTRACT FROM AUTHOR]

The thermal power industry takes the important social responsibility of energy conservation and environmental protection. The carbon emissions made by the thermal power industry are affected by the industrial structure. In this paper, the carbon emission of thermal power generation is divided into three links: energy combustion, desulfurization process, and power transportation. The total carbon emission of thermal power in 11 provinces in western China from 2000 to 2017 is calculated. Combined with industrial reform, this paper constructs a panel data fixed effect model to systematically analyze the interactive response relationship between thermal power carbon emission and industrial structure in the western region. The research shows that due to the continuous expansion of hydropower, wind power, and other new energy power generation scale and the improvement of energy efficiency in the western region, the growth trend of thermal power carbon emission has slowed down since 2010. The industrial development pattern is the main driving force of regional economic development, and the secondary industry in the western region is the main driving factor of thermal power carbon emission. High quality economic development in the western region can be promoted through technological upgrading, new energy development, and industrial multi-mode operation. [ABSTRACT FROM AUTHOR]

In the context of the joint operation of China's intra-provincial markets and inter-provincial trading, how to meet the load demand and energy consumption using inter-provincial renewable energy trading is a key problem. The combined operation of intra-provincial and inter-provincial markets provides a new way for provincial power companies to optimize and clear the intra-provincial power market, complete the intra-provincial consumption responsibility weight index, and consume renewable energy across provinces and regions. This paper combines power generation and consumption within the province, uses inter-provincial renewable energy trading to meet the load demand within the province and completes the index of intra-provincial consumption responsibility weights. The intra-provincial market trading and inter-provincial market clearing are respectively taken as the upper and lower levels of the model. Under the two-level electricity market operation framework, the upper-level model aims to minimize the expected total operating cost within the province considering the carbon emission cost and the weight of the consumption responsibility, while the lower-level model aims to minimize the inter-provincial renewable energy purchasing cost. Finally, the influence of inter-provincial transaction mechanism, risk aversion coefficient, voucher price, and responsibility weight on operating cost is analyzed. Simulation is used to verify that the proposed model can meet the requirements of the provincial load power consumption and the consumption responsibility weight index, and promote the consumption of renewable energy. [ABSTRACT FROM AUTHOR]

The rapid growth of the livestock and poultry production in China has led to a rise in manure generation, which contributes to the emissions of GHGs (greenhouse gases including CH4, N2O and CO2) and other harmful gases (NH3, H2S). Reducing and managing carbon emissions has become a critical global environmental imperative due to the adverse impacts of GHGs. Unlike previous reviews that focused on resource recovery, this work provides an unique insight of transformation from resource-oriented manure treatment to integration of resource recovery with pollution reduction, carbon accounting and trading, focusing on the sustainable development of manure management system. Considering the importance of accounting methodologies for carbon emission and trading system toward carbon neutrality society, suggestions and strategies including attaching high importance to the development of more accuracy accounting methodologies and more practical GHG emission reduction methodologies are given in this paper. This work directs the establishment of carbon reduction methodologies and the formulation of governmental policies for livestock and poultry manure management system in China. [ABSTRACT FROM AUTHOR]

A significant industrial transformation in China's tourism sector is currently taking place in response to carbon peak and carbon neutrality targets. This paper applies the data envelopment analysis (DEA) model to calculate the efficiency of the tourism industry under carbon emission constraints and further investigates its influencing factors through the Tobit regression. The results are as follows: (1) The tourism efficiency under carbon emission constraints of China from 2000 to 2019 showed a trend of first rising and then declining, and there were obvious regional differences; (2) from 2000 to 2019, the total factor productivity of tourism in China increased significantly, while the contributions of technical progress, pure technical efficiency, and scale efficiency decreased sequentially; (3) the factors of industrial structure, transportation convenience, economic development level, degree of opening to the outside world, and the level of scientific and technological development have varying degrees of influence on tourism efficiency. Based on the analysis results, this paper puts forward several policy suggestions on tourism efficiency and low-carbon development. The findings of this paper have some bearing on developing nations' efforts to boost tourism efficiency and realize high-quality industry growth within the framework of sustainable development. [ABSTRACT FROM AUTHOR]

