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The integration of the digital transformation of agriculture and China's 'dual-carbon' strategy for agriculture is new momentum for developing agriculture, reducing rural income inequality, and improving the subjective well-being of farm households. This paper uses data from the China Family Panel Studies (CFPS) in 2014, 2016, and 2018 to examine the impact of internet use on rural income inequality at the household level. The results show that internet use can significantly reduce rural income inequality by enhancing information availability and farm households' nonfarm employment level. The results of a heterogeneity analysis reveal that the internet is more conducive to improving the income inequality of rural burdened families and families in Western China. Further analysis shows that improving income inequality can enhance the subjective well-being of farmer households. Accelerating the construction of digital villages, building internet skills cultivation systems, and focusing on the utility of internet use among vulnerable rural groups can reduce rural income inequality. [ABSTRACT FROM AUTHOR]

Copyright of China Mining Magazine is the property of China Mining Magazine Co., Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Vigorously developing new energy sources is an important approach to achieving the carbon peaking and carbon neutrality goals. However, the randomness, volatility, and intermittency of new energy pose severe challenges to the supply-demand balance and stability of the electric power system. Therefore, there is an urgent need to develop diversified flexible resources to guarantee the system’s safe and stable operation. This study summarizes the electricity demand and the power structure development pathways in China under the carbon neutrality goal. Based on this, it analyzes the different flexibility demands of electric power systems with different proportions of wind and solar power generation capacities and elaborates on the characteristics of various types of flexible resources needed for power generation, transmission, load, and storage from four aspects: peak capacity (adequacy), ramping flexibility, stability, and inertia. Drawing from the international experience regarding flexible resource development, we propose the principles for flexible resource development: supply security guarantee, low-carbon development, and economic optimization. Considering the existing problems in the flexible resource development in China, we propose a flexible resource development pathway that aligns with the emission reduction goal of the power sector and the medium- to long-term development trend of the electric power structure of China. Furthermore, key initiatives to ensure the development of flexible resources are proposed from five aspects: power source, power grid, load, energy storage, and market mechanism.

Considering the dual requirements of stability and low carbon, integrating clean coal power with carbon capture, utilization and storage (CCUS) and combining new energy power generation with energy storage have become the inevitable trends of China’s power industry. This study investigates the typical cases regarding clean coal power, CCUS, new energy power generation, and energy storage in China and abroad, analyzing the trend of technological development. A levelling cost model is used to measure the economical efficiency and changes of “clean coal power + CCUS” in three stages: current stage, technological breakthroughs, and commercial application. The competitiveness of “clean coal power + CCUS” is evaluated by comparing it with the “new energy + energy storage” mode from three dimensions: economical efficiency, stability, and security. The results indicate that technological breakthroughs and commercialization of CCUS will reduce the cost of “clean coal power + CCUS” by 30.3%−77.6%. When the cost of CCUS is lower than 550 CNY/t CO2, “clean coal power + CCUS” is more competitive than the “new energy + energy storage” mode. When the cost of CCUS is lower than 150 CNY/t CO2, the cost of “clean coal power + CCUS” will be lower than that of “new energy + energy storage”. Moreover, advantageous technical routes and application scenarios of “clean coal power + CCUS” are calculated and analyzed based on the competitiveness and synergy of “clean coal power + CCUS” and “new energy + energy storage”. The breakthrough directions and technical path of zero-carbon clean coal power are proposed from the aspects of improving the complementarity of clean coal power, enhancing the competitiveness of “clean coal power + CCUS”, and promoting the optimal combination of coal power and new energy. Furthermore, the following suggestions are proposed to promote the development of lowcarbon clean coal: (1) clarifying the preferential technology route, (2) strengthening the research and development of transformative and disruptive technologies, (3) improving the peak shaving capability of clean coal-fired power units, (4) promoting the coupling and coordinated development of coal-fired power and new energy, and (5) establishing a high-end composite talent support system.

