Properties and Characterization of Two Clays Raw Material from Mountain District (West of Côte d’Ivoire) for Use in Low-Carbon Cements

This work was devoted to the study of the physico-chemical properties of two clay minerals from the Mountain District (West Côte d'Ivoire) referenced ME1 and ME2. These samples were characterized by the experimental techniques, such as X-ray diffraction (XRD), Infrared spectroscopy (IR), Inductively Coupled Plasma Atomic Emission Spectrometry (ICP-AES), Differential Thermal Analysis and Thermogravimetry (DTA-TG), Brunauer, Emett and Teller method (BET), laser particle size analysis and Scanning Electron Microscope (SEM). The main results of these analyses reveal that the two clay samples mainly contain quartz (52.91% for ME1 and 51.72% for ME2), kaolinite (36.60% for ME1 and 41.6% for ME2) and associated phases, namely goethite and hematite (13.47% for ME1 and 11.00% for ME2). The specific surface values obtained for samples ME1 and ME2 are 34.78 m2/g and 29.18 m2/g respectively. The results obtained show that the samples studied belong to the kaolinite family. After calcination, they could have good pozzolanic activity and therefore be used in the manufacture of low-carbon cements.

Does China's digital economy contribute to low-carbon transition?

The digital economy,as a new emerging economic form,has become an important power for realizing Chinese-style modernization and promoting green development in China.This paper measures the digital economy and low-carbon transition index based on the data of 30 provinces in China from 2013 to 2020 and analyzes the mechanism and path of the digital economy affecting low-carbon transition using the fixed effect panel data model and the threshold effect model.It is found that,(1)The digital economy and low-carbon transition in China are various in different regions,with characteristics of being unbalanced and insufficient.(2)The digital economy significantly promotes low-carbon transition,with the greatest influence in the Central region,followed by the Eastern region and the Western region.Under different dimensions,the development of informatization and digital transactions promote low-carbon transition,but the development of the internet plays an inhibiting role.(3)The higher the degree of urbanization and environmental regulation,the greater the influence of the digital economy on low-carbon transition.

Effect of ZrC Modified Graphite on Structure and Properties of Low-carbon Al_(2)O_(3)-C Refractories

To address the issues of reduced performance and shortened lifespan during the low-carbonizating process of Al_(2)O_(3)-C refractories,nano-crystalline ZrC modified graphite was prepared using Zr powder and flake graphite as raw materials,with NaCl and NaF mixed salt serving as the medium.The flake graphite was gradually replaced by ZrC modified graphite in the preparation of Al_(2)O_(3)-C refractories,and its impact on the material’s structure and properties was investigated.The results indicate that,compared to samples with only flake graphite,the introduction of 1 mass%to 5 mass%nano-crystalline ZrC modified graphite can significantly enhance the mechanical performance of low-carbon Al_(2)O_(3)-C refractories.When 5 mass%ZrC modified graphite is added,the mechanical properties of the samples are optimal,with the cold modulus of rupture and elastic modulus reaching 22.5 MPa and 65.0 GPa,respectively.

Performance Evaluation of Low-Carbon and Clean Transformation of China’s Coal Economy

In China,the oversupply of coal occurred in 2009,and from that year onwards,China’s coal economy began a low-carbon and clean transformation.Evaluating transformation performance is the research goal of this paper.The data collection for this paper includes data on deep processing of Chinese coal products from 2009 to 2020,as well as data on asset structure evolution and financial performance of 34 listed companies in the Chinese coal mining.Entropy value method is used to calculate the entropy value of low-carbon transformation,and the regression analysis is used to study the performance of cleaner transformation,the conclusion is as follows:(1)From 2009 to 2020,in China’s total energy consumption,coal consumption accounted for 71.6%in 2009 and 56.8%in 2020,the goals set by the state have been achieved.(2)The national goal of reducing the proportion of coal consumption and reducing carbon emissions has forced the transformation of deep processing of coal products.The transformation of coal enterprises towards low-carbon and clean production has achieved remarkable results.(3)From 2009 to 2020,the non coal industry income of 34 listed companies in China’s coal mining industry increased by 8.21%annually.At the same time,the asset structure was adjusted,and nearly 80%of the asset structure evolution showed an orderly development trend.(4)The regression analysis results show that the entropy value of coal deep processing products and the entropy value of asset structure adjustment are significantly related to transformation performance.The paper proposes to summarize the successful experience of China’s coal energy economic transformation,lay a foundation for achieving the carbon peak and carbon neutral goals in the future,further increase the intensity of coal deep processing,increase the proportion of clean energy in total energy consumption,and strive to control asset operation towards the goal of increasing the proportion of non coal industry income.