This paper takes Jiangsu as an example to measure the carbon emissions from the electric power industry from 2002 to 2017, builds an extended STIRPAT model to quantify its driving factors, and uses the Monte Carlo method to simulate the evolution of carbon emissions in multiple scenarios from 2018 to 2030. The results show that: (1)Population scale, urbanization level, GDP per capita, industrial added value, and electricity consumption intensity promote the increase of carbon emissions in the electric power industry. (2)Trade openness and the transmission level of other provinces play a role in reducing carbon emissions. (3)Under the baseline scenario and the green development scenario, the carbon emissions of the electric power industry have shown a continuous growth trend, but the growth rate of carbon emissions has slowed down significantly under the green development scenario. [ABSTRACT FROM AUTHOR]

As the world's largest developing country, China has played an important role in the achievement of the global CO2 emissions mitigation goal. The monitoring and analysis of CO2 emissions in the Yangtze River Economic Belt (YREB) urban agglomerations is strategic to the carbon peak and carbon neutrality in China. In this paper, we revealed the spatial and temporal variations of CO2 emissions in Cheng-Yu urban agglomeration (CY-UA), Yangtze River Middle-Reach urban agglomeration (YRMR-UA), and Yangtze River Delta urban agglomeration (YRD-UA) in YREB and investigated the carbon emission development stage of YREB urban agglomerations. Particularly, a carbon emission development stage framework that considered the relationship between economic growth and carbon emissions was built based on Environmental Kuznets Curves (EKCs). Meanwhile, multiscale geographically weighted regression (MGWR) was used to analyze the impact of different influencing factors, including population (POP), GDP per capita (GDPPC), the proportion of secondary industry (SI), carbon emission intensity (CI), and urbanization (UR), on the CO2 emissions of three urban agglomerations. The results illustrate the following: (1) The CO2 emissions of YREB urban agglomerations decreased, with YRD-UA having the highest CO2 emissions among the three urban agglomerations and contributing 41.87% of YREB CO2 emissions in 2017. (2) CY-UA, YRMR-UA, and YRD-UA reached the CO2 emissions peak in 2012, 2011, and 2020, respectively, all of which are at the low-carbon stage. (3) POP and GDPPC show the greatest impact on the CO2 emissions of the three YREB urban agglomerations. [ABSTRACT FROM AUTHOR]

To explore the impact of promotion of electric vehicles on carbon emissions in China, this paper used the principal component analysis (PCA)-logistic regression model to predict the demand for traditional vehicles, and used the scenario analysis method to analyze the proportion of electric vehicles in traditional vehicles qualitatively. Then this paper calculated the carbon emissions during the power generation process based on the existing power structure. In addition, the IPCC carbon emission calculation method is used to compare the CO2 emissions produced by electric vehicles and fuel vehicles with similar vehicle quality while driving the same distance and consuming different energy sources. The results showed that the CO2 emissions of electric vehicles accounted for only 37.05% of fuel vehicles. By 2050, the annual electricity demand of electric vehicles will be 828.7, 776.9, and 752.1 billion kWh under the radical scenario, the reference scenario, and the negative scenario, respectively. According to the current power structure, the carbon emissions will be 1.2, 1.1, and 1 billion tons, respectively. The rapid growth of electric vehicles has a substantial impact on the grid load. Studying the changes in CO2 emissions from energy substitution is significant to formulate the development strategy of the automobile industry and adjust energy structure policies. [ABSTRACT FROM AUTHOR]

