Search

It has been clearly demonstrated that it would be feasible to consider recycling paper in an academic institution. This can be achieved through combining specific waste paper baskets, a pulping machine and power supplied by a renewable energy source, with an already established local paper making company. The paper making company would be able to gain a subsidy from the government which pays them to actually recycle paper, to counteract the cost of the pulped paper which is 30% more expensive than raw wood pulp. The academic institution would save money on waste disposal and decrease its carbon footprint by 600% with savings of up to around 5e6 tons of CO2 per year, instead of the 1e2 tones carbon offset for just recycling the paper normally. This entire process could be adapted for recycling the vast quantities of waste paper produced by students, an initiative which often fails due to the high cost of disposal. This could be achieved through urged use of the same paper disposal methods already in use, with the paper being collected and pulped once a week directly from the student paper waste bins. This research aims to study and limit the quantities of paper consumed in academic institutions in Iraq, by identifying the steps of recycling, and the extent of its environmental and economic impact, on the one hand, and on the other hand, the extent to which the Iraqi university community accepts this idea, and then study these quantities and evaluate them economically and find out the possibility of establishing a paper recycling plant based on these quantities. As well as the current research deals with the accumulation of paper waste caused by the performance of exams. In the third semester of the research, the amount of paper waste at Thi Qar University was calculated as a model for conducting a detailed research study of all departments and colleges of the University. the amount of paper waste was (11,055 tons/year), as well as calculating the cost of paper processing for the University amounted to (126252271 Iraqi dinars) and at the end of the third semester, the amount of paper waste in Iraqi academic institutions for the academic year 2022e2023, approximately (367,60976 tons/year). The cost of preparing exam books in Iraqi academic institutions for the academic year 2022e2023 amounted to approximately (4202150971 Iraqi dinars). The devices used in the practical aspect and each device and its purpose in the paper waste recycling process were explained. In addition, in the fourth chapter of the research, waste recycling was carried out in a practical way, and the results were satisfactory. We proposed a project to establish a paper and cardboard waste recycling plant in Nasiriyah, detailing its technical processes and stages in a mature way, the costs of establishing such projects in detail, as well as the annual profit of the project. At the conclusion of the research, some important recommendations were attached that help the paper waste recycling process and its success. [ABSTRACT FROM AUTHOR]

Paper mill sludge (PMS) is featured with a high content of cellulose and hemicellulose, and using its characteristics to make paperboard can achieve a high-value utilization of PMS, which has attracted growing interest. In this study, currently prevalent landfill, incineration technologies (generating heat and electricity by incineration), and three paperboard technologies (medium density fiberboard, pulp board, and corrugated paper) were evaluated and compared via life cycle assessment (LCA) and life cycle costing (LCC) methods. LCA results show that the PMS-to-pulp board outperforms others with an energy conservation and emission reduction (ECER) value of − 2.86 × 10−8, while the landfill exhibits the highest overall environmental impact with an ECER value of 4.80 × 10−9. LCC results reveal that the PMS-to-pulp board delivers the highest economic profit with $257.357, while the landfill is the lowest with $ − 35.63. The PMS paperboard technologies are more economically friendly than the incineration technologies due to additional electricity/steam consumption during the PMS pre-drying process in incineration. In addition, different scenarios were set up to explore national GHG emission reduction potential by increasing paperboard technologies application rate and reducing the proportion of landfill and incineration. The scenario analysis suggests that replacing 90% of landfill and incineration ratio with PMS paperboard technologies could tremendously improve the overall emission reduction performance with − 9.08 × 1010 kg CO2 eq. This result indicates that the PMS treatment technology transformation has a significant favorable impact on the achievement of the "carbon neutrality" target. [ABSTRACT FROM AUTHOR]