A Mechanism for Digital Finance to Drive Green and Low-Carbon Development

Given the global focus on green and low-carbon development and the increasing prominence of digital finance,it is particularly important to explore how to leverage digital finance to achieve these environmental goals.This study,through mechanism analysis,deeply examines how China’s digital finance promotes green and low-carbon development and elucidates the positive interaction between digital finance and the green industry.The study found that digital finance,through more flexible and efficient financial functions,alters the cost structure of carbon emissions,and reduces the risks and costs of green investments,thereby creating a cooperative green mechanism benefiting all parties,and guiding social groups toward a green and low-carbon transformation.Additionally,the rapid development of digital finance has strengthened the implementation of environmental protection policies,effectively promoted the expansion of the environmental protection industry,and established the green ethos as a mainstream concept in financial development.This study aims to provide reference perspectives and suggestions,assist policymakers in promoting the green and lowcarbon development of digital finance,and offer insights into the integrated development of digital finance and the green environmental protection industry.

Plasma-electrified up-carbonization for low-carbon clean energy

Low-value,renewable,carbon-rich resources,with different biomass feedstocks and their derivatives as typical examples,represent virtually inexhaustive carbon sources and carbon-related energy on Earth.Upon conversion to higher-value forms(referred to as“up-carbonization”here),these abundant feedstocks provide viable opportunities for energy-rich fuels and sustainable platform chemicals production.However,many of the current methods for such up-carbonization still lack sufficient energy,cost,and material efficiency,which affect their economics and carbon-emissions footprint.With external electricity precisely delivered,discharge plasmas enable many stubborn reactions to occur under mild conditions,by creating locally intensified and highly reactive environments.This technology emerges as a novel,versatile technology platform for integrated or stand-alone conversion of carbon-rich resources.The plasma-based processes are compatible for integration with increasingly abundant and cost-effective renewable electricity,making the whole conversion carbon-neutral and further paving the plasma-electrified upcarbonization to be performance-,environment-,and economics-viable.Despite the chief interest in this emerging area,no review article brings together the state-of-the-art results from diverse disciplines and underlies basic mechanisms and chemistry underpinned.As such,this review aims to fill this gap and provide basic guidelines for future research and transformation,by providing an overview of the application of plasma techniques for carbon-rich resource conversion,with particular focus on the perspective of discharge plasmas,the fundamentals of why plasmas are particularly suited for upcarbonization,and featured examples of plasma-enabled resource valorization.With parallels drawn and specificity highlighted,we also discuss the technique shortcomings,current challenges,and research needs for future work.

An Intelligent Control Method for the Low-Carbon Operation of Energy-Intensive Equipment

Based on an analysis of the operational control behavior of operation experts on energy-intensive equipment,this paper proposes an intelligent control method for low-carbon operation by combining mechanism analysis with deep learning,linking control and optimization with prediction,and integrating decision-making with control.This method,which consists of setpoint control,self-optimized tuning,and tracking control,ensures that the energy consumption per tonne is as low as possible,while remaining within the target range.An intelligent control system for low-carbon operation is developed by adopting the end-edge-cloud collaboration technology of the Industrial Internet.The system is successfully applied to a fused magnesium furnace and achieves remarkable results in reducing carbon emissions.