City cluster is an effective platform for encouraging regionally coordinated development. Coordinated reduction of carbon emissions within city cluster via the spatial association network between cities can help coordinate the regional carbon emission management, realize sustainable development, and assist China in achieving the carbon peaking and carbon neutrality goals. This paper applies the improved gravity model and social network analysis (SNA) to the study of spatial correlation of carbon emissions in city clusters and analyzes the structural characteristics of the spatial correlation network of carbon emissions in the the Yangtze River Delta (YRD) city cluster in China and its influencing factors. The results demonstrate that: 1) the spatial association of carbon emissions in the YRD city cluster exhibits a typical and complex multi-threaded network structure. The network association number and density show an upward trend, indicating closer spatial association between cities, but their values remain generally low. Meanwhile, the network hierarchy and network efficiency show a downward trend but remain high. 2) The spatial association network of carbon emissions in the YRD city cluster shows an obvious 'core-edge' distribution pattern. The network is centered around Shanghai, Suzhou and Wuxi, all of which play the role of 'bridges', while cities such as Zhoushan, Ma'anshan, Tongling and other cities characterized by the remote location, single transportation mode or lower economic level are positioned at the edge of the network. 3) Geographic proximity, varying levels of economic development, different industrial structures, degrees of urbanization, levels of technological innovation, energy intensities and environmental regulation are important influencing factors on the spatial association of within the YRD city cluster. Finally, policy implications are provided from four aspects: government macro-control and market mechanism guidance, structural characteristics of the 'core-edge' network, reconfiguration and optimization of the spatial layout of the YRD city cluster, and the application of advanced technologies. [ABSTRACT FROM AUTHOR]

The mechanism of the environmental regulations affecting carbon emissions is complex, and for many years it has been a hot research topic for researchers. However, few of the previous studies have focused on whether or not environmental regulations can potentially influence carbon emissions through technical efficiency. Therefore, the present study chose to investigate the mediation effects of the technical efficiencies between environmental regulations and carbon emissions using the provincial panel data of energy-intensive industries for the period ranging from 2005 to 2015. The results were as follows: (i) In regard to the entire group of energy-intensive industries, it was found that environmental regulations could not only potentially directly reduce carbon emissions, but also indirectly reduce carbon emissions through technical efficiency. In other words, technical efficiency had played a partial mediation role between the environmental regulations and the carbon emissions; (ii) It was observed that for the different subdivided energy-intensive industries, the different levels of technical efficiency had shown various mediation effects. For example, the mediation effects of technical efficiency in the petroleum processing and coking (PPC) industry; papermaking and paper products (PPP) industry, and raw chemical materials and chemical products (RCMCP) industry, were found to be similar to those of the whole energy-intensive industries. Furthermore, the "Porter Hypothesis" had been verified in the nonmetal mineral products (NMP) industry. However, there were no mediation effects observed in the smelting and pressing of ferrous metals (SPFM) and smelting and pressing of nonferrous metals (SPNM) industries; (iii) In this study, in accordance with the regression results of the double-threshold models, it was found that for the energy-intensive industries as a whole, the carbon emission reduction effects of environmental regulations had become stronger with the increases in technical efficiency. For the PPP and RCMCP industries, there was an inverted U-shaped relationship observed between environmental regulations and carbon emissions when the technical efficiency was taken as the threshold variable. Therefore, based on the research conclusions achieved in this study, some policy recommendations were put forward. • Environmental regulation reduces carbon emission of the energy intensive industries of China. • Technical efficiency plays a partial mediation effect between environmental regulation and carbon emission. • The mediation effects of technical efficiency differ in the subdivided energy-intensive industries. • The "Porter hypothesis" is verified in Nonmetal Mineral Products (NMP) industry. [ABSTRACT FROM AUTHOR]

Estimating carbon emissions and assessing their contribution are critical steps toward China's objective of reaching a "carbon peak" in 2030 and "carbon neutrality" in 2060. This paper selects relevant statistical data on carbon emissions from 2000 to 2018, combines the emission coefficient method and the Logarithmic Mean Divisia Index model (LMDI) to calculate carbon emissions, and analyses the driving force of carbon emission growth using Henan Province as a case study. Based on the partial least squares regression analysis model (PLS), the contributions of inter-provincial factors of carbon emission are analyzed. Finally, a county-level downscaling estimation model of carbon emission is further formulated to analyze the temporal and spatial distribution of carbon emissions and their evolution. The research results show that: 1) The effect of energy intensity is responsible for 82 percent of the increase in carbon emissions, whereas the effect of industrial structure is responsible for -8 percent of the increase in carbon emissions. 2) The proportion of secondary industry and energy intensity, which are 1.64 and 0.82, respectively, have the most evident explanatory effect on total carbon emissions; 3). Carbon emissions vary widely among counties, with high emissions in the central and northern regions and low emissions in the southern. However, their carbon emissions have constantly decreased over time. 4) The number of high-emission counties, their carbon emissions, and the degree of their discrepancies are gradually reduced. The findings serve as a foundation for relevant agencies to gain a macro-level understanding of the industrial landscape and to investigate the feasibility of carbon emission reduction programs. [ABSTRACT FROM AUTHOR]

