Search

Accounting for the embodied carbon in construction materials and calculating the carbon footprint of entire construction projects in life-cycle assessments is a rapidly developing area in the construction industry. Carbon emission accounting relies on inventories that claim to represent the values of carbon contained in materials. However, these values vary between different carbon inventories. This scoping review identifies academic research on the carbon inventories used in Australia, as well as the methods used to compare these inventories. The study was conducted in accordance with the JBI methodology for scoping reviews. We identified 182 papers and narrowed these down to 11 that complied with the objectives of this study. Data for a range of construction materials were compared in these papers, as were the methods used to calculate the values. While some carbon inventories were used frequently, no clear preference for the method of calculating carbon values was apparent. The system boundaries also varied between publications, and a range of functional units was used. There was agreement that the variables involved in calculating carbon values for building materials are compounded by the practical issues of extracting and manufacturing materials in different regional or local conditions, cultures, and technological situations. It is therefore understandable that different inventories store different values when so many factors need to be considered. There is thus a clear need for agreement to be reached about standardisation of the processes involved. If the trustworthiness of the data stored in carbon inventories is questionable, so too are the outcomes of subsequent activities. [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]

A major goal of the "14th Five-Year Plan" phase is to promote the green transformation of industrial enterprises to address the 'dual carbon' challenge. Utilizing the China Industrial Enterprises Database and the Polluting Enterprises Database, this paper calculates the carbon emissions of Chinese industrial enterprises from 2001 to 2010 at the micro level. It presents an analysis of the heterogeneity of carbon emission efficiency (TPI) in industrial enterprises, as well as the factors influencing corporate TPI. This study finds that enterprises within a subdivided industry exhibit heterogeneous levels of TPI, with carbon emissions largely affected by the structure of energy consumption. The researchers suggest accelerating the transition of industrial enterprises to green technology and argue that carbon emission policies should shift from controlling direct total targets to strengthening market-oriented policy tools. Carbon reduction targets should be more stringent for enterprises with lower TPI, considering the heterogeneity among enterprises. To meet the challenges of emission reduction, industrial enterprises are encouraged to actively reform their energy consumption structure. Government policies should aim to reduce clean energy costs and encourage the use of clean energy by industrial enterprises. [ABSTRACT FROM AUTHOR]

Public participation is playing an increasingly important role in environmental governance. This paper uses panel data from Chinese cities to evaluate the causal relationship between public participation, regional carbon emissions, and regional carbon intensity. We obtain the following conclusions: (1) Public participation significantly reduces regional carbon emissions and regional carbon intensity, which remains robust after a series of robustness and endogeneity discussions. (2) The carbon reduction effect of public participation performs better in eastern regions, regions with higher per capita income, and regions with a concentration of tertiary industries and talents. (3) We divided the public participation into resident participation and environment non-governmental organizations (ENGOs) participation. We found an excellent interactive emission reduction effect with resident participation and a good interaction between resident participation and government and environmental organizations. (4) This paper finds that promoting regional green technology innovation is a significant mechanism for public participation in achieving carbon emission reduction. (5) Finally, this paper found an "inverted U-shaped" non-linear relationship between public participation and regional carbon emissions. The results reveal the importance of public participation in regional carbon emissions and provide an empirical basis for promoting informal environmental regulation. [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]

Carbon emission intensity is an important index reflecting an entity's low-carbon competitiveness. This paper presents an extended logarithmic mean divisia index (LMDI) model to dissect carbon intensity within China's civil aviation from 1998 to 2019, revealing a significant reduction in CO2 emissions per air transport revenue. It attributes this decrease to technological advancements, optimized fleet structures, and improved operational efficiencies, highlighting the impact of larger, more efficient aircraft and enhanced load factors. The study also explores economic factors influencing carbon efficiency, suggesting a comprehensive approach encompassing technological innovation and strategic operational improvements for sustainable aviation development. [ABSTRACT FROM AUTHOR]

The rapid development of China's manufacturing industry has brought about environmental problems that have aroused people's attention to improving carbon emission efficiency and reducing carbon emissions. In this paper, 13 prefecture-level cities in Hunan Province from 2010 to 2020 were selected as research samples, and the coupling coordination degree model and super-efficiency slacks-based measure (SBM) model were used to calculate the level of integration of "two industries" (manufacturing and producer services, short for "TI") and the efficiency of carbon emissions. Then, hypotheses are established: The integration of TI can promote the improvement of carbon emission efficiency; The integration of TI promotes technological innovation; Technological innovation can promote carbon emission efficiency; Technological innovation is an intermediary in integrating TI affecting carbon emission efficiency. By using the fixed effect model and the mediation effect test method, we empirically analyze the influence of the integration of TI on carbon emission efficiency and the mediating role of technological innovation in this process. The conclusions are as follows: the integration of TI has a significant promoting effect on carbon emission efficiency; The integration of TI improves carbon emission efficiency by promoting technological innovation, and technological innovation bears part of the intermediary effect in the process of the impact of the integration of TI on carbon emission efficiency. The policy implications for improving carbon emission efficiency are proposed based on the research results. [ABSTRACT FROM AUTHOR]

In the context of achieving carbon peaking and carbon neutrality goals, focusing on coordinated efficiency in loss and carbon reduction, and promoting comprehensive green transformation of economic and social development are critical strategies. Line loss is an economic and technical indicator for measuring losses in a power system, and loss reduction is one of the important ways to achieve the carbon peaking and carbon neutrality goals in the power system. However, with the continuous increase in the power grid scale and the increasingly complex operation mode of the system, it is difficult to clearly quantify the carbon reduction benefits brought by system loss reduction. In order to synergize grid loss reduction and system carbon reduction, and generate economic and environmental benefits at the same time, this paper proposes a carbon market trading model that considers multi-layer reactive power compensation strategies. Based on the carbon emission flow model, a node carbon cost pricing is formed, and multi-layer reactive power compensation measures are set in the distribution network nodes to obtain an optimal loss reduction strategy, with the carbon market trading cost minimization as the objective. The effectiveness of the model is verified by simulating and analyzing four scenarios. Compared with the original system that does not consider carbon trading and reactive compensation, the model proposed in this paper can reduce losses by 20% and reduce carbon emissions by 5.7%. This paper is of great value for reactive power loss reduction management in distribution networks of a low-carbon background. [ABSTRACT FROM AUTHOR]

In response to the challenges of global warming and the development of A low-carbon economy, the integrated electricity and natural gas energy system (IEGES) is known as an important structure for future energy supply; thus, its planning and design must take low-carbon and environmental protection factors into account. Regarding carbon emissions as an optimization criterion, this paper built life-cycle carbon emission models of IEGES components. Then, taking the capacities of the energy resources, storage and conversion units of IEGES as the optimization variables, a multi-objective optimization configuration model was established considering the annual investment operation cost and the life-cycle carbon emissions. The multi-objective model was transformed into a single-objective one by an ε-constraint approach and the polynomial fitting method was employed to obtain the value of ε for obtaining uniformly distributed Pareto sets. Based on the fuzzy entropy weight method and the fuzzy affiliation degree approach, the obtained Pareto sets were ranked and the solution with the highest ranking value was selected as the optimal solution for the original problem. Finally, the configuration schemes were analyzed from the perspectives of economy, carbon emission and renewable energy utilization, and the effectiveness and rationality of the proposed optimization method were verified through MATLAB simulation. [ABSTRACT FROM AUTHOR]