Risk preferences and the low-carbon agricultural technology adoption:Evidence from rice production in China

Climate change which is mainly caused by carbon emissions is a global problem affecting the economic development and well-being of human society.Low-carbon agriculture is of particular significance in slowing down global warming and reaching the goal of“carbon peak and carbon neutrality”.Therefore,taking straw incorporation as an example,this paper aims to investigate the impact of risk preferences on farmers’low-carbon agricultural technology(LCAT)adoption.Based on a two-phase micro-survey data of 1038 rice farmers in Jiangsu,Jiangxi,and Hunan provinces,this paper uses experimental economics methods to measure farmers’risk aversion and loss aversion to obtain the real risk preferences information of the farmers.We also explore the data to examine the actual LCAT adoption behavior of farmers.The results revealed that both risk aversion and loss aversion significantly inhibit farmers’LCAT adoption:more risk-averse or more loss-averse farmers are less likely to adopt LCAT.It is further found that crop insurance,farm scale and governmental regulations can alleviate the negative impact of risk aversion and loss aversion on farmers’LCAT adoption.Therefore,we propose that local governments need to promote low-carbon agricultural development by propagating the benefits of LCAT,extending crop insurance,promoting appropriate scale operations,and strengthening governmental regulations to promote farmers’LCAT adoption.

A low-carbon economic dispatch model for electricity market with wind power based on improved ant-lion optimisation algorithm

Introducing carbon trading into electricity market can convert carbon dioxide into schedulable resources with economic value.However,the randomness of wind power generation puts forward higher requirements for electricity market transactions.Therefore,the carbon trading market is introduced into the wind power market,and a new form of low-carbon economic dispatch model is developed.First,the economic dispatch goal of wind power is be considered.It is projected to save money and reduce the cost of power generation for the system.The model includes risk operating costs to account for the impact of wind power output variability on the system,as well as wind farm negative efficiency operating costs to account for the loss caused by wind abandonment.The model also employs carbon trading market metrics to achieve the goal of lowering system carbon emissions,and analyze the impact of different carbon trading prices on the system.A low-carbon economic dispatch model for the wind power market is implemented based on the following two goals.Finally,the solution is optimised using the Ant-lion optimisation method,which combines Levi's flight mechanism and golden sine.The proposed model and algorithm's rationality is proven through the use of cases.

Cold plasma-activated Cu-Co catalysts with CN vacancies for enhancing CO_(2)electroreduction to low-carbon alcohol

Electrocatalytic CO_(2)reduction reaction to low-carbon alcohol is a challenging task,especially high selectivity for ethanol,which is mainly limited by the regulation of reaction intermediates and subsequent C–C coupling.A Cu-Co bimetallic catalyst with CN vacancies is successfully developed by H_(2)cold plasma toward a high-efficiency CO_(2)RR into low-carbon alcohol.The Cu-Co PBA-V_(CN)(Prussian blue analogues with CN vacancies)electrocatalyst yields methanol and ethanol as major products with a total low-carbon alcohol FE of 83.8%(methanol:39.2%,ethanol:44.6%)at-0.9 V vs.RHE,excellent durability(100 h)and a small onset potential of-0.21 V.ATR-SEIRAS(attenuated total internal reflection surface enhanced infrared absorption spectroscopy)and DFT(density functional theory)reveal that the steric hindrance of V_(CN)can enhance the CO generation from*COOH,and the C–C coupling can also be increased by CO spillover on uniformly dispersed Cu atoms.This work provides a strategy for the design and preparation of electrocatalysts for CO_(2)RR into low-carbon alcohol products and highlights the impact of catalyst steric hindrance to catalytic performance.