Under the background of "dual carbon" strategy, the integration of renewable energy adds volatility to the grid. Relying solely on generation-side resources for regulation is inadequate, necessitating a flexible demand response from diverse demandside resources. This paper employs a physical connection and information exchange between the distribution network and microgrids to leverage the advantages of centralized-distributed optimization. This establishes a coordinated demand response model between the distribution network and microgrids, gradually establishing a new type of distribution network that integrates interconnected grids and microgrids. This also necessitates the analysis of the response characteristics of various load resources within microgrids and the categorization and modeling of loads based on their response speeds. Additionally, a method for evaluating the multi-time scale schedulable capacity of microgrids is proposed. Finally, a coordinated demand response model between the distribution network and microgrids based on the schedulable capacity assessment is established. This model is validated through case studies, demonstrating its effectiveness. The coordinated demand response between distribution networks and microgrids enables them to operate in a collaborative and economically safe manner. [ABSTRACT FROM AUTHOR]

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The implementation of emission reduction and carbon reduction measures and the implementation of the “double carbon” goal are important transformation opportunity for coal chemical enterprises to move towards high-end,diversified and low-carbon development. Shaanxi Coal Industry Group Yulin Chemical planned a 4 million ton/year carbon dioxide capture, transportation and storage (CCS) demonstration project and carried out a 400000 ton/year pilot test project to help the country reach carbon peak and carbon neutrality. Based on the experience of Shenhua 100000 ton CCS demonstration project and CO2 produced in the 1.8 million ton/year ethylene glycol project, two supercritical CO2 storage processes, high purity (98.94%) and low purity (77.78%), are designed in this paper; Based on the understanding of Triassic and Permian salt water layers in the eastern Ordos Basin, three sets of geological salt water layers (Liujiagou Formation, Shiqianfeng Formation and Shihezi Formation) with good physical properties and great CO2 storage potential were found.After in-depth evaluation and analysis of CO2 storage layer cover and storage capacity, it is believed that the best storage environment for CO2 in salt water layer over 1000 meters. By designing four injection and storage Wells and combining with the numerical simulation method, the storage operation mechanism of 400000 ton/year CO2 is studied and analyzed, and it is theoretically feasible; It is designed to use PNX logging, downhole optical fiber sensing and surface InSAR monitoring methods to build an integrated monitoring and management platform for CO2 from wellbore to reservoir and then to reservoir diffusion; From the perspective of CCS’s current economic and technological costs, industrial policy development, opportunities and challenges,the development of CCS in coal mining chemical industry has great potential.

In order to realize in-situ, green and large-scale disposal of coal gangue, coal gangue slurry filling technology, as a new filling technology, has been rapidly developed and applied in recent years. This paper systematically reviews and summarizes the landmark achievements and key technologies of coal gangue slurry filling at different stages, such as the proposal of the technical framework, the formation of the theoretical system of slurry filling, the application of engineering demonstration and the innovation of technology iteration, and forms three filling methods, namely, high-level grouting, low-level grouting and adjacent grouting. The “intervention theory” of coal gangue slurry flow in goaf caving zone and the “three degrees and one field” theory of slurry pipeline transportation have been established, and the first demonstration project of coal gangue underground slurry filling and surface slurry preparation + underground adjacent grouting filling has been successfully carried out at home and abroad; This paper expounds the technical system of coal gangue slurry filling, and discusses the key technical core issues of coal gangue high-efficiency grading crushing, slurry precise preparation, slurry pipeline transportation and end filling, focusing on the process flow of coal gangue crushing, water slurrying of finished gangue powder, slurry pumping preparation and underground target area filling. The technical principles and application scenarios of key equipment such as crushing equipment, screening equipment, metering equipment, mixing equipment and pumping equipment are analyzed; Based on the engineering background of small space, multi-equipment and high capacity of coal gangue slurry filling in Zhangjiamao Coal Mine, the layout of different systems such as surface slurry making, pipeline transportation, underground filling and intelligent control of coal gangue slurry filling was innovatively developed and designed, and the annual filling amount of coal gangue could reach 554 000 tons, forming a demonstration of coal gangue slurry filling engineering. In the future, the coal gangue slurry filling technology will be further studied and developed in the direction of small and lightweight equipment, highly integrated system, iterative and innovative technology, which will provide technical support for the construction of green coal mining technology system and the realization of the national carbon peaking and carbon neutrality goal.