In 2023, China's crude steel production amount reached 1.019 billion tons, and the energy consumption of China's steel industry amount reached 561 million tons of coal. China's steel industry, with its dominant reliance on coal for energy and the primary use of blast furnaces and converters in production processes, as well as its massive output, has become the main field for achieving China's "carbon peaking" and "carbon neutrality" goals. Firstly, this article summarizes the current production status of the steel industry and the situation of carbon emissions in the steel industry. Secondly, it discusses the dual-carbon policies based on the national and steel industry levels and outlines the future directions for China's steel industry. Subsequently, it analyzes the current state of research and application of mature and emerging low-carbon technology in China's steel industry and details the low-carbon plans of China's steel companies using the low-carbon technology roadmaps of two representative steel companies as examples. Finally, the article gives policy suggestions for the further carbon reduction of China's steel industry. The purpose of this paper is to show the efforts and contributions of China's steel industry to the early realization of its "carbon peaking" and "carbon neutrality" goals. [ABSTRACT FROM AUTHOR]

Carbon dioxide, the leading contributor to anthropogenic climate change, is released mainly via fossil fuel combustion, mostly for energy generation. Carbon capture technologies are employed for reducing the emissions from existing huge point sources, along with capturing them from direct air, to reduce the existing concentration. This paper provides a quantitative analysis of the various subtypes of carbon capture technologies with the aim of providing an assessment of each from technological, social, geo-political, economic, and environmental perspectives. Since the emissions intensity and quantity, along with the social–political–economic conditions, vary in different geographic regions, prioritising and finding the right type of technology is critical for achieving ambitious net-zero targets. Four main types of carbon capture technology were analysed (adsorption, absorption, membrane, and cryogenic) under four scenarios depending on the jurisdiction. The Technique for Order of Preference by Similarity to Ideal Solution (also known as the TOPSIS method) was used to establish a quantitative ranking of each, where weightages were allocated according to the emissions status and economics of each depending on the jurisdiction. Furthermore, forecasting the trends for technology types vis à vis carbon neutral targets between 2040 and 2050 was carried out by applying regression analysis on existing data and the emissions footprint of major contributing countries. The study found the membrane score to be the highest in the TOPSIS analysis in three of the four scenarios analysed. However, absorption remains the most popular for post-combustion capture despite having the highest energy penalty per ton of CO2 capture. Overall, capture rates are well short of projections for carbon neutrality; the methodology put forward for prioritising and aligning appropriate technologies and the region-by-region analysis will help highlight to technocrats, governments, and policymakers the state of the art and how to best utilise them to mitigate carbon emissions—critical in achieving the net-zero goals set at various international agreements on climate change. [ABSTRACT FROM AUTHOR]

With the global climate problem becoming increasingly severe, governments have adopted policies to encourage enterprises to invest in low-carbon technologies. However, the opacity of the carbon emission reduction process leads to incomplete consumer trust in low-carbon products as well as higher supply chain transaction costs. Based on this, this paper constructs Stackelberg game models with and without blockchain under different power structures and compares the impact of these models on low-carbon emission reduction decisions. The results show that: (1) blockchain does not necessarily improve enterprise profits and can only help enterprises maintain optimal profits within a certain range when the carbon emission cost is low; (2) when consumers' environmental awareness is high, the blockchain can incentivize manufacturers to enhance carbon emission reduction, and it has an obvious promotional effect on retailers' profits; and (3) the profit gap between enterprises in the supply chain is larger under different power structures, and the implementation of blockchain can coordinate profit distribution and narrow the gap between enterprises. Compared with the manufacturer-dominated model, the emission reduction in products is maximized under the retailer-dominated model. Our study provides theoretical support for the government to regulate greenhouse gas emissions as well as for the optimization of enterprises' decision-making supported by blockchain. [ABSTRACT FROM AUTHOR]

Climate anomalies are affecting the world. How to reduce carbon emissions has become an important issue for governments and academics. Although previous researchers have discussed the factors of carbon emission reduction from environmental regulation, economic development, and industrial structure, limited studies have explored the carbon emission reduction effect of a city's spatial structure. Based on 108 Chinese cities from the Yangtze River Economic Belt between 2003 and 2017, this paper examines the impact of the city cluster policy on city carbon emissions using the difference-in-differences (DID) method. We find that: (1) The city cluster policy has significantly reduced the cities' carbon emissions by 7.4%. Furthermore, after a series of robust and endogenous tests, such as parallel trend and PSM-DID, the core conclusion still remains. (2) We further identify possible economic channels through this effect, and find that city cluster policy would increase city productivity, city technological innovation, and industrial structure optimization. The conclusions of this paper have important practical significance for China to achieve carbon neutrality and facilitate future deep decarbonization. [ABSTRACT FROM AUTHOR]

The launch of the national carbon emissions trading (CET) market has resulted in a closer relationship between China's CET market and its electricity market, making it easy for risks to transfer between markets. This paper utilizes data from China's CET market and electric power companies between 2017 and 2023 to construct the spillover index model of Diebold and Yilmaz, the frequency-domain spillover approach developed by Barun'ik and Křehl'ik, and a minimum spanning tree model. The comparison is made before and after the launch of the national CET market. Subsequently, this paper examines the market spillover effects, as well as the static and dynamic properties of network structures, considering both the time domain and frequency-domain perspectives. The research findings suggest the following: (1) There is a strong risk spillover effect between China's CET market and the stock prices of electric power companies; (2) There is asymmetry in the paired spillover effects between carbon trading pilot markets and the national CET market, and differences exist in the impact of risk spillovers from power companies between the two; (3) The results of the MST model indicate that the risk contagion efficiency is higher in the regional CET pilot stage compared to the national CET market launch stage, with significant changes occurring in key nodes before and after the launch of the national CET market; (4) Both the dynamic spillover index and the standardized tree length results demonstrate that crisis events can worsen the risk contagion between markets. Besides offering a theoretical foundation and empirical evidence for the development of China's CET and electricity markets, the findings of this paper can provide recommendations for financial market participants as well. [ABSTRACT FROM AUTHOR]