The Low-Carbon Transition of Energy Systems:A Bibliometric Review from an Engineering Management Perspective

As a major solution to climate change,the low-carbon transition of energy systems has received growing attention in the past decade.This paper presents a bibliometric review of the literature on the low-carbon transition of energy systems from an engineering management perspective.First,the definition and boundaries of the energy system transition are clarified,covering transformation of the energy structure,decarbonization of fossil fuel utilization,and improvement in energy efficiency.Second,a systematic search of the related literature and a bibliometric analysis are conducted to reveal the research trends.It is found that the number of related publications has been growing exponentially during the past decade,with researchers from China,the United Kingdom,the United States,Germany,and the Netherlands comprising the majority of authors.Related studies with interdisciplinary characteristics appear in journals focusing on energy engineering,environmental science,and social science related to energy issues.Four major research themes are identified by clustering the existing literature:(1)low-carbon transition pathways with different spatiotemporal scales and transition constraints;(2)low-carbon technology diffusion with a focus on renewable energy technologies,pollution control technologies,and other technologies facilitating the energy transition;(3)infrastructure network planning for energy systems covering various sectors and regions;and(4)transition-driving mechanisms from the political,economic,social,and natural perspectives.These four topics play distinct but mutually supportive roles in facilitating the low-carbon transition of energy systems,and require more in-depth research on designing resilient low-carbon transition pathways with coordinated goals,promoting low-carbon technologies with cost-effective and reliable infrastructure network deployment,and balancing multi-level risks in various systems.Finally,business models,nongovernment actors,energy justice,deep decarbonization,and zero-energy buildings are recognized as emerging hot topics.

Dynamic decision and its complex dynamics analysis of low-carbon supply chain considering risk-aversion under carbon tax policy

This study establishes a low-carbon supply chain game model under the centralized decision situation and the decentralized decision situation considering the manufacturer risk-aversion behavior, and discusses the influence of the manufacturer risk-aversion behavior on the optimal decision, profit, coordination, and complex dynamics of the supply chain. We find that comparing with the risk-neutral decentralized decision, the increase of manufacturer's risk tolerance attitude can narrow the gap between the supply chain profit and the centralized decision, but it will further reduce the carbon emission reduction level. The increase of risk tolerance of the manufacturer and carbon tax will narrow the stable region of the system. Under this situation, the manufacturer should carefully adjust parameters to prevent the system from losing stability,especially the adjustment parameters for carbon emission reduction level. When the system is in a chaotic state, the increase of carbon tax rate makes the system show more complex dynamic characteristics. Under the chaotic state, it is difficult for the manufacturer to make correct price decision and carbon emission reduction strategy for the next period, which damages its profit, but increases the profit of the retailer and the supply chain. Finally, the carbon emission reduction cost-sharing contract is proposed to improve the carbon emission reduction level and the supply chain efficiency, achieving Pareto improvement. The stability region of the system is larger than that in the centralized decision situation, but the increase of the cost sharing coefficient will reduce the stability of the system in the decentralized decision-making situation.

Core Competitiveness Construction of Clothing Brands in Low-Carbon Economy

The climate issue has become an environmental concern for all sectors of the world and the low-carbon economy has thus become a new economic development model to combat climate change.With the development of low-carbon economy era,the textile and clothing industry plays an important role in stabilizing the development of low-carbon economy and society,and China has put forward the development requirements of low-carbon transformation for the textile and clothing industry,and also it has an important strategic value to promote the high-quality development of low-carbon economy and society,and the construction of brands’ core competitiveness is an inevitable choice for clothing brands in the face of the new form of international competition.As a result,the evaluation indicator of clothing brands’ core competitiveness in the low-carbon economy is used to measure the core competitiveness of clothing brands.Based on the corresponding verification results obtained by analytic hierarchy process(AHP) analysis,it can guide the low-carbon development of the clothing industry,thus proposing a more reasonable way to build the core competitiveness of clothing brands.It can promote the low-carbon transformation and upgrading of the clothing industry,effectively increase the market share of clothing brands,and promote the high-quality development of clothing brands.