A text generation based multidisciplinary problem identification method is proposed, which does not rely on a large amount of data annotation. The proposed method first identifies the research objective types and disciplinary labels of papers using a text classification technique; second, it generates abstractive titles for each paper based on abstract and research objective types using a generative pre-trained language model; third, it extracts problem phrases from generated titles according to regular expression rules; fourth, it creates problem relation networks and identifies the same problems by exploiting a weighted community detection algorithm; finally, it identifies multidisciplinary problems based on the disciplinary labels of papers. Experiments in the "Carbon Peaking and Carbon Neutrality" field show that the proposed method can effectively identify multidisciplinary research problems. The disciplinary distribution of the identified problems is consistent with our understanding of multidisciplinary collaboration in the field. It is necessary to use the proposed method in other multidisciplinary fields to validate its effectiveness. Multidisciplinary problem identification helps to gather multidisciplinary forces to solve complex real-world problems for the governments, fund valuable multidisciplinary problems for research management authorities, and borrow ideas from other disciplines for researchers. This approach proposes a novel multidisciplinary problem identification method based on text generation, which identifies multidisciplinary problems based on generative abstractive titles of papers without data annotation required by standard sequence labeling techniques. [ABSTRACT FROM AUTHOR]

In order to address the planning problem of integrated energy system (IES) under the goal of "dual-carbon", this paper proposes a multi-objective planning method for IES with carbon trading mechanism based on CVaR (Conditional Value at Risk). Firstly, this paper establishes the IES energy supply equipment model and the improved stepped carbon trading model. Moreover, this paper proposes the IES multi-objective two-layer planning model based on the consideration of carbon trading cost. The upper layer of the planning model takes the optimization of economy and environmental as the goal to realize the rational planning of the integrated energy system. The lower layer model takes the minimum operating cost as the goal to optimize the system operating conditions and verify the rationality of the planning results. Then, the uncertainty model based on mean-CVaR is established for the uncertainty of carbon trading price and new energy output in the planning process. Finally, this paper sets up cases and solves the model using non-dominated sorting genetic algorithm-II (NSGA-II) and solver, which shows that the proposed method can realize the IES low-carbon planning while guaranteeing the economy. [ABSTRACT FROM AUTHOR]

Cities are the core carriers and key positions to achieve the dual carbon goals. It is of great significance to explore whether promoting urbanization can improve carbon emission performance, which is of great significance to comprehensively promote the goal of carbon neutrality. Based on the panel data from 2006 to 2021, this paper analyzes the spatial autocorrelation of carbon emission performance per unit space and the impact mechanism of urbanization process on it. The fixed-effect model was further used to identify the influencing factors of spatial carbon emission performance. The results show that: 1) China's carbon emission performance per unit space is declining year by year. 2) There is a strong positive spatial correlation and stable path dependence on the performance of carbon emissions per unit space in each region. 3) To a certain extent, increasing the level of urbanization will reduce the carbon emission performance per unit space. 4) The urbanization process has a spatial spillover effect on the carbon emission performance per unit space of surrounding provinces, and the spatial spillover effect of industrial structure and energy consumption structure is more obvious than that of economic level, population density and urbanization rate. Based on the conclusions, this paper puts forward specific policy suggestions to reduce the carbon emission performance per unit space to help the low-carbon development of cities. [ABSTRACT FROM AUTHOR]

Facing the double constraints of the "double carbon" target and high-quality economic development, carbon trading policy is an important tool for realizing the emission reduction commitment; based on the perspective of microenterprises, the specific mechanism and spatial effect of carbon trading policy still need to be evaluated. Taking China's carbon emissions trading pilot as a quasi-natural experiment, this paper empirically investigates the impact of carbon trading policy on the carbon emission intensity of pilot enterprises and its mechanism of action, and its impact on the carbon emission intensity of neighboring enterprises, based on the multi-temporal double-difference model, moderating effect model, and spatial Durbin model with the A-sharelisted enterprises in the period of 2009-2019 as the samples. It is found that: 1) Carbon trading policy will reduce the carbon emission intensity of enterprises to different degrees, and there are significant differences under different ownership types, degrees of marketization and the level of digitization. 2) Under the influence of environmental uncertainty, ESG disclosure will weaken the effectiveness of carbon emission reduction in the pre-pilot stage of the policy; with the gradual improvement of the carbon trading policy and ESG disclosure mechanism, ESG ratings will positively regulate the inhibitory effect of the carbon trading policy on the carbon emission intensity of enterprises through multiple paths. 3) Carbon trading policy effectively reduces multiple negative spillovers through the demonstration effect and competition effect of neighboring enterprises, driving the carbon emission reduction behavior of non-pilot enterprise. The research in this paper enriches the research paradigm of carbon emission intensity influencing factors, provides reference suggestions for the government to improve its policies, and better contributes to the realization of the "dual-carbon" vision in China as soon as possible. [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]