China is one of the world's largest energy consumers and carbon emitters, and the situation of carbon emission reduction is serious. This paper forecasts the future trend of China's carbon emissions by constructing a system dynamics model of China's carbon emissions. The results show that China cannot fulfill its commitment to peak its carbon emissions in 2030 as scheduled. Secondly, the Logarithmic Mean Divisia Index model (LMDI) was used to analyze the influencing factors of China's carbon emissions. The contribution rates of the five factors to China's carbon emissions are as follows: economic development (226.30%), technological innovation (−105.92%), industrial structure (−26.55%), population scale (11.44%) and energy structure (−5.28%). Finally, this paper formulates five carbon emission reduction paths according to the size and direction of various factors that affect China's carbon emissions. The paths of carbon emission reduction were simulated by using the system dynamics model of China's carbon emissions. It is found that technological innovation is the key pathway for China to realize its commitment to carbon emission reduction. Slowing economic growth will delay the arrival time of peak carbon emissions and increase the intensity of carbon emissions. Optimizing the industrial structure, reducing the population scale and adjusting the energy structure can reduce the peak and carbon emissions in China, but the effect is small. [ABSTRACT FROM AUTHOR]

With the proposal of China's "carbon peak, carbon neutral" strategy, the increasing awareness of low carbon production among consumers, and the government's introduction of carbon trading mechanism and low carbon consumption subsidy policies, enterprises are facing good opportunities for development. However, how the government can reasonably formulate low carbon policies and how enterprises can implement optimal low-carbon production decisions are still key issues in China's low-carbon transition development. In this context, this paper is based on the carbon trading mechanism and carbon consumption subsidies. In this context, based on the carbon trading mechanism, this paper focuses on green production and green consumption, considers the impact of low-carbon consumer preferences and government subsidies on enterprises' low-carbon production decisions, and uses the optimal theory to study the optimal pricing strategy and the optimal carbon reduction strategy. The study shows that the increase in carbon price has a positive effect on the increase in enterprise profit; the increase of carbon emission has a negative effect on the increase of enterprise profit and the high carbon price will intensify this effect. In addition, changing the intensity of government subsidies to consumers will lead to the change of enterprise carbon emission strategy. The study of this paper provides a certain reference for the government to reasonably formulate carbon trading prices and consumer low-carbon subsidies. In addition, considering consumer low-carbon preferences is also conducive to promoting green production practices of enterprises, thus promoting the realization of the carbon neutral strategy. [ABSTRACT FROM AUTHOR]

This paper attempts to develop a calculation model to estimate the carbon dioxide (CO2) emissions during the mixing process of asphalt mixtures and explore energy-saving and emission reduction technologies. Based on a comprehensive analysis of the mixer's working mechanism, mixing quality requirement, and theoretical deductions, a CO2 emission model for the mixing process of asphalt mixtures is established. The model highlights the significant impact of mixing time on both mixing quality and carbon emissions. The model demonstrates that the mixing quality improves with an increase in mixing time, but the degree of improvement diminishes after an initial significant enhancement, eventually stabilizing. Importantly, excessive mixing time does not significantly improve the mixing quality; conversely, an extended mixing time has a notable impact on carbon emissions. Results show that when the deviation of the asphalt content is changed from 0.3% to 0.2% for a 5% asphalt content mixture, the mixing time and resulting CO2 emissions increase by 14%; similarly, when the deviation is 0.1%, the mixing time and resulting CO2 emissions increase by nearly 40%. Additionally, the agitator's capacity also significantly influences the CO2 emissions. For a project of a given scale, increasing the agitator capacity leads to a reduction in total carbon emissions during the mixing process. Compared to a type 1500 agitator, employing agitators of types 3000, 4000, and 5000 can achieve reductions in total CO2 emissions by 26.3%, 32.9%, and 36.8%, respectively. Therefore, for large-scale engineering projects aiming to minimize CO2 emissions during the mixing process, it is essential to determine the optimal mixing time to avoid excessive mixing and select a larger capacity agitator, preferably type 4000 or higher. These findings could support the development of effective emission reduction measures in the field of road construction, thereby contributing to the achievement of emission reduction targets and promoting the advancement of sustainable road development. [ABSTRACT FROM AUTHOR]

Urban agglomerations are regions where the economy and population are highly concentrated, which are also spatial units with more concentrated carbon emissions. A detailed decomposition of driving factors based on changes in carbon emissions of urban agglomerations can provide a reference for better carbon reduction policies. In this paper, we establish an evaluation framework of carbon emission drivers of urban agglomeration from the perspective of CO2 generation and removal using a system dynamics method. The key influencing factors and optimal emission reduction measures of carbon emissions in urban agglomerations are explored. The results are as follows: (1) The industrial structure is the key influencing factor of carbon emissions; (2) compared with no implementation of any policies, the total carbon emissions and carbon emission intensity of integrated policies all significantly decrease, with a decrease of 43.68% and 53.32%, respectively in 2035; (3) energy structure adjustment has a significant effect in reducing carbon emissions and carbon emission intensity; (4) the role of increasing investment in technological innovation in ensuring achievement of "carbon peak" should not be ignored. It is found that integrated policies often exhibit a better emission reduction effect, but this effect is not a simple summation of the effects of each single policy. [ABSTRACT FROM AUTHOR]

This paper considers a fresh food supply chain with a supplier who takes responsibility for the cold chain and a retailer who needs to reprocess the fresh food. Carbon emissions will be produced in the processes of production, transportation, processing, etc. We consider the four-stage game, obtain the function expressions of optimal market prices with respect to carbon emission reduction level (CERL), analyze the best responses of the supplier and the retailer regarding their CERLs, and obtain the 25 optimal CERLs under competitive equilibrium. In 24 of the 25 equilibrium cases, the supplier or the retailer either do nothing to reduce carbon emissions, or make the most effort to reduce carbon emissions. Excluding these special cases, we focused on a non-trivial case where the increasing consumer preferences for low-carbon products will encourage the supplier and the retailer to reduce carbon emissions. Interestingly, we find that when the consumer preference for low-carbon products is low, the retailer's and supplier's equilibrium carbon reduction levels are low, so that the potential market size is small such that the competition for two kinds of customers is fierce. Then, an increase in the sale cost will reduce the retail price. However, when the consumer preference for low-carbon products is high, the potential market size is large such that the competition is not fierce. Then, an increase in the sale cost will advance the retail price. [ABSTRACT FROM AUTHOR]

Due to the need for comprehensive transportation hub construction, an existing bridge in a bustling urban area with an operation duration of 25 years was required to be demolished. Based on Life Cycle Assessment (LCA), this paper proposes a scheme of "Self-propelled modular transporter (SPMT) technology + large segment cutting" to compare the carbon emissions of demolition schemes qualitatively and quantitatively. To ensure structural safety during demolition, the finite element analysis was used to simulate the entire demolishing process, and measuring points were set up to monitor the deformation of the main girder in real time under various demolition conditions. The results indicate that the scheme of SPMT has the lowest carbon emissions during the demolition stage. Additionally, the long-term prestress loss shall be considered when demolishing existing bridges; the suggested 25% proportional value for the long-term prestress loss of the Caitian Bridge is appropriate, which is determined by comparing the calculated results from various formulas. The values of the calculated and measured deformations of the main girder under different working conditions are in good agreement, with errors mostly within 10% and a maximum of no more than 14.7%. The demolition of the entire bridge was completed in a total of 28 h with little noise and pollution, and the impact on daily traffic was avoided, proving that the proposed "SPMT technology + large segment cutting" scheme is safe, efficient, and achieves the goal of green, environmentally friendly, and rapid demolition. [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]