Application of Intuitionistic Z-Numbers in Supplier Selection

Intuitionistic fuzzy numbers incorporate the membership and non-membership degrees.In contrast,Z-numbers consist of restriction components,with the existence of a reliability component describing the degree of certainty for the restriction.The combination of intuitionistic fuzzy numbers and Z-numbers produce a new type of fuzzy numbers,namely intuitionistic Z-numbers(IZN).The strength of IZN is their capability of better handling the uncertainty compared to Zadeh's Z-numbers since both components of Z-numbers are charac-terized by the membership and non-membership functions,exhibiting the degree of the hesitancy of decision-makers.This paper presents the application of such numbers in fuzzy multi-criteria decision-making problems.A decision-making model is proposed using the trapezoidal intuitionistic fuzzy power ordered weighted average as the aggregation function and the ranking function to rank the alternatives.The proposed model is then implemented in a supplier selection problem.The obtained ranking is compared to the existing models based on Z-numbers.The results show that the ranking order is slightly different from the existing models.Sensitivity analysis is performed to validate the obtained ranking.The sensitivity analysis result shows that the best supplier is obtained using the proposed model with 80%to 100%consistency despite the drastic change of criteria weights.Intuitionistic Z-numbers play a very important role in describing the uncertainty in the decision makers’opinions in solving decision-making problems.

Impact of minimalism on consumers’ low-carbon innovation behavior: Interactive role of quantitative behavior

Minimalism has become a new consumer trend that can guide low-carbon innovation behaviors.This study uses two experiments and one survey to explore the mechanisms underlying the relationships among minimalism,quantitative behavior,and low-carbon innovation behavior.The results show that(1)minimalism can positively influence consumers’low-carbon innovation behavior;(2)the interactive effect of minimalist and quantitative behavior on low-carbon innovation behavior is significant;and(3)meaning in life can play a significant mediating role in the relationship between minimalism and low-carbon innovation behavior.Finally,corresponding strategies for theory and management practices are proposed.

Two-Stage Low-Carbon Economic Dispatch of Integrated Demand Response-Enabled Integrated Energy System with Ladder-Type Carbon Trading

Driven by the goal of“carbon neutrality”and“emission peak”,effectively controlling system carbon emissions has become significantly important to governments around the world.To this end,a novel two-stage low-carbon economic scheduling framework that considers the coordinated optimization of ladder-type carbon trading and integrated demand response(IDR)is proposed in this paper for the integrated energy system(IES),where the first stage determines the energy consumption plan of users by leveraging the price-based electrical-heat IDR.In contrast,the second stage minimizes the system total cost to optimize the outputs of generations with consideration of the uncertainty of renewables.In addition,to fully exploit the system’s emission reduction potential,a carbon trading cost model with segmented CO_(2) emission intervals is built by introducing a reward-penalty ladder-type carbon trading mechanism,and the flexible thermal comfort elasticity of customers is taken into account by putting forward a predicted mean vote index on the load side.The CPLEX optimizer resolves the two-stage model,and the study results on a modified IES situated in North China show the proposed model can effectively reduce carbon emissions and guarantee economical efficiency operation of the system.

China's low-carbon competitiveness and its effect decomposition from the perspective of wellbeing performance of ecological input

From the perspective of wellbeing performance of ecological input,this paper constructs a low-carbon competitiveness evaluation model with wellbeing performance of carbon emissions as the measurement standard,and uses the LMDI factor decomposition method to decompose the total effect of low-carbon competitiveness changes into technology effect and service effect.And then it conducts positive analysis and comparison of the low-carbon competitiveness and its effect contribution of G20 countries from1990 to 2018.The results are as follows:Firstly,in 2018,the UK,France,Argentina,Brazil,and Germany had higher low-carbon competitiveness.From 1990 to 2018,the low-carbon competitiveness of the UK,Turkey,Germany,Italy,and Brazil increase rapidly.Secondly,from 1990 to 2018,the total effect of low-carbon competitiveness of G20 member states was all positive,that is to say,the overall wellbeing performance of carbon emissions increased,technology effect and service effect are positive in 17 countries and negative in 2 countries respectively.Thirdly,China's low-carbon competitiveness is low,lacking static and dynamic advantages,although the technology effect is the highest,but the service effect is the lowest,resulting in a low total effect,which indicates that the wellbeing performance of economic growth is the main bottleneck of China's low-carbon development.Finally,the policy recommendations for China's future low-carbon transition and sustainable development are put forward.