Coal‐fired thermal power must be flexible to enable the grid absorption of inconsistent photovoltaic (PV) and wind power. Combined heat and power (CHP) coal‐fired plants are the primary source for district heating systems. This paper uses a 330 MW subcritical CHP unit as an example to carry out the study. With the promotion of building energy efficiency, when the thermal index is reduced to below 20 W/m2, the low‐load operation of CHP can meet the wind power and PV feed‐in demand and guarantee residential heating without the need for flexibility modification. Meanwhile, more renewable energy generation can reduce carbon emissions from the power supply, further contributing to reducing carbon emissions from buildings. The impacts of different envelope parameters and supplementary heat sources on building carbon emissions are also studied. The conclusion shows that the degree of their impact on carbon emissions ranks as ESMs (energy supply modes) > Factor D (infiltration N50) > Factor A (external wall heat transfer coefficient) > Factor C (window heat transfer coefficient) > Factor B (roof heat transfer coefficient). When the building's heating energy consumption gradually decreases, the distributed heat pump unit can replace the coal‐fired boiler to supply the peak heat load demand. In the future, China's district heating systems can be gradually changed from the current CHP and coal‐fired boilers to CHP and distributed heat pumps. [ABSTRACT FROM AUTHOR]

A scientific evaluation of the carbon emission efficiency is crucial for ensuring the sustainable development of wastewater treatment plants (WWTPs). In this paper, we applied a non-radial data envelopment analysis (DEA) model to calculate the carbon emission efficiency of 225 WWTPs located in China. The results showed that the average carbon emission efficiency of China's WWTPs was 0.59, indicating that the efficiencies of most samples still require improvement. The carbon emission efficiency of WWTPs from 2015 to 2017 decreased because of the decrease in technology efficiency. Among the influencing factors, different treating scales had positive impact on carbon emission efficiency improvement. WWTPs with anaerobic oxic process and the first-class A standard were likely to have higher carbon emission efficiency in the 225 WWTPs. By incorporating direct and indirect carbon emissions into WWTP efficiency evaluation, this study helped decision-makers and related water authorities to better understand the contribution of WWTPs to the aquatic and atmospheric environments. [ABSTRACT FROM AUTHOR]

As the carrier of human economic activities, the change of territorial space affects the level of regional carbon balance. Therefore, with regional carbon balance as the goal, this paper proposed a framework from the perspective of production-living-ecological space and took Henan Province of China as a study area for empirical research. First, the study area established an accounting inventory that considers nature, society, and economic activities to calculate carbon sequestration/emission. Then, the spatiotemporal pattern of carbon balance was analyzed by ArcGIS from 1995 to 2015. Later, the CA-MCE-Markov model was used to simulate the production-living-ecological space pattern in 2035, and carbon balance in three future scenarios was predicted. The study showed that from 1995 to 2015, the living space gradually expanded, and the aggregation rose while the production space decreased. Carbon sequestration (CS) was less than carbon emission (CE) and presented an unbalanced state of negative income in 1995, while CS exceeded CE and showed a positive income imbalance in 2015. In 2035, living space has the highest carbon emission capacity under natural change scenario (NC), while ecological space has the highest carbon sequestration capacity under ecological protection scenario (EP), and production space has the highest carbon sequestration capacity under food security scenario (FS). The results are crucial for understanding the carbon balance changes in territorial space and supporting regional carbon balance goals in the future. [ABSTRACT FROM AUTHOR]