The coal industry is the ballast stone and stabilizer that supports the rapid development of China’s economy and society and ensures national energy security. It also undertakes the mission of ensuring energy supply and supporting the stable development of new energy. At present, the high-quality development of China’s coal industry has achieved some staged results, with remarkable achievements in energy supply, the continuous optimization of industrial structure, the significant improvement of scientific and technological innovation capabilities, and the continuous advance of green development and clean and efficient utilization. However, the current development level of the coal industry is far from meeting the national needs of Chinese-style modernization. The sustainable development is restricted by multiple factors. The digital technology and coal development and utilization have not yet been deeply integrated. The intelligent construction is still in the demonstration and cultivation stage. The green development is unbalanced and contradictory and prominent. The transformation and upgrading of the coal industry still has a long way to go. In view of the current development status and challenges of the coal industry, this paper proposes a synergistic development mode of digitalization, intelligentization and greenization (three -izations), clarifies the core connotation of new-quality coal productivity, constructs the overall framework of the synergistic development of new-quality coal productivity, and expounds the technical path for the transformation of the innovative allocation of production factors by digitalization, the breakthrough of key technologies led by intelligentization, and the deep transformation of traditional industries by greenization, i.e., by these three factors to generate new-quality coal productivity. Six major technical systems are proposed: through the research and development of the technical system of efficient data collection and in-depth governance of the whole industry chain, the data barriers among coal production, transportation, storage, marketing and use of the whole process are removed. Through the research and development of the knowledge map and intelligent decision-making and control technological system of the coal industry, the correlation relationship and value of the upstream and downstream business scenarios of the coal industry are deeply explored, so as to lay the foundation for the independent decision-making and intelligent control of the whole process of coal production and utilization. Also, the research should be carried out in terms of the intelligent-green-efficient development technological system of coal resources, the technical system of collaborative guarantee of safety in the coal industry, the technical system of ecological intelligent monitoring-early warning-restoration in mining areas, and the technical system of flexible development and clean and low-carbon utilization of coal, so as to realize the synergistic development of the whole industrial chain and the whole process of coal development and utilization, cultivate and form a new-quality coal productivity, and bring some fundamental changes and improvements to the overall image of the coal industry.

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Copyright of Coal Science & Technology (0253-2336) is the property of Coal Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Low-Carbon Chemistry & Chemical Engineering is the property of Low-Carbon Chemistry & Chemical Engineering Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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Driving enterprises to implement carbon emission reduction actions and reduce carbon emissions is a crucial research topic in achieving the carbon peaking and carbon neutrality goals. As a significant external environment factor influencing corporate behavior, can institutional pressures effectively promote enterprises to reduce carbon emissions? This study aims to probe into the impact and mechanism of three institutional pressures, namely coercive, mimetic, and normative, on corporate carbon emissions, taking Chinese-listed companies as the research object. The results indicate that coercive pressure is positively associated with corporate carbon reduction, while normative pressure has no significant impact. Furthermore, mimetic pressure impedes corporate carbon emissions. The mechanism test shows that carbon reduction is a mediator in the influence exerted by three institutional pressures on corporate carbon emissions. In response to coercive pressure and mimetic pressure, enterprises tend to reduce their carbon emissions by cultivating concepts related to carbon emission reduction. Concepts related to carbon reduction play a more dominant role than carbon reduction actions when both are mediators, with the former even replacing the latter. This research provides a new perspective for improving corporate environmental performance and corporate sustainability. [ABSTRACT FROM AUTHOR]

Copyright of Arid Land Geography is the property of Chinese Academy of Sciences, Xinjiang Institute of Ecology & Geography and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