The development mode of expanding agricultural scale will inevitably lead to an increase in agricultural carbon emissions but the impacts of agricultural technology progress on agricultural carbon emission and carbon sink are still not quite clear. This paper firstly discuss the definition of agricultural technology level. Then the estimating methods of agricultural technology, agricultural carbon emission and carbon sink are introduced. Based on the China's provincial panel data with 31 province from 2000 to 2019, the indicators are calculated and statistically analysed. After that, the representativeness of the three secondary classifications of the agricultural technology is empirically checked. Panel data regression models especially the fixed effect model is employed to estimate the effects of agricultural technology level as well as its components on agricultural carbon emission and carbon sink. Results show that the agricultural carbon sink is approximately 10 times higher than agricultural carbon emission. Agricultural technology level in general has significant effect on the carbon emission rather than the carbon sink. Our suggestion is that (1) it is not necessary to worry about the agricultural carbon emission since the net effect of agriculture is carbon neutrality; (2) the development of agricultural production technology and agricultural management technology needs strong support, and the two need to develop coordinated. [ABSTRACT FROM AUTHOR]

The research project discussed in this paper is driven by the United Kingdom's (UK's) need to reduce operational energy and carbon by promoting the adoption of the Active Building (AB) concept for UK building projects. The AB concept offers a practical solution to reducing the operational energy use and carbon emissions of buildings by using emerging technologies applied to architectural design; thus, helping the UK meet its decarbonisation targets and, consequently, helping to combat the global problem of climate change. The aim of the project was to design and implement an AB Protocol with an AB Toolkit, to provide a knowledge base and sustainable architectural design guidance to aid the design of ABs. The AB Toolkit was tested, evaluated, and refined by engaging with architectural designers in the UK through focus groups (FGs) that combined data collection with knowledge dissemination—a method which provided a contribution to the continuous professional development (CPD) of architectural designers in the UK, while aiding the research project. The FG data proved the original hypothesis that a whole host of measures are needed to support the adoption of the AB concept (as outlined in the AB Protocol), but that some design guidance was needed initially to enable the development of other supporting measures. Therefore, the main output of this research project was the development of a structured approach to enable architectural designers and other built-environment professionals to adopt the AB concept for the delivery of net zero operational energy buildings, supporting the aims of the SPECIFIC Innovation and Knowledge Centre, Swansea University, and the Active Building Centre (ABC). The method of data collection developed, and the structured approach to enabling the adoption of a new concept outlined, could be beneficial to other researchers. [ABSTRACT FROM AUTHOR]

The construction industry is a high-energy-consumption industry. Nearly 40% of global carbon emissions derive from the construction industry. Prefabricated assembly technology is an effective means of carbon emission reduction, but the incremental cost of prefabricated components is much more expensive than that of cast-in-place components. It is not conducive for enterprises to choose prefabricated assembly technology to decrease emissions. Most of the current studies focus on the carbon-reduction effect of prefabricated assembled buildings, and there are fewer studies related to the impact of cost factors on enterprises' participation in building carbon reduction. The cost factor will affect the choice of prefabricated assembly technology to reduce carbon emissions. Therefore, it is necessary to analyze the relationship between carbon emissions and costs in prefabricated buildings. Aiming at this problem, this paper proposes a dual-objective method to optimize cost and carbon emissions by using the improved optimization algorithm to solve the problem. Through the analysis of actual cases, the results show that when the prefabrication rate is 35–40%, enterprises can obtain a better carbon-emission-reduction effect by appropriately increasing the cost. When the prefabrication rate is higher than 40%, the carbon-reduction effect that can be obtained by greatly increasing the cost is limited. Therefore, when enterprises decide a prefabrication range of 35–40%, they are able to obtain the maximum carbon-reduction effect with the minimum cost. This study can provide a reference for the government to formulate relevant policies with energy conservation and emission reductions in prefabricated buildings and also can provide a reference for enterprises to make decisions between carbon emission reduction and cost. [ABSTRACT FROM AUTHOR]

China's economic development is characterized by openness, and trade and investment are important engines for promoting economic development. China's economy is now in a transitional period, during which excessive carbon emission reduction would inevitably hinder economic development. In this context, improving carbon emission efficiency is an effective way to achieve sustainable development. This paper deals with the relationships among foreign direct investment, technological innovation and carbon emission efficiency. Our research findings include the following. First, carbon efficiency shows regional differences. East China has the highest mean value of carbon emission efficiency, followed by central China and west China over the sample period. Second, FDI exerts both direct and indirect impacts on carbon emission efficiency through technological innovation, which confirms the intermediate effect of technological innovation. Finally, sub-sample analysis indicates that the impact of FDI and technological innovation on carbon emission efficiency show regional heterogeneity. According to these findings, we offer policy recommendations as follows. The government should stimulate independent innovation, promote technological progress in renewable energy and green energy, and attract environmentally friendly foreign investment to improve carbon emission efficiency and boost green development. [ABSTRACT FROM AUTHOR]

To improve the distributed carbon emission optimization control capability of the smart distribution network system, thereby reducing the carbon emissions in the distribution process, it is a very important issue to comprehensively analyze the importance of the node carbon emission flow of the smart distribution network. This paper transforms the power grid into a carbon emission flow network through power flow calculations: Based on the complex network theory, it determines the coupling scale of the two networks by means of the correlation coefficient method and the correlation matrix method, and establishes a coupling network model based on the carbon emission flow network; Combining the different business characteristics of carbon emission flow and information flow, an evaluation index system considering the dual-network coupling scale is established, and a multi-indicator comprehensive evaluation method that combines the Topsis and grey relational analysis method, that can objectively evaluate indicators that contain subjective components was proposed; The obtained node importance values can be used to determine the relative key line, greater sum node importance values represent a greater carbon emission impact of the line, providing a sequential basis for the carbon reduction and restructuring of the distribution network; Taking the 3-machine 9-node system as an example, the carbon flow distribution in the corresponding network is calculated, and the comprehensive importance value of the coupling node is calculated to analyze the rationality of this method. [ABSTRACT FROM AUTHOR]

The construction sector is responsible for the 40% of consumed resources, 40% of CO2 emissions, and approximately 40% of construction and demolition waste. For the assessment of the building, there exists a standardized method, life cycle assessment (LCA), however, the process requires time, cost, and most importantly expertise. In this paper, a method is proposed and analyzed for the life cycle assessment of the building for the embodied carbon in the three stages, construction, operation, and demolition. Moreover, the result of the analysis is considered as the base result, and de-carbonization strategies identified through literature study for the three stages of construction, operation, and demolition are assessed with the same method to know how much each strategy will be effective in minimizing the embodied carbon. For the base case, a high-rise residential building in an urban region of India is analyzed, based on existing conditions through the building information modeling (BIM) method. The carbon emission of the selected building comes out to be 414 kg CO2e/m2/year, and assessing different decarbonization strategies, considering the first analysis as the baseline, it can be minimized to 135 kg CO2e/m2/year. [ABSTRACT FROM AUTHOR]