Animal husbandry is an important emission source of greenhouse gas. In order to discover the real situation of carbon emission in China's animal husbandry scientifically, the paper measured and calculated carbon emission in China's animal husbandry from 1997 to 2017 on the basis of soil and water resources. In addition, analyzing its time-order characters, structural characters, driving factors and decoupling relationships are all done in this treatise. Major findings are as follows: (1) The carbon emission of China's animal husbandry in 2017 was 374.3528 million tons, an increase of 17.8066 million tons over 1997, with the average annual growth rate of 0.24% and the average annual carbon emission of 398.7817 million tons; (2) There was a decreasing trend in carbon emission of intestinal fermentation in China's animal husbandry while there was an increasing trend in carbon emission of manure emission in China's animal husbandry; (3) The carbon emission of China's animal husbandry peaked in 2006 and went through three phases of up-down-steady between 1997 and 2017; (4) The contribution of cattle, pig, sheep, other large livestock, poultry and rabbits to China's animal husbandry carbon emissions decreased in turn, and the average contribution of cattle, pigs and sheep to China's animal husbandry carbon emissions was as high as 98.15%. (5) Five factors reducing carbon emission of China's animal husbandry were carbon intensity, agricultural industrial structure, agricultural population-water resources matching degree, agricultural water-soil resources and per capita cultivated land area. Two factors increasing carbon emission of China's animal husbandry were population and economic benefits of agriculture per unit agricultural population; (6) There was a generally weak decoupling between carbon emission in China's animal husbandry and animal husbandry's economic growth from 1997 to 2017. [ABSTRACT FROM AUTHOR]

Green credit is an important green financial policy tool to promote green development. However, research is needed to explore how green credit reduces carbon emissions, especially with respect to its dynamic spatial interactions and regional disparities. Based on a theoretical analysis, this paper empirically tests the carbon emission reduction effect of green credit and its three mechanisms by combining a Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model, dynamic spatial Durbin model (SDM), and the mediation model, including their dynamic spatial interactions and regional disparities. The study concludes that green credit can reduce carbon emission intensity based on strong spatio-temporal interactions in China. Green credit mainly reduces carbon emission intensity through scale and technology mechanisms with different spatio-temporal interactions. The tertiary industry in China does not currently have completely clean production; as such, the upgrading of the industrial structure as stimulated by green credit in the long term cannot yet effectively reduce carbon emissions. In addition, the carbon emission reduction effect of green credit and its three mechanisms have different levels of performance and dynamic spatial interactions in different regions of China. Finally, targeted policy recommendations are proposed to apply green credit to effectively reduce the carbon emission intensity. [ABSTRACT FROM AUTHOR]

To explore the sources of regional carbon emission differences and the evolution characteristics of spatial heterogeneity pattern, this paper first calculates the corresponding carbon emissions according to the relevant statistical data of eight economic regions in China from 2005 to 2019. It analyzes the overall differences and temporal and spatial evolution characteristics of regional carbon emissions combined with the visualization method of GIS. Then, the total carbon emission difference is decomposed by the Theil index to find out the primary sources affecting the regional carbon emission difference. Finally, the driving factors affecting the spatial heterogeneity pattern of regional carbon emissions are studied with the help of the Geodetector method. The results show that (1) significant differences in carbon emissions among China's eight economic regions. The contribution rate of inter-regional and intra-regional differences of carbon emissions in different regions to the overall carbon emission difference is diverse. (2) Regional carbon emissions are affected by single driving factors and the interaction of two driving factors. The interaction has an increasing impact on the determinant of regional carbon emission spatial differentiation. (3) The factor detection results and interaction detection results, respectively, show that the level of energy consumption, industrialization, and technological development has always been the main driving factors affecting the spatial heterogeneity pattern of regional carbon emissions, and the critical interaction factors have multiple spatial superposition interaction effects. Therefore, regional carbon emission reduction should consider the national strategic objectives and own regional characteristics and implement differentiated emission reduction schemes. [ABSTRACT FROM AUTHOR]