SignificanceWith the escalating global climate change and ecological pollution issues, the "dual carbon" target of Carbon Peak and Carbon Neutrality has been incorporated into various sectors of China's social development. To ensure the green and sustainable development of agriculture, it is imperative to minimize energy consumption and reduce pollution emissions at every stage of agricultural mechanization, meet the diversified needs of agricultural machinery and equipment in the era of intelligent information, and develop low-carbon agricultural mechanization. The development of low-carbon agricultural mechanization is not only an important part of the transformation and upgrading of agricultural mechanization in China but also an objective requirement for the sustainable development of agriculture under the "dual carbon" target.Progress]The connotation and objectives of low-carbon agricultural mechanization are clarified and the development logic of low-carbon agricultural mechanization from three dimensions: theoretical, practical, and systematic are expounded. The "triple-win" of life, production, and ecology is proposed, it is an important criterion for judging the functional realization of low-carbon agricultural mechanization system from a theoretical perspective. The necessity and urgency of low-carbon agricultural mechanization development from a practical perspective is revealed. The "human-machine-environment" system of low-carbon agricultural mechanization development is analyzed and the principles and feasibility of coordinated development of low-carbon agricultural mechanization based on a systemic perspective is explained. Furthermore, the deep-rooted reasons affecting the development of low-carbon agricultural mechanization from six aspects are analyzed: factor conditions, demand conditions, related and supporting industries, production entities, government, and opportunities.Conclusion and Prospects]Four approaches are proposed for the realization of low-carbon agricultural mechanization development: (1) Encouraging enterprises to implement agricultural machinery ecological design and green manufacturing throughout the life cycle through key and core technology research, government policies, and financial support; (2) Guiding agricultural entities to implement clean production operations in agricultural mechanization, including but not limited to innovative models of intensive agricultural land, exploration and promotion of new models of clean production in agricultural mechanization, and the construction of a carbon emission measurement system for agricultural low-carbonization; (3) Strengthening the guidance and implementation of the concept of socialized services for low-carbon agricultural machinery by government departments, constructing and improving a "8S" system of agricultural machinery operation services mainly consisting of Sale, Spare part, Service, Survey, Show, School, Service, and Scrap, to achieve the long-term development of dematerialized agricultural machinery socialized services and green shared operation system; (4) Starting from concept guidance, policy promotion, and financial support, comprehensively advancing the process of low-carbon disposal and green remanufacturing of retired and waste agricultural machinery by government departments.

Carbon emission reduction in the construction industry is crucial for promoting low-carbon transformation of the industry and for realizing the carbon peaking and carbon neutrality goals. This study analyzes the current status of carbon emissions in Chinese construction industry. It identifies that the production of building materials and the operation of buildings are the primary sources of carbon emissions in the overall construction process. Moreover, the growth rate of carbon emissions from the construction industry in China is decelerating, and the spatial characteristics of carbon emissions demonstrate an increase from the south to the north and from the west to the east. We have identified six key challenges that must be addressed to achieve carbon peaking and carbon neutrality in the construction industry of China: policy and standards framework, energy-efficient and carbon-reducing technologies, reduction of carbon emissions from existing buildings, carbon emission data collection and monitoring systems, economic incentives, and increased awareness of carbon reduction. Staged goals for the low-carbon development of the construction industry are also proposed. Furthermore, we suggest improving related policies and standards system, optimizing the use of energy-saving technologies, reducing carbon emissions in existing buildings, developing green finance, improving the ability to monitor carbon emissions, and enhancing the awareness of energy conservation and carbon reduction, so as to provide references for the low-carbon transformation and high-quality development of China’s construction industry.

In this paper, an NEV purchase intention model featuring "external scenario-internal scenario-application behavior" is built on the basis of technology acceptance model and situational factors. A questionnaire survey combined with structural equation modeling is conducted to investigate the impacts of diversified policies concerning regulatory restrictions, support & improvement, technological enhancement and financial incentives on NEV consumers' purchase intention. Our research results show the financial incentives exert the greatest influence on consumers' purchase intention, followed by the technological enhancement and the regulatory restrictions. Policies concerning the support & improvement indirectly affect consumers' purchase intention by creating positive conforming-to-the-public mentality, but they have the least impact on consumers' purchase intention. From the perception perspective, the perceived value has a fairly large impact on consumers' purchase intention. [ABSTRACT FROM AUTHOR]

Copyright of Smart Agriculture is the property of Smart Agriculture Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study defines Provincial Carbon Emission Characteristics (PCEC) as the socioeconomic conditions influencing provincial carbon emissions, the potential for carbon neutrality, and carbon management strategies. Given China’s commitment to peak carbon emissions and to achieve carbon neutrality, the development of a robust and versatile PCEC evaluation system is imperative. However, previous studies that rely on single-objective evaluation models are limited. To address this gap, we propose a multi-objective PCEC evaluation system using a novel three-layer approach. This approach enhances the scientific rigor, comprehensiveness, and comparability of PCEC evaluation indicators (PCEC-EIs) by segregating the extraction process into three layers: (1) a factor layer, which identifies critical socioeconomic conditions; (2) a quantitative layer, which selects optimal quantitative indicators for each identified condition; and (3) a standardized layer, which standardizes these indicators, thereby improving their comparability. By applying hierarchical cluster analysis, our study classified 30 Chinese provinces into 7 distinct clusters, each with unique carbon emission characteristics. Further investigation of these clusters across various climate governance issues revealed the versatility of our multi-objective PCEC evaluation system. Our system supports the identification of provinces qualified to reach the emission peak earlier than 2030, differentiation of carbon intensity reduction efforts during the carbon peaking stage, and exploration of various emission reduction pathways to achieve carbon neutrality. Hence, our findings can guide the creation of bespoke emission-reduction strategies for each province; thus, aiding China’s national ambition to achieve peak carbon emissions and carbon neutrality. Importantly, our three-layered approach has broader implications beyond China, potentially assisting other regions or countries in grappling with similar climate-mitigation challenges.