The sustainability of the construction industry is a priority in innovations made towards mitigating its notoriously high carbon emissions. Developments in low-carbon concrete technology are of peak interest today under the scrutiny of emerging policy pressures. Concrete is the external part of most structures vulnerable to permanent degradation and weathering, the possibility of an intrinsic restoration of its engineering properties promises unprecedented advancements towards structural resilience. Existing research in self-healing concrete (SHC) has often concerned the scope of material development and evaluation with inconclusive field testing, hindering its progress towards structural feasibility. This paper presents an overview of recent progress in SHC, and possible opportunities and challenges of popular healing systems are discussed. Moreover, trends are observed to investigate SHC's influence on the engineering properties of concrete, and future projections of SHC are suggested with identification of potential research needs. [ABSTRACT FROM AUTHOR]

The decarbonization of the power system forces the rapid development of electric energy storage (EES). Electricity consumption is the fundamental driving force of carbon emissions in the power system. However, the current EES capacity planning research that considers the load-side carbon emission responsibility is still limited. To fill this research gap, this paper proposes a carbon incentive mechanism while considering load-side carbon emission responsibility. Additionally, a bi-level optimal capacity planning model of the load-side EES based on carbon emission flow (CEF) theory is proposed. The upper level obtained the bus carbon intensities through the optimal economic dispatch and passed them to the lower level. Considering the carbon incentive mechanism, the lower level optimized the EES capacity. Finally, the model was tested by MATLAB/Gurobi in the modified IEEE-39 bus power system. The results show that under the stimulation of the carbon incentive mechanism, the bi-level optimal capacity planning model of the load-side EES could effectively promote peak shaving, valley filling, and carbon reduction. Furthermore, compared with the two existing EES subsidy policies, the proposed carbon incentive mechanism is verified to be more conducive to reducing system carbon emissions. [ABSTRACT FROM AUTHOR]

As an important energy base in China, Shanxi Province, in its economic development, has depended heavily on coal resources. However, enormous coal consumption produces a large amount of carbon dioxide and an aggravated ecological problem. In this paper, the super efficiency slack-based measure and data envelopment analysis (SBM-DEA) model and Malmquist index were used to calculate the energy consumption and carbon emission efficiency of 11 prefecture-level cities in Shanxi in the period from 2000 to 2020. The results were as follows: (1) The primary form of energy consumption in Shanxi Province is the burning of coal, and the carbon emission efficiencies of the 11 prefecture-level cities are quite different. The technical efficiency, technological progress, and total factor productivity of Taiyuan and Shuozhou were found to be greater than 1 compared to other cities in Shanxi. (2) On the whole, although the carbon emission rate of Shanxi Province has slowed down, it still faces the problems of a large total emission base, high carbon emission intensity, and low efficiency of the unit carbon emission output. Industrial structure is the key factor restricting improvements in the efficiency of carbon emissions in Shanxi Province. (3) From the spatial and temporal evolution of the carbon emission efficiency in Shanxi Province, we can see that the carbon emission efficiency of the whole province gradually dispersed and improved from the central and northern regions to the southern regions during the period of 2000–2020. In order to achieve a low-carbon economy, Shanxi Province must optimize its industrial structure, accelerate research and development in low-carbon technologies, adjust the energy structure, and promote the construction of an energy supply system with clean low-carbon energy as the main source. [ABSTRACT FROM AUTHOR]

Due to increased global carbon dioxide emissions, the greenhouse effect is being aggravated, which has attracted wide attention. China is committed to promoting the low-carbon development of all industries. This paper analyzed the influencing factors of carbon emissions in the Chinese logistics industry, so as to identify the key factors that influence carbon emissions. Based on the carbon emission data of China's logistics industry in 2000–2019, this paper applied the carbon emission coefficients issued by the Intergovernmental Panel on Climate Change. For the first time, the Generalized Divisia Index Method was used to analyze the degree of influence of the factors on carbon emissions. This method considered more variables and their relationships. The results showed that (1) the carbon emissions of the logistics industry were increased by 3.22 times from 2000 to 2018, and showed negative growth for the first time in 2019; (2) the added value of the logistics industry is the most important factor in increasing carbon emissions (with a contribution ratio of 65.45%), energy consumption and practical population size are the main factors in carbon emissions. The promotion of this industry is subjected to decreased per capita carbon emissions, which have a large impact on total carbon emissions; (3) the intensity of carbon output is the most important factor in the reduction of carbon emissions (with a contribution ratio of −29.1%), where the energy carbon intensity and per capita added value are the main influencing factors with regard to the reduction of carbon emissions, while energy intensity has a negative inhibitory effect on carbon emissions, and (4) the influencing factors have negative effects on the cumulative inhibition of carbon emissions in the logistics industry, to an extent that is far less than the integral promotion of carbon emissions. Finally, according to the research conclusions of this paper, it is feasible to make recommendations for the carbon reduction of the logistics industry. [ABSTRACT FROM AUTHOR]

A growing number of countries worldwide have committed to achieving net zero emissions targets by around mid-century since the Paris Agreement. As the world's greatest carbon emitter and the largest developing economy, China has also set clear targets for carbon peaking by 2030 and carbon neutrality by 2060. Carbon-reduction AI applications promote the green economy. However, there is no comprehensive explanation of how AI affects carbon emissions. Based on panel data for 270 Chinese cities from 2011 to 2017, this study uses the Bartik method to quantify data on manufacturing firms and robots in China and demonstrates the effect of AI on carbon emissions. The results of the study indicate that (1) artificial intelligence has a significant inhibitory effect on carbon emission intensity; (2) the carbon emission reduction effect of AI is more significant in super- and megacities, large cities, and cities with better infrastructure and advanced technology, whereas it is not significant in small and medium cities, and cities with poor infrastructure and low technology level; (3) artificial intelligence reduces carbon emissions through optimizing industrial structure, enhancing information infrastructure, and improving green technology innovation. In order to achieve carbon peaking and carbon neutrality as quickly as possible during economic development, China should make greater efforts to apply AI in production and life, infrastructure construction, energy conservation, and emission reduction, particularly in developed cities. [ABSTRACT FROM AUTHOR]

