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Transitioning to clean cooking fuels is not only part of achieving SDG7 but also makes a significant contribution to mitigating climate change by reducing carbon emissions. Research projects and pilots across a number of countries in Africa and South Asia have been exploring the suitability and energy performance of different cooking appliances and fuels. The paper presents the first statistical analysis across these multiple datasets to determine the range of energy required to cook dishes using different technologies and fuels. The paper draws out distinctions between African and Asian dishes, notably the impact of energy-intensive dishes prepared mostly in Africa. The paper demonstrates that the standard efficiency-based approaches to comparing the performance of stoves are not appropriate to modern electric cooking devices, so a novel alternative approach based on specific energy consumption and termed energy ratios is developed. Charcoal stoves are shown to use 15 times as much energy as electric pressure cookers (EPCs) to cook African dishes, and a detailed review of how the EPC works explains why this should be. Energy ratios provide a basis for estimating carbon emission reductions associated with transitioning to modern cooking fuels and also for estimating household cooking costs. Fuel and electricity prices from studies show that the cost of cooking with an EPC can be only 20% of the cost of cooking with charcoal, which highlights the potential for modern, energy-efficient electric cooking devices to defy the conventional wisdom of the energy ladder. [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]

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]

The decarbonization of power systems plays a great part in the carbon neutrality goal. Currently, researchers have explored reducing carbon in power systems in terms of the optimization of energy supply structure and operation strategies, but ignored the carbon reduction potential of users. To investigate the carbon reduction capability of users and further promote power system decarbonization through the active response of electricity loads, this paper proposes a carbon-reduction-oriented demand response (CRODR) technology based on generalized nodal carbon emission flow theory. First, the framework of the CRODR mechanism is established to provide an interaction baseline for users facing carbon reduction guiding signals. Secondly, the generalized nodal carbon emission flow theory is introduced to provide a calculation method for the guiding signals, considering dynamic electricity carbon emission factors with various spatiotemporal resolutions. Then, a matrix-based method is proposed to efficiently solve the carbon emission flow and obtain the guiding signals. On this basis, an optimal load-regulating model to help users meet their carbon reduction goals is built, and a carbon reduction benefit-evaluation method is proposed. Case studies on China's national power system and a textile company verify that CRODR technology can realize efficient carbon reduction through load shifting while maintaining the total power consumption of users. The proposed CRODR technology is expected to provide a theoretical basis and guiding mechanism for promoting carbon reduction throughout the entire power system. [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]

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]

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]

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]

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]

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 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]

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]

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]

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]

Rising carbon emissions are linked to the increase in global temperature, because of increasing human activities and increasing greenhouse gas emissions. Since manufacturing is one of the most carbon intensive sectors, it is vital to suggest solutions that lead to carbon emission reduction in all sectors, among which is the steelmaking manufacturing sector. The present study focuses on presenting a framework for energy intensive industries introducing digitalization and energy efficient equipment in the production line. The current framework proposes different metrics, both from carbon emissions and cost viewpoints. A secondary steelmaking industry was used as a case study, showcasing the impact of digitalization and energy efficient equipment towards the reduction of carbon emissions. In addition, different metrics were calculated with energy efficient scenarios providing the lowest energy consumption metric, but their high purchasing costs make these scenarios less attractive. However, if carbon emission reduction per cost is the metric, a combination of digital tools and energy efficient equipment is the answer to the company's needs. Applying the concepts of innovation absorption and digitalization, the number of alternatives is kept low, however, the impact on the line is quite large. The introduction of new technologies is also supported by training of the workforce, aligning the framework with current industrial trends. [ABSTRACT FROM AUTHOR]