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Copyright of Modern Economic Science is the property of Modern Economic Science Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Ecology & Rural Environment is the property of Journal of Ecology & Rural Environment Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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• analyze the energy efficiency of Beijing's industrial sectors from 2002 to 2018. • model industry heterogeneity of Beijing's industrial sectors accurately. • low energy efficiency of Beijing's industrial sectors due to management inefficiency. • the energy efficiency of heavy industry is higher than that of light industry. • explore the influencing factors of energy efficiency of Beijing's industrial sectors. Improving energy efficiency is one of the effective means to achieve China's carbon peaking and carbon neutrality goals. As the capital of China, Beijing should improve energy efficiency and has a primary responsibility in achieving the goals. Considering the heterogeneity of industrial sectors, this paper proposes a data envelopment analysis (DEA) approach to analyze the total factor energy efficiency and its influencing factors of 31 industrial sectors in Beijing from 2002 to 2018. We show that the low energy efficiency of Beijing's industrial sectors, mainly due to management inefficiency, is not conducive to the realization of the goals. Besides, the energy efficiency of heavy industry is higher than that of light industry. The expansion of enterprise scale has a positive impact on energy efficiency, while the property right structure, foreign trade and energy consumption structure have a negative impact on energy efficiency. Finally, we put forward some policy recommendations. [ABSTRACT FROM AUTHOR]

Copyright of Modern Economic Science is the property of Modern Economic Science Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Modern Economic Science is the property of Modern Economic Science Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

To accelerate the pace of realizing carbon peaking and carbon neutrality goals, it is increasingly urgent to optimize the energy consumption of crude oil pipeline system, which is an important part of energy system. Therefore,a universal optimization model of energy consumption for swarm intelligence optimization was proposed based on the combination of pipeline simulation and penalty factor. In this way, the intelligent optimization process was realized to make the unreasonable schemes become reasonable, and the reasonable schemes to be optimal. Specifically, comparison was made for several swarm intelligence optimization algorithms that were widely applied based on RizhaoYizheng Crude Oil Pipeline System. In terms of the energy consumption optimization of crude oil pipeline system,the differential evolution algorithm was found to be capable of providing more stable and better energy consumption,thus having a better effect of energy consumption. Further, good optimization effect was obtained by applying the new optimization model of energy consumption and the differential evolution algorithm to several actual crude oil pipelines with different characteristics, including Yizheng-Changling Pipeline, Yizheng-Changling Double Pipeline and Dongying-Linyi Double Pipeline. It is indicated that the proposed optimization method is of great universality.Thus, the research results could provide technical support for the energy saving and consumption reduction of crude oil pipeline systems.

China's carbon peaking and carbon neutrality targets have created huge challenges for all the economic sectors in China, including the shipping industry. Various emission reduction measures, such as Waste Heat Recovery Systems (WHRSs), Drag Reduction Coatings (DRCs), and Slow Steaming (SS), are the main options for container ship companies to select in advance. This paper aims to find the optimal combination of measures for container ship companies to reach the carbon reduction targets, which are mainly set according to the carbon reduction requirements of the International Maritime Organization (IMO). A 0–1 integer programming model is proposed under the Maritime Emissions Trading Scheme (METS) to help container ship companies select the optimal combination of measures in the context of carbon peaking and carbon neutrality. Our results show that combination 6 (using a WHRS alone and a 5.0% reduction in the original speed) is the most suitable solution with the selected values of parameters. Sensitivity analyses of the parameters are performed, such as bunker price, the auction and purchase prices of carbon and incentive levels. From the sensitivity analysis, it is found that using a WHRS is the optimal combination of abatement measures within the fluctuation range of the parameters. At the same time, according to the results, container ship companies could choose the most appropriate and profitable strategy in the dual-carbon context. Therefore, container ship companies and policymakers have access to relevant carbon reduction suggestions to encourage the implementation of carbon reduction initiatives. [ABSTRACT FROM AUTHOR]