Particularly within recent years, the rising number of city actors worldwide declaring climate emergencies and pledging commitments to carbon neutrality has sparked a spatial turn in broader sustainable transition thinking, noting the importance of the local level for governing sustainable transitions. Using a Geographical Political Economy approach, this paper critically engages with path creation theory and sustainable transitions literature to explore the potential of urban net-zero carbon transitions in a multi-scalar governance framework. The main argument is that municipal ownership across sectors has a fundamental role in sustainable transitions at the city level. This paper makes a distinct conceptual contribution to sustainable transitions literature by drawing on path creation theory to illustrate how municipal ownership is a central tenet of path creation by bringing together local actors and enabling political capacity and agency to control and strategize integrated sustainable urban pathways. Using the transport and energy sectors in Nottingham in the UK, it applies the Path Creation Framework in an urban setting to illustrate that municipal ownership stimulates a positive path creation through three main arguments. First, municipal ownership enables a positive embeddedness and historical legacy in the provision of sustainable urban energy and transport services; second, it facilitates the establishment of skills and expertise that positively reinforces urban political capacity for the pursuit of urban sustainability; and third, it stimulates the creation of innovative urban projects for sustainable and equitable pathways. [ABSTRACT FROM AUTHOR]

This paper studies the optimal vehicle fleet planning and collaboration problem for a fuel vehicle (FV) transport service provider, a commercial electric vehicle (CEV) transport service provider, and a carbon emission treatment agency under carbon neutrality. The FV transport service provider pays a fixed fee or a portion of its sales revenue to a carbon emission treatment agency in exchange for technology to reduce its carbon emissions, and it can adopt three strategies (i.e., no emission reduction, purchasing technology for emission reduction, and entrusting a carbon emission treatment agency). We derive each party's optimal fleet size, price, and profit in the three scenarios. Our results suggest that carbon emission reduction strategies may improve the market performance of the FV transport service provider. Then, we find no certain strategy is always preferable to another: the optimal cooperation strategy between the transport service provider and carbon emission treatment agency depends on the fixed technology fee, ratio of revenue sharing, government penalty, the transport service market potential, and consumer green preference, as well as the cost per CEV. This paper gives the transport service provider and carbon emission treatment agency a full picture of whether, when, and how to collaborate in green commerce. [ABSTRACT FROM AUTHOR]

To advance carbon neutrality policies, many countries are increasingly integrating Renewable Energy Sources (RESs) into their energy mix. However, for harnessing natural energy in power generation, RESs present challenges in output control, potentially leading to power imbalances. Such imbalances, when coupled with an excessive reliance on unpredictable RES, may necessitate the curtailment of grid-integrated renewable generation, halting production despite available capacity. This paper proposes strategies to mitigate the economic and operational efficiency impacts of increased RESs on the power grid. It focuses on the optimal operation of Battery Energy Storage Systems (BESSs) and Power to Gas (P2G) technology, which flexibly converts surplus electricity into hydrogen. By employing Mixed Integer Linear Programming (MILP) for optimization and Stochastic Programming (SP) for the management of the uncertainty of renewable energy output, this paper evaluates the anticipated benefits of BESS and P2G applications. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to answer three questions: (1) Which countries invest more capital in green firms? (2) What kind of industries do venture capitals (VCs) invest in? (3) Do VCs invest more capital in green firms? Design/methodology/approach: First, the authors provide summary statistics of the key variables for green and non-green firms. Then the authors use figures to plot the growth of green firms over time. Next, the authors use descriptive data to study VC-invested firms for the top 10 countries and industries for all firms, green firms and non-green firms. Finally, the authors compare the VC investors' characteristics and investment behavior between green and non-green firms. Findings: This study documents that venture-backed investments in clean technologies have increased dramatically in the number of deals and in the total amount of dollar volume over time. This paper provides evidence that VC firms invest more in green firms in each deal than in non-green firms. The United States and European countries play an important role in funding clean technologies across countries, and this study's results suggest that VC investors play a considerable role in shaping the development of green finance. Originality/value: This paper makes the first attempt to investigate the role of VCs in clean technologies to support carbon neutrality, providing initial evidence on venture capitalists' investment efforts towards carbon neutrality. The paper also has practical implications for start-up firms that raise capital and venture capitalists who finance green start-ups. [ABSTRACT FROM AUTHOR]