Urban areas contribute to over 80% of carbon dioxide emissions, and considerable efforts are being undertaken to characterize spatiotemporal variations of CO2 (carbon dioxide) at a city, regional, and national level, aiming at providing pipelines for carbon mission reduction. The complex underlying surface composition of urban areas makes process-based and physiology-based models inadequate for simulating carbon flux in this context. In this study, long short-term memory (LSTM), support vector machine (SVM), random forest (RF), and artificial neural network (ANN) were employed to develop and investigate their viability in estimating carbon flux at the ecosystem level. All the data used in our study were derived from the long-term chronosequence observations collected from the flux towers within urban complex underlying surface, along with meteorological reanalysis datasets. To assess the generalization ability of these models, the following statistical metrics were utilized: coefficient of determination (R2), root mean square error (RMSE), and mean absolute error (MAE). Our analysis revealed that the RF model performed the best in simulating carbon flux over long time series, with the highest R2 values reaching up to 0.852, and exhibiting the smallest RMSE and MAE values at 0.293 μmol·m−2·s−1 and 0.157 μmol·m−2·s−1. As a result, the RF model was chosen for simulating carbon flux at spatial scale and assessing the impact of urban impervious surfaces in the simulation. The results showed that the RF model performs well in simulating carbon flux at the spatial scale. The input of impervious surface area index can improve the performance of the RF model in simulating carbon flux, with R2 values of 84.46% (with the impervious surface area index in) and 83.74% (without the impervious surface area index in). Furthermore, the carbon flux in Fengxian District, Shanghai, exhibited significant spatial heterogeneity: the CO2 flux in the western part of Fengxian District was less than in the eastern part, and the CO2 flux gradually increased from the west to the east. In addition, we creatively introduced the diurnal impervious surface area index based on the Kljun model, and clarified the influence of impervious surface on the spatiotemporal simulation of CO2 flux over the complex urban underlying surface. Based on these findings, we conclude that the RF models can be effectively applied for estimating carbon flux on the complex underlying urban surface. The results of our study reduce the uncertainty in modeling carbon cycling in terrestrial ecosystems, and make the variety of models for the carbon cycling of terrestrial ecosystems more diverse. [ABSTRACT FROM AUTHOR]

To cope with huge carbon emission pressure, China has implemented a carbon emissions trading pilot policy that aims to provide reasonable suggestions for the smooth operation of the national carbon market. This paper selects the provincial panel data in China from 2005 to 2019 and uses the propensity score matching-difference in difference (PSM-DID) method to evaluate the carbon emission policy's reduction effect. Based on carbon emissions (CE) and carbon emission intensity (CI), provinces and cities are divided into four regions, and each region is verified by spatial difference analysis. Furthermore, the mediating effects of carbon emission reduction through the dual aspects of technological progress and industry structure are also discussed. Results verified that, (1) under the carbon emission trading policy, regional carbon emissions and carbon emission intensity are both significantly reduced. (2) Technological progress helps to reduce carbon emissions, while industrial structure shows no obvious contribution. (3) The four regions all show ideal emission reduction effects, of which the High CE-High CI region shows the best, but is greatly restricted by techniques. The industrial structure of the High CE-Low CI region needs to be further optimized for carbon reduction. In the Low CE-High CI region, the carbon emissions brought by economic development fail to effectively improve per capita GDP. The Low CE-Low CI region contributes greatly to carbon emission reduction with technical advantages. [ABSTRACT FROM AUTHOR]

China's digital economy has been expanding rapidly in the past decade. This expansion is having a profound impact on the country's economy. Using panel data on 97 prefecture-level cities in the Yellow River Basin from 2011 to 2020, this study investigates the multifaceted relationship between the digital economy and total-factor carbon emission efficiency. The research yields three key findings: (1) The digital economy positively enhances overall carbon emission efficiency. This conclusion is drawn with robustness tests. (2) Green technology innovation serves as a partial mediator between the digital economy and total-factor carbon emission efficiency, and this mediation role is influenced by government intervention, which negatively moderates the relationship between the digital economy and green technology innovation but positively impacts the mediation role of green technology innovation between the digital economy and total-factor carbon emission efficiency. (3) The positive impact of the digital economy on total-factor carbon emission efficiency is more significant in the upper reaches, lower reaches, and resource-based cities of the Yellow River Basin. These findings provide new perspectives and empirical evidence for better understanding the relationship between digital economy development and total-factor carbon emission efficiency. They also provide policy recommendations for achieving strategic objectives, including digital economy development, carbon emission reduction, carbon peaking, and carbon neutrality. [ABSTRACT FROM AUTHOR]

China's industrial sector generally relies on electricity as its main source of energy, and industrial production can be affected if there are problems with the electricity supply. In order to deal with the uncertain electricity supply and achieve the "dual carbon" target, the industrial sector needs to take effective measures to enhance carbon total factor productivity (CTFP). We use the biennial Luenberger productivity index (BLPI) to try to provide strategies for low-carbon industrial development in China. The results indicate that the overall CTFP of China's industrial sector showed an increasing trend from 2006 to 2019. Technology change was the main contributor to the change in CTFP, but fluctuations in efficiency change remained a challenge. Differences were observed between the light industry sector (LIS) and the heavy industry sector (HIS) in terms of changes in CTFP, with LIS showing more stable changes and HIS experiencing larger fluctuations. Most sub-sectors showed increased CTFP during the sample period. R&D investment and R&D personnel have a positive impact on CTFP, while energy structure is found to hinder CTFP. According to the research results of this study, we offer the corresponding policy implications. This study is the first to explore the balance between low-carbon goals and industrial production from the perspective of improving CTFP, providing a new viewpoint on the contributions of technological innovation to solving socio-economic issues. [ABSTRACT FROM AUTHOR]

The greening trend in consumer markets and the marketization and financialization of carbon emission rights have begun to revitalize carbon assets. However, solitary efforts and the spillover of environmental protection effects still hamper enterprises' enthusiasm for carbon emission reduction. To tackle this challenge, two vertical cooperation mechanisms, cost cooperation and alliance cooperation, are proposed. The mathematical models and solutions are developed for both of the two mechanisms, and their values and applicability are explored, respectively. In addition, the impact of fluctuations in consumer markets, financial markets, and carbon markets on cooperation is examined. The results show that both cooperation models effectively motivate enterprises to enhance carbon reduction and boost market demand. However, cost cooperation may result in inflated product prices and even weaken the profitability of the supply chain. In contrast, alliance cooperation can enhance product price performance and effectively increase supply chain profits. Concerning environmental performance, the initial market is better suited for alliance cooperation, whereas cost cooperation fits the mid-to-late market. The higher financing costs of the financial market and the trading price of the carbon market will strengthen the applicability of cost cooperation. This study offers managerial insights for collaborative decision-making in the context of a multi-market cross-section. [ABSTRACT FROM AUTHOR]

China has clearly put forward the strategic goals of reaching the "Carbon Emission Peak" by 2030, and achieving "Carbon Neutrality" by 2060. To achieve these goals, it is necessary to precisely understand the spatial distribution characteristics of historical carbon emissions in different regions. This paper has selected a representative national-level urban agglomeration in China, the Harbin–Changchun urban agglomeration, to study the temporal and spatial distribution characteristics of carbon emissions in its counties. This paper has constructed global and local Moran's I indexes for the 103 counties in this urban agglomeration by using the carbon emission values reflected by night light data from 1997 to 2017 to perform global and local autocorrelation analysis on a spatial level. The results show that: (1) the main characteristic of carbon emission clustering in the Harbin–Changchun urban agglomeration is similar clustering; (2) the changes in carbon emissions of the Harbin–Changchun urban agglomeration have a strong correlation with relevant policies. For example, due to the impact of the "Twelfth Five-Year Plan" policies, in 2013, the global county-level Moran's I index of the carbon emissions in the Harbin–Changchun urban agglomeration decreased by 0.0598; (3) the areas where high carbon emission values cluster together ("High–High Cluster") and low carbon emission values cluster together ("Low–Low Cluster") in the Harbin–Changchun urban agglomeration are highly concentrated, and the clusters are closely related to the development level of different regions. [ABSTRACT FROM AUTHOR]