Climate change is a global problem facing mankind, and achieving peak CO2 emissions and carbon neutrality is an important task for China to respond to global climate change. The quantitative evaluation of the trends of urban energy consumption and carbon emissions is a premise for achieving this goal. Therefore, from the perspective of urban expansion, this paper analyzes the complex relationship between the mutual interactions and feedback between urban population, land expansion, economic growth, energy structure and carbon emissions. STELLA simulation software is used to establish a system dynamics model of urban-level carbon emissions effects, and Changsha city is used for the case study. The simulated outputs of energy consumption and carbon emissions cover the period from 1949 to 2016. From 1949 to 2016, Changsha's total energy consumption and carbon emissions per capita have continuously grown. The total carbon emissions increased from 0.66 Mt-CO2 to 60.95 Mt-CO2, while the per capita carbon emissions increased from 1.73 t-CO2/10,000 people to 18.3 Mt-CO2/10,000 people. The analysis of the structure of carbon emissions shows that the industrial sector accounted for the largest proportion of emissions, but it had gradually dropped from between 60% and 70% to about 40%. The carbon emissions of residential and commercial services accounted for less than 25%, and the proportion of transportation carbon emissions fluctuated greatly in 2013 and 2016. From the perspective of carbon emissions effects, carbon emissions per unit of GDP had a clear downward trend, from 186.11 t-CO2/CNY104 to 1.33 t-CO2/CNY104, and carbon emissions per unit of land showed two inflection points: one in 1961 and the other in 1996. The general trend showed an increase first, followed by a decrease, then a stabilization. There is a certain linear correlation between the compactness of urban shape and the overall trend of carbon emissions intensity, while the urban shape index has no linear correlation with the growth rate of carbon emissions. The carbon emissions assessment model constructed in this paper can be used by other municipalities, and the assessment results can provide guidance for future energy planning and decision making. [ABSTRACT FROM AUTHOR]

The construction industry is the backbone of most countries, but its carbon emissions are huge and growing rapidly, constraining the achievement of global carbon-peaking and carbon-neutrality goals. China's carbon emissions are the highest in the world, and the construction industry is the largest contributor. Due to significant differences between provinces in pressure, potential, and motivation to reduce emissions, the "one-size-fits-all" emission reduction policy has failed to achieve the desired results. This paper empirically investigates the spatial and temporal evolution of carbon emissions in China's construction industry and their decoupling relationship with economic growth relying on GIS tools and decoupling model in an attempt to provide a basis for the formulation of differentiated construction emission reduction policies and plans in China. The study shows that, firstly, the changes in carbon emissions and carbon intensity in the provincial construction industry are becoming increasingly complex, with a variety of types emerging, such as declining, "inverted U-shaped", growing, "U-shaped", and smooth fluctuating patterns. Secondly, the coefficient of variation is higher than 0.65 for a long time, indicating high spatial heterogeneity. However, spatial agglomeration and correlation are low, with only a few cluster-like agglomerations formed in the Pearl River Delta, Yangtze River Delta, Bohai Bay, Northeast China, and Loess and Yunnan–Guizhou Plateau regions. Thirdly, most provinces have not reached peak carbon emissions from the construction industry, with 25% having reached peak and being in the plateau stage, respectively. Fourthly, the decoupling relationship between carbon emissions from the construction industry and economic growth, as well as their changes, is increasingly diversified, and most provinces are in a strong and weak decoupling state. Moreover, a growing number of provinces that have achieved decoupling are moving backward to re-coupling, due to the impact of economic transformation and the outbreaks of COVID-19, with the degraded regions increasingly concentrated in the northeast and northwest. Fifthly, we classify China's 30 provinces into Leader, Intermediate, and Laggard policy zones and further propose differentiated response strategies. In conclusion, studying the trends and patterns of carbon-emission changes in the construction industry in different regions, revealing their spatial differentiation and correlation, and developing a classification management strategy for low carbonized development of the construction industry help significantly improve the reliability, efficiency, and self-adaptability of policy design and implementation. [ABSTRACT FROM AUTHOR]

This paper measures tourism carbon efficiency (TCE) in China by incorporating energy consumption and carbon dioxide (CO2) emissions into an efficiency assessment framework, and to further investigate the determinants of TCE by considering the spatial spillover effects. To do this, a bootstrap slacks-based measure (SBM) model was applied to assess the TCE in 30 provincial-level administrative regions of China from 2008 to 2019. Next, the Moran's index and spatial Durbin model (SDM) were adopted to explore the spatial distribution and determinants of TCE. The results indicate that regional differences affect the level of China's TCE, as do spatial spillover effects. In addition, technology innovation, urbanization rate, and government support positively affect TCE. In contrast, economic growth negatively affects TCE. Educational attainment, green infrastructure, and government support have a negative spatial spillover effect on TCE. Transportation infrastructure has a negative total effect on TCE. [ABSTRACT FROM AUTHOR]