The adoption of new energy vehicles (NEVs) can effectively reduce vehicle exhaust emissions and achieve carbon peaking and carbon neutrality goals in the transportation sector. To facilitate the development of NEVs, the Chinese government issued the dual credit policy (DCP). However, whether the DCP can promote the technological innovation of NEVs and effectively reduce carbon emissions in the transportation sector remains to be studied. This study constructed the decision-making model of NEVs under the DCP and obtained the optimal strategy to study the impact of the DCP on carbon emissions. Furthermore, we constructed a bargaining game model based on an alliance strategy to demonstrate the coordination of the NEV supply chain. The results showed that implementing the DCP can effectively reduce carbon emissions in the transportation field. The higher the technological innovation credit coefficient or credit price, the more significant the DCP’s incentive effect on reducing carbon emissions. Decentralized decision-making weakens the DCP’s incentive effect on reducing carbon emissions. The bargaining game based on alliance negotiation can enable independent companies to achieve carbon emission reduction when making centralized decisions so that the DCP’s incentive effect on reducing carbon emissions is optimized. The alliance between manufacturers is not to increase profits but to enhance their product advantages. However, suppliers can gain higher profits by participating in the alliance, which provides a theoretical reference for the alliance’s cooperation in decision-making.

Consolidating carbon sink capacity and reducing carbon pressure are important channels to achieve the carbon peaking and carbon neutrality goals actively yet prudently. In order to study the current situation of carbon pressure in the Northwestern Sichuan, we took the carbon pressure of the Aba Tibetan-Qiang autonomous prefecture (Aba prefecture) as an example and used the Intergovernmental Panel on Climate Change (IPCC) approach to measure the carbon emissions, carbon uptake, and the carbon balance index (CBI) of each county-level city in Aba prefecture from 2012 to 2020. The study found that: (a) There was a continuous trend of declining carbon emissions, increased carbon uptake, and decreased CBI in Aba prefecture during the sample period, but there is a large variability among county-level cities; (b) Aba prefecture differs in the spatiotemporal distribution of carbon emissions, carbon uptake, and CBI. Based on the research results, we propose several optimized paths for alleviating the current carbon pressure situation in the Northwestern Sichuan. [ABSTRACT FROM AUTHOR]

Copyright of Agricultural Outlook (1673-3908) is the property of Institute of Agricultural Information, Chinese Academy of Agricultural Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In order to simulate the impacts of carbon peaking and carbon neutrality goals on power system supply side transformation from, the system dynamics method is used to analyze the main influencing factors for carbon emissions in the process of power structure transformation and their correlations under four different development scenarios. The evolution of power generation structure and power carbon emission in four development paths are studied. The results show that the power system supply side transformation would be affected by many factors. Under the premise of policy support, the development of market absorption mechanism and absorption technology would contribute to the transformation of the power generation structure, which is of great significance to the realization of the dual carbon targets.

Although shipping is a relatively energy-saving and environmentally friendly mode of transportation, the growth rate of its energy consumption and carbon emissions far exceeds that of other industries. As an important response to climate change, shipping decarbonization is not only an important part of achieving the temperature control goal of the Paris Agreement but is also an important direction for the future development of China’s ecological civilization construction. China has formulated and promulgated legislation and policies on shipping decarbonization both at the national and local levels. The proposal in 2020 of the goal of carbon peaking and carbon neutrality has accelerated this process. In this context, this paper aims at reflecting on legislation and policies for decarbonization of shipping under China’s “double carbon” target, and proposing suggestions for improvement. Firstly, we systematically review China’s legislation and policies on shipping decarbonization to outline the normative system of China’s shipping carbon reduction. Secondly, this paper evaluates China’s legislation and policies on shipping decarbonization from the perspective of both achievements and challenges. Finally, this paper proposes that China’s legislation and policies for decarbonization of shipping should be further improved from two aspects: enhancing mandatory force and expanding normative content.