A low-carbon economic optimization dispatch model of integrated energy system is proposed to improve the low-carbon and economic efficiency of the integrated energy systems. Firstly, the waste heat generator with the organic Rankine cycle is introduced into the combined heat and power to decouple the combined heat and power operation, and a coupled model with an organic Rankine cycle, power to gas, combined heat and power and carbon capture system is established. Then, the ladder-type carbon trading mechanism is introduced to improve the low-carbon model. Finally, the function is established to minimize the sum of energy purchase costs, operation and maintenance costs, and environmental costs. The proposed integrated energy systems' low-carbon economic dispatch model reduces the total operating cost by 18.9% and the carbon emissions by 83.7% by setting up different models for comparative analysis. [ABSTRACT FROM AUTHOR]

In the present climate, due to the cost of investments, pollutants of fossil fuel, and global warming, it seems rational to accept numerous potential benefits of optimal generation expansion planning. Generation expansion planning by regarding these goals and providing the best plan for the future of the power plants reinforces the idea that plants are capable of generating electricity in environmentally friendly circumstances, particularly by reducing greenhouse gas production. This paper has applied a teaching–learning-based optimization algorithm to provide an optimal strategy for power plants and the proposed algorithm has been compared with other optimization methods. Then the game theory approach is implemented to make a competitive situation among power plants. A combined algorithm has been developed to reach the Nash equilibrium point. Moreover, the government role has been considered in order to reduce carbon emission and achieve the green earth policies. Three scenarios have been regarded to evaluate the efficiency of the proposed method. Finally, sensitivity analysis has been applied, and then the simulation results have been discussed. [ABSTRACT FROM AUTHOR]

Under the trend of digitization and global carbon reductions, clay construction has increasingly attracted attention due to advantages such as an excellent thermal performance, low carbon emissions, and high cost-effectiveness. In this article, an in-depth investigation is conducted into the potential, challenges, and future in the development of digital manufacturing technologies for clay architecture, especially 3D printing, robotic construction, and prefabrication systems. It is revealed through a review that digital clay construction is under rapid development and likely to provide a viable solution to achieving global carbon neutrality, which is conducive to addressing various regional issues. The key findings from this review are as follows. Firstly, as a flexible, precise, and low-carbon industrial solution, 3D printing lays a foundation for the extensive research on materials, equipment, and algorithm optimization. Secondly, the use of machine construction methods such as modern rammed earth technology and drone spraying is effective in improving efficiency and lowering costs. Lastly, the prefabricated building system shows its potential in renewing and developing the rammed earth architecture culture. These findings indicate a massive potential of digital clay construction to support sustainability efforts in the future. [ABSTRACT FROM AUTHOR]

Disruption risks exacerbate the complexity of low-carbon supply chain network design in an uncertain supply chain environment. Considering the low frequency and non-repeatability of these disruption events makes it impossible to collect data to obtain their probabilities. In this study, supply disruptions were regarded as uncertain events; supply chain uncertain disruption risk is defined and quantified based on the uncertainty theory, in which uncertain disruptions are characterized by the belief degree on account of expert estimation with duality, i.e., symmetry. Optimization models were constructed with the objective of minimizing expected carbon emissions and costs, which optimizes the selection of suppliers with uncertain disruptions, and the assignment of manufacturers and customers. The properties of the model were analyzed, and the models were solved separately using different methods according to different decision criteria. Finally, the validity of the proposed models and algorithm were verified using a real case study of a glass manufacturing company. The findings exhibit promising insights for designing a sustainable and resilient supply chain network in an uncertain environment. [ABSTRACT FROM AUTHOR]

In the pursuit of China's environmental targets to achieve a carbon peak by 2030 and carbon neutrality by 2060, the carbon emission trading scheme (CETs) has emerged as a critical policy instrument. Since the 14th Five-Year Plan, China has been on a two-wheel drive to prevent pollution and combat climate change and proposes to fight the Blue Sky Defense. Therefore, this study focuses on prefecture-level cities in China and employs a spatial difference-difference (SDID) model to investigate the spatial spillover effects of CETs on urban total factor carbon emission efficiency (TFCEE). Furthermore, a mediating effect model is constructed to explore the channels through which CETs influence carbon emission efficiency. The results show that (1) implementing urban CETs can significantly improve urban itself and the surrounding carbon emission efficiency. (2) The CETs can indirectly promote the improvement of carbon efficiency by optimizing the allocation of labor resources and strengthening the level of green technology innovation. (3) Compared with the cities in central and western China, implementing the CETs has a stronger promotion effect on the carbon emission efficiency of the cities in eastern China. [ABSTRACT FROM AUTHOR]

Numerous studies have examined the relationship between technological development and pollution. From a global economic perspective, the narrowing of one country's technological gap relative to the world technology frontier (due to the technological progress) may affect its environmental pollution. However, few studies have focused on this issue. This study examined the relationship between technology gap and air pollution both theoretically and empirically. The theoretical model shows that narrowing the technology gap may help reduce pollution. Using patent data from USPTO, as well as industrial level pollution and socio-economic data in China, this paper found that the narrowing of technology gap plays a role in reducing air pollution emissions in China, which confirms the theoretical model. This study provides a new perspective on the relationship between technology progress and pollution. [ABSTRACT FROM AUTHOR]

The carbon reduction effect of technological innovation in the transportation industry is conducive to China's anticipated realization of carbon neutrality. Therefore, we evaluated carbon emission reduction effect of technological innovation in the transportation industry in China. Based on the panel data of 30 sample provinces in China (excluding Hong Kong, Macao, Taiwan and Tibet) from 2012 to 2018, using the Moran'I index and Getis-Ord Gi index, this paper analyzes the evolutionary trend and spatial autocorrelation of carbon emission in the transportation industry, and analyzes the impact of technological innovation on carbon emission levels of the transportation industry and its spatiotemporal differences by using the geographical and temporal weighted regression (GTWR) model by using ArcGIS 10.4 software. The conclusions are as follows: The carbon emission level of China's transportation industry generally has been rising steadily, showing a spatial distribution pattern of high emissions in the east and low emissions in the west. The cold spots are concentrated in the western region, and the hot spots are situated in the central and eastern regions. Technological innovation has a carbon reduction effect on the transportation industry in the eastern and north-eastern regions, while the effect in other regions is not obvious. However, there is an obvious "inverted U-shaped" relationship between technological innovation and the transportation industry's carbon emissions. The technological innovation in the transportation industry will have a significant carbon reduction effect after breaking through the technical pain points. This carbon reduction effect has a higher effect on the western region than on the eastern region. In addition, the economic development level, the fiscal expenditure proportion of the transportation industry, the higher education level, and the proportion of fixed asset investment in the transportation industry have played a positive role in reducing carbon in the transportation industry, but the spatial heterogeneity of this carbon reduction effect is relatively strong. Therefore, during the "14th Five-Year Plan" development period in China, it is necessary to continuously promote the low-carbon development of the transportation industry with technological innovation, while highlighting the differentiated carbon reduction governance, and consolidating the role of talents and fiscal support. [ABSTRACT FROM AUTHOR]