Industrial land is currently the main carrier and important source of global carbon emissions, and as the world's largest developing country, China's large-scale and diversified industrial land supply has made it the world's largest carbon emitter. Therefore, researching the impact of different supply methods of industrial land on carbon emissions and its impact paths in China can help provide a reference for other countries to reduce carbon emissions from the perspective of urban industrial land management, which is of great significance for effectively promoting global carbon reduction. Based on this, this paper analyses the impact of different supply methods of industrial land on carbon emissions and its urban heterogeneity using the SYS-GMM and chain-mediated effects models for 285 cities in China from 2008 to 2020. The study found that, in general, the impact of different industrial land transfer modes on carbon emission has hysteresis and persistence. Agreement and listing transfer with government intervention can significantly exacerbate carbon emissions, while more market-based bidding and auction transfer can dampen carbon emissions. In terms of intermediary effects, the transfer of industrial land by agreement and listing will inhibit the rationalization and advancement of industrial structure, thus aggravating carbon emissions. The transfer of industrial land by bidding and auction will create barriers to entry and a crowding-out effect, promote the rationalization of industrial structure and the transformation and upgrading of industrial structure and moderate carbon emissions. In terms of city heterogeneity, there is urban heterogeneity in the impact of industrial land transfer on carbon emissions in cities with different economic types. Bidding and auction transfer for industrial land in both economically developed and less developed cities can promote carbon pollution. While the more developed urban economy makes the intermediary effect of industrial structure not significant. In the future, it is necessary to strictly control the scale of industrial land supply; the whole process supervision mechanism of industrial land allocation and differentiated industrial land supply strategies will provide useful experience for many developing countries in allocating industrial land to mitigate carbon emissions, generating effective contributions to global carbon emission reduction. [ABSTRACT FROM AUTHOR]

Unlike the decarbonization trajectories adopted by developed countries, some research suggests that non-pricing policies should be prioritized over pricing policies to mitigate carbon emissions in developing economies. This paper enriches the current literature on carbon pricing by empirically linking China's carbon pricing and non-pricing policies, using a difference-in-differences approach. The results indicate the effectiveness of the carbon pricing strategy. Furthermore, by introducing an interaction effect model, we find that a higher carbon price will significantly increase the carbon emission abatement effects. In conclusion, the findings highlight the necessity of carbon pricing instruments for decarbonization in developing countries. [ABSTRACT FROM AUTHOR]

With the increasing penetration of renewable sources, the cogeneration integrated energy system (CIES) is much more efficient and flexible to achieve various types of energy supply for remote loads. Due to uncertainties in both sources and loads, the CIES should be carefully planned and optimised to keep it working at the suitable operation condition. Therefore, this paper proposes a multi-objective capacity allocation optimisation method for the islanded CIES, which is composed of renewable energy generation unit, electric-thermal conversion unit, electric storage, thermal storage and various loads. Firstly, three optimisation objectives are selected as typical indexes, including economic cost, solar energy utilisation, and life cycle carbon emission. An improved radar chart evaluation (RCE) solution is subsequently utilised for calculating a fitness function and building the multi-objective optimisation model. Besides, several compulsory constraints are supplemented to ensure the overall CIES performance satisfy energy supply requirement. As a mature and widely accepted algorithm, a genetic algorithm is chosen as an example to obtain the optimal capacity allocation scheme. Case study of an islanded CIES is provided on the basis of real data from the remote region of northwestern China, which successfully verifies the effectiveness of the proposed optimal capacity allocation method. [ABSTRACT FROM AUTHOR]

In this paper, a reaction-diffusion dual carbon model associated with Dirichlet boundary condition is proposed under the influence of economic development in China. First, we enumerate and analyse some influencing factors of carbon emission and carbon absorption, and select economic development as the influence factor of carbon emission. Second, we establish a model associated with dual carbon and analyse the existence and stability of equilibrium and the existence of bifurcations. Finally, we analyse and predict for the value of parameters. Numerical simulations are presented to support our theory results. Combined with theoretical analysis and numerical simulations, we obtain that China can achieve carbon peak before 2030. If we want to achieve carbon neutral before 2060, it requires efforts from all of parts of society. Therefore, we put forward some practical suggestions to achieve carbon neutrality and carbon peak on schedule in China for the next few decades. [ABSTRACT FROM AUTHOR]