The Yellow River Basin (YRB) serves as a critical energy hub in China. Enhancing energy efficiency in cities across the YRB is pivotal for achieving high-quality development and meeting carbon peaking and neutrality targets. This paper proposes a multidimensional technology heterogeneity assessment framework to refine the classification of production technologies. It leverages this framework to develop a data envelopment analysis model for evaluating green total factor energy efficiency (GTFEE) in 78 cities within the YRB from 2006 to 2022. The key findings are as follows: (1) Grouping outcomes from the multidimensional heterogeneity framework significantly differ from existing literature. (2) GTFEE shows notable spatiotemporal variations within the YRB, with a substantial overall increase since 2011. However, cities in the central YRB exhibit lower GTFEE performance. (3) Energy inefficiency in groups 1, 2, and 3 is attributed to developmental inefficiency, management inefficiency, and practical inefficiency, respectively. (4) Evaluation of energy-saving potential reveals an average annual potential of around 8 million tce per city during 2006–2022. The study concludes with strategies for enhancing GTFEE based on dynamic GTFEE decomposition outcomes, supporting policy design for achieving dual-carbon goals through improved energy efficiency in the YRB region. • Technology heterogeneity grouping results differ from those in literature. • GTFEE within the Yellow River Basin exhibits significant spatiotemporal variations. • Sources of energy inefficiency vary among the groups. • Average annual energy-saving potential of approximately 8 million tce per city during 2006–2022. • GTFEE improvement path is devised according to the decomposition of MMGTFEEI. [ABSTRACT FROM AUTHOR]

Prioritizing the reduction of carbon emissions in key developing urban centers is a significant step toward achieving China's carbon peaking and neutrality goals. We examined the Chengdu metropolitan area as a case study. We proposed a coupled method for inversely estimating nighttime light and carbon emissions from energy consumption, enhancing the accuracy of fitting at the county scale and addressing the issue of missing energy consumption data. We integrated the Tapio decoupling model and the Logarithmic Mean Divisia Index (LMDI) model for comprehensive analysis, mitigating the limitations arising from the use of a singular model. Furthermore, we employed a multi-scenario analysis with an extended STIRPAT model to forecast the carbon emission trajectory of the Chengdu urban agglomeration and elucidate potential pathways for achieving carbon peaking and carbon neutrality goals. The findings indicated the following: (1) carbon emissions are predominantly concentrated in regions characterized by high levels of urban development. Forested land serves as the primary carbon sink; however, its capacity in the Chengdu metropolitan area fails to offset carbon emissions from energy consumption; (2) factor decomposition analysis revealed that economic development was the principal driver of carbon emissions, leading to an increase of 23.7964 million tons. Conversely, energy intensity emerged as the primary mitigation factor, reducin g carbon emissions by 11.0677 million tons; (3) The Chengdu metropolitan area is projected to reach a carbon peak by 2030, with the multi-factor coordinated optimization (MFO) model representing the most favorable trajectory, with a projected peak of approximately 15.6998 million tons. However, to achieve carbon neutrality by 2060, there is still a surplus of approximately 10.4808 million tons. • The carbon sink effect of forests is insufficient to offset the carbon emissions generated by energy consumption. • Multiscale analysis of carbon emission status. • Four scenario models have been developed to explore the path of regional scientific emission reduction. • Achieving carbon neutrality in the study area presents a challenge. [ABSTRACT FROM AUTHOR]

The Healthy China 2030 Initiative is closely related to the coordinated development between national health, economy, and society. This major move demonstrates China's active engagement in global health governance and in the fulfillment of the 2030 Agenda for Sustainable Development (SDGs). Based on Grossman's health production function, this paper introduces key factors such as environmental pollution and environmental regulation to empirically investigate the regulating effect of environmental regulation, as well as the spatial spillover of environmental pollution and environmental regulation acting on resident health. We examine these effects by using the panel data of 28 cities of the urban agglomeration in the middle reaches of the Yangtze River (UAMYRY) between 2009 and 2019. The results show that: (1) Environmental pollution brings a loss to resident health. Among the urban agglomerations, the circum-Changsha–Zhuzhou–Xiangtan urban agglomeration (CCZXUA) and the Poyang Lake urban agglomeration (PLUA) have a much lower health effect of environmental pollution than the Wuhan urban agglomeration (WUA). (2) With the growing intensity of environmental regulation, the negative effect of environmental pollution on resident health will gradually decrease. Regionally, the environmental regulation in the CCZXUA has the best effect on residents' health, followed by the WUA and the PLUA, which have the worst. (3) As a whole, the spatial spillover of environmental regulation and pollution has a significant impact on residents' health, and the spatial spillover effect between urban agglomerations is stronger than that between cities in each urban agglomeration. The conclusions remain robust with various tests such as replacing control variables, introducing lagged explanatory variables, and considering endogeneity. Based on robust empirical evidence, several specific region policy suggestions, including rolling out proper environmental regulation policies, and establishing a linking mechanism of environmental management, were put forward to improve the environmental pollution state and resident health level of the UAMYRY. [ABSTRACT FROM AUTHOR]