Taking 57 prefecture-level cities in the Yellow River basin as a research area, this study evaluates the coupling coordination level of the water–energy–carbon (WEC) system in the Yellow River basin from 2012 to 2021 and explores the driving factors of coupling coordinated development. The study revealed that: (1) the development level of the three subsystems all showed an upward trend. The development level of the carbon system exhibited the highest level. The development index of the carbon and energy systems rose steadily, whereas the development index of the water system fluctuated considerably during the research period, although the magnitude of the fluctuation gradually slowed down. (2) The coupling coordination degree displayed a distribution characteristic of "high in the east and low in the west, high in the south and low in the north". While the coupling coordination degree improved year by year, the spatial heterogeneity gradually increased. (3) The coupling coordination degree presented a positive correlation, and the agglomeration level was dominated by "high-high" and "low-low" agglomeration types. The "high-high" agglomeration area had a certain degree of spatial mobility, while the "low-low" agglomeration areas showed a tendency for spreading towards the middle reaches of the Yellow River basin. (4) Technological innovation, and the economic basis, had a significant positive impact on the coupling coordinated development, while the industrial structure bias showed a clear inhibitory effect. The positive role of opening up is not yet significant. Meanwhile, the indirect effect of each driving factor was greater than the direct effect. [ABSTRACT FROM AUTHOR]

The manufacturing industry is the pillar industry of China's economy and a major carbon emitter, and its carbon emission reduction efforts directly determine whether the country's carbon emission reduction target can be successfully met. In the context of the goals of the carbon peak and carbon neutrality policy, we examine the impact of manufacturing structure optimization on carbon emissions from 2003 to 2020 through a spatial econometric model, taking the old industrial centers in Northeast China as an example. We then apply a machine learning model to simulate manufacturing carbon emissions during the carbon peak stage and identify the optimal path for carbon emission reduction, which is important for promoting manufacturing carbon emission reduction in Northeast China. Since the goal of low-carbon economic development has gradually replaced the goal of maximizing economic efficiency in recent years, manufacturing structure optimization has come to focus on energy saving and emission reduction. Therefore, we define manufacturing structure optimization from the dual perspective of technology and energy consumption to broaden the existing research perspective. The results show the following: (1) The overall trend in manufacturing structure optimization in Northeast China is steadily improving, and the level of manufacturing structure optimization from the technology perspective is higher than that from the energy consumption perspective. (2) Manufacturing structure optimization and manufacturing carbon emissions in Northeast China both show a positive spatial correlation. Manufacturing structure optimization in Northeast China can effectively promote carbon emission reduction, and it also has a spatial spillover effect. (3) The carbon emission reduction effect of manufacturing structure optimization from the energy consumption perspective is better than that from the technology perspective, and the carbon emission reduction effect under the institutional innovation scenario is better than that under the baseline scenario and the technological innovation scenario. Focusing on manufacturing structure optimization from both technology and energy consumption perspectives, as well as continuously improving technological innovation and institutional innovation, can help to achieve manufacturing carbon emission reduction in Northeast China. [ABSTRACT FROM AUTHOR]

To solve the problems of the impact of carbon emission reduction and low-carbon advertising on the supply chain of fresh agricultural products, a three-level low-carbon supply chain system composed of a manufacturer, a retailer and a third-party logistics service provider is taken as the research object. The profit functions of each party under the three contracts of the manufacturer bearing, the retailer bearing and the two parties jointly bearing the advertising cost are, respectively, established to solve the optimal pricing, advertising level preservation efforts, service levels and carbon emission reduction decisions. The numerical analysis shows that, with the increase in wholesale price and the decrease in fresh-keeping price coefficient and low-carbon cost coefficient, manufacturers will choose better fresh-keeping effort level and low-carbon service level. When the proportion of advertising cost borne by the supplier increases, the benefits of all parties in the supply chain will decrease; however, when the retailer bears the advertising cost alone, the profit of the supply chain system is the largest. [ABSTRACT FROM AUTHOR]

After the official launch of China's unified carbon market, the potential for carbon emission reduction is huge. The pilot regional markets urgently need to be connected with the national carbon market to form a regional synergy and linkage mechanism and further promote the development of a unified carbon market. Spillover effects can be used to analyze the interaction between multiple markets. In this context, this study focuses on the overall spillover relationship among regional carbon trading markets. Using the VAR-GARCH-BEKK model and social network analysis (SNA), this study empirically analyzes the mean spillover effect and volatility spillover effect of regional carbon markets, and it establishes a spillover network between markets. The results show that the spillover effect of China's regional carbon markets is widespread. Among them, the mean spillover effect is weak, and the impact period is short;. The volatility spillover effect is strong and has various directions; the spillover network connection between regional carbon markets is strong, but the spillover intensity is weak. Spillover effects will spread to the overall carbon market through information spillover paths and risk spillover paths. The stronger spillover effect and the stronger linkage between markets can bring more resource integration and unified supervision. Finally, we put forward policy recommendations, such as improving the carbon market mechanism and enhancing the maturity of carbon market development, increasing the participation and activity of the carbon market to encourage more participants to join the carbon market, improving the institutional system of the carbon market, and effectively supervising the process of information and risk spillover between carbon markets. [ABSTRACT FROM AUTHOR]

Based on China's goal of achieving carbon neutrality by 2060, this study focused on its coal gasification in 2010–2019. Carbon emissions were calculated from industrial data, and an LMDt model was established to analyze the influencing factors of carbon emissions. Through scenario analysis, the paths of carbon emission reductions in the chemical industry were analyzed, and their emission reduction potential was estimated. The results showed that the carbon emissions in the chemical industry increased rapidly in 2010–2019, reaching 196 million tons in 2019. The emission structure was the most important factor in mitigating carbon emissions, and the emission intensity, industrial structure, economic development level, and labor force scale had different degrees of promotion effects, of which emission intensity was the strongest. The chemical industry can reach a carbon peak before 2030 under the three analyzed scenarios, and the emission reduction potential is the largest under the landing policy scenario. The results showed that carbon capture, usage, and storage (CCUS) technology is key for carbon emission reductions and that it is necessary to adjust the industrial structure, reduce emission intensity, and increase forest carbon sink to achieve carbon neutrality in the chemical industry. [ABSTRACT FROM AUTHOR]