不同集中度下供应商稳定性对公司债务融资成本的影响

近年来,上市公司供应商断供事件频发,对公司的经营管理产生了不可忽视的负面影响,引起了社会各界的广泛关注。基于此,从外部利益相关者债权人的视角,收集整理2008—2021年沪深A股804家上市公司2825个年度供应商稳定性数据,实证检验供应商稳定性对公司债务融资成本的影响及其机制。研究发现,供应商稳定性能够显著降低公司的债务融资成本,表明外部债权人更看好供应商关系稳定的公司。调节机制分析表明,较高的供应商集中度会削弱供应商稳定性对债务融资成本的降低效应。在采用替换变量、更换回归模型、赫克曼两步法、倾向得分匹配法进行稳健性检验后,以上结论仍然成立。从作用机制上看,供应商稳定性通过提升供应链效率降低债务融资成本。异质性分析发现,在大规模公司、行业市场竞争程度较强及地区市场化程度较高的公司样本中,供应商稳定性对债务融资成本的降低效应更显著。为更有效降低公司债务融资成本,公司应重视供应商的管理和维护,保持稳定的供应商关系,提高供应链效率;为充分发挥供应商稳定性对公司债务融资成本的降低效应,应将供应商集中度控制在合理水平;应实施差异化供应商管理策略,大规模公司、行业市场竞争较强及地区市场化程度较高的公司要高度重视供应商稳定性的促进作用,着力完善供应商关系管理,促使公司确定更合理的供应商稳定性水平。

客户资产减值与供应商企业投资

高效投资是产业链安全的重要保证,供应链信息溢出效应会导致客户信息对供应商企业投资产生影响。本文运用中国上市公司的供应商企业—客户关系数据,考察了客户资产减值如何影响供应商企业投资。研究发现,客户资产减值会降低供应商企业的投资水平,这验证了客户资产减值在供应链上存在溢出效应。进一步研究发现,客户资产减值通过使供应商企业的管理层产生悲观预期,以及加剧供应商企业的经营风险,进而降低供应商企业的投资水平,但未通过减少信贷资源供给影响供应商企业的投资。此外,对于非国有控股、较弱议价能力、较低行业资产流动性及较高客户媒体关注度的供应商企业,客户资产减值对其投资水平的负向影响更为明显。本文研究结论不仅为客户信息影响上游供应商企业投资提供了经验证据,而且还为监管层规范企业计提资产减值行为,进而提升供应链整体投资效率提供了政策启示。

网络嵌入与双元学习如何提升供应商创新性——一个模糊集定性比较分析

供应商创新性在推动供应链创新发展中发挥重要作用。既有文献侧重研究单个或多因素对供应商创新性的净效应,鲜有分析多因素对供应商创新性的协同效应。面对日益复杂和高度不确定的外部环境,需从整体角度探索供应商创新驱动路径。基于组态视角,采用模糊集定性比较分析方法(fsQCA),从网络嵌入和双元学习两个层面探讨4个前因条件对供应商创新性的联动效应及其作用路径。研究发现:关系嵌入、结构嵌入、利用式学习和探索式学习并不是构成企业提高或导致非高水平供应商创新性的必要条件,且单个前因条件对供应商创新水平的解释力较弱,提高供应商创新性的影响因素是多方面的;存在4条驱动供应商创新性的路径,即互动—学习模式、合作共创模式、学习驱动模式、探索-引领模式;导致非高水平供应商创新性的路径有2条,且与供应商创新性提升路径具有非对称性;网络嵌入与双元学习的合理匹配,对提升供应商创新性具有重要作用。研究结论不仅可深化供应链创新、网络嵌入和双元学习相关理论,而且可为提高供应商创新性、促进供应链创新发展提供借鉴。