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With the introduction of “dual carbon” goals of “peaking its carbon emissions before 2030 and achieving carbon neutrality by 2060" and the gradual promotion of the carbon trading market, it is the main trend to achieve low-carbon and clean development in the future. It is of great practical significance to effectively measure the low-carbon development level and conduct obstacle degree analysis. Based on this, this article aims to investigate the low-carbon development level index of Fujian province from 2006 to 2019 by using the entropy weight TOPSIS model. Then, the key influencing factors are explored by using the obstacle degree model. The results show that the low-carbon development level index of Fujian province shows a fluctuating upward trend, rising from 0.164 in 2006 to 0.803 in 2019. The environmental system has always been an important factor affecting the low-carbon development in Fujian province, with an average annual obstacle degree of 46.52%, but the impact of the other three subsystems is also gradually increasing. Green innovation, energy conservation, air pollution, economic development, and environmental governance are the top five indexes with the highest annual obstacles. Based on the previous results, this article puts forward corresponding policy recommendations, which provide theoretical support for the low-carbon development of Fujian province.

China’s carbon peaking and carbon neutrality targets have created huge challenges for all the economic sectors in China, including the shipping industry. Various emission reduction measures, such as Waste Heat Recovery Systems (WHRSs), Drag Reduction Coatings (DRCs), and Slow Steaming (SS), are the main options for container ship companies to select in advance. This paper aims to find the optimal combination of measures for container ship companies to reach the carbon reduction targets, which are mainly set according to the carbon reduction requirements of the International Maritime Organization (IMO). A 0–1 integer programming model is proposed under the Maritime Emissions Trading Scheme (METS) to help container ship companies select the optimal combination of measures in the context of carbon peaking and carbon neutrality. Our results show that combination 6 (using a WHRS alone and a 5.0% reduction in the original speed) is the most suitable solution with the selected values of parameters. Sensitivity analyses of the parameters are performed, such as bunker price, the auction and purchase prices of carbon and incentive levels. From the sensitivity analysis, it is found that using a WHRS is the optimal combination of abatement measures within the fluctuation range of the parameters. At the same time, according to the results, container ship companies could choose the most appropriate and profitable strategy in the dual-carbon context. Therefore, container ship companies and policymakers have access to relevant carbon reduction suggestions to encourage the implementation of carbon reduction initiatives.

With the establishment of carbon peaking and carbon neutrality goals in China, developing low-carbon cities has become crucial. Previous studies primarily focus on the quantitative structure of land use to achieve low carbon optimization, while ignoring the spatial integration between urban form and carbon emissions. To fulfill this gap, this paper proposed a dual-scale low carbon oriented multi-objective land use allocation (DOLA) optimization model, utilizing idea-point multi-objective linear programming (IMLP) and non-dominated sorting genetic algorithm II (NSGA-II) to optimize the low-carbon-emission pattern of the city at both the structural and spatial scales respectively. By innovatively linking the urban shape index with carbon emissions, this model aims to minimize urban carbon emissions, while maximizing economic development, urban development suitability, and the compactness of city. The proposed method is applied to Wuhan's main urban area in China, the DOLA model shows significant improvements in target values across all scenarios. Among them, the scenario that prioritized low carbon emissions at both the structural and spatial scales achieved the most significant reduction of 6.43 % in carbon emissions. The DOLA effectively contributes to achieving multiple spatial targets, thereby aiding in reducing carbon emissions. It offers technical support for developing pathways towards China's "dual carbon" target. • A dual-scale low carbon oriented multi-objective land use allocation (DOLA) optimization model is proposed. • The DOLA model innovatively incorporates urban form indices to carbon emissions. • The DOLA model achieves spatial aggregation targets, thereby facilitating significant reductions in carbon emissions. • The DOLA model generates a series of land use optimization scenarios, offering a valuable reference for land use planning. [ABSTRACT FROM AUTHOR]