Under the goal of "achieving carbon peak by 2030 and carbon neutrality by 2060", how to select the type of fresh air system has become a key area of energy conservation. The method of outdoor design PM2.5 concentration is one of the important factors affecting the selection of fresh air filtration system. This paper first analyzed the PM2.5 concentration values of 31 cities in China from 2017 to 2020 based on mathematical induction, and next gave the recommended coefficient K under six urban economic regions methods in combination with the actual situation. Finally, the selection of air filters in five typical cities was taken as an example, the differences in recommended coefficient K and selection of outdoor design PM2.5 concentration under different recommended methods were compared and analyzed. The results showed that the recommended coefficient K under the six economic regions could meet the required K value needs of the region. The recommended coefficient K by the six economic regions methods based on per capita GDP is the best. Under that conditions, the recommended coefficient K of the five typical cities under strict and normal conditions differs from the average K values of the six methods by 0.06 and 0.04. This paper will provide a new method for the correct selection of outdoor design PM2.5 concentration in fresh air systems to achieve the dual carbon energy-saving goal. [ABSTRACT FROM AUTHOR]

Corporate carbon emissions accounting has become a research focus for researchers and government departments. Based on corporate production processes, this study proposes and establishes a comprehensive system for corporate carbon emissions. Taking Stora Enso (Guangxi) Company as an example, this paper provides a thorough analysis of the production and operational status of paper-making companies. The production process is divided into five stages: material preparation, pulping, pulp board production, papermaking, and alkali recycling. Based on these production processes, it proposes and constructs a corporate carbon emissions accounting system from an accounting perspective, which specifically includes accounting objectives, information quality characteristics, accounting recognition, accounting measurement, accounting treatments, and information disclosure. The findings show that the carbon emissions accounting system targeted at production processes can clearly awaken corporate carbon emissions responsibilities, further improve the corporate accounting system, and provide effective technical support for the government to implement environmental regulations and formulate carbon reduction policies. [ABSTRACT FROM AUTHOR]

Green and low carbon reflect the high-quality development, while income distribution is an indicator of the balance of development. Is there a lack of fairness in the process of green and low carbon transition of enterprises? Using data from A-share listed companies from 2009 to 2016, this paper constructs a DID identification framework for controlling the endogeneity problem using the 2013 carbon trading policy pilot as a quasi-natural experiment to empirically test the impact of corporate low-carbon transformation on corporate labor income share in the context of carbon trading policy. The findings indicate that carbon trading policy decreases the labor income share of firms. In addition, we demonstrate that the low-carbon transition promotes labor productivity, suggesting that the Porter's hypothesis is confirmed in China, but the increase in labor wages is not in tandem with productivity growth, resulting in reduced labor income share. Heterogeneity analysis shows that the impact of carbon trading policy on labor income share is mainly pronounced in larger firms, high technology firms and persistent incumbent firms. Collectively, these results are expected to accurately improve our understanding on the impact of low-carbon transformation of enterprises on income distribution and provide reference for the government to formulate industrial policies and distribution mechanisms under low-carbon economy. [ABSTRACT FROM AUTHOR]

Purpose: The research objective of this paper is to investigate the direct and indirect impacts of green finance on agricultural carbon total factor productivity (ACTFP) within the framework of the carbon peaking and carbon neutrality (dual carbon) goals, while also identifying the driving factors through an exponential decomposition of ACTFP, aiming to provide policy recommendations to enhance financial support for low-carbon agricultural development. Design/methodology/approach: In this paper, the Global Malmquist Luenberger (GML) Index method was employed to analyze and decompose the ACTFP, while the direct and spillover effects of China's green finance pilot policy (GFPP) on ACTFP were assessed using the difference-in-differences (DID) method and the spatial differences-in-differences (SDID) method, respectively. Findings: After the implementation of the GFPP, the ACTFP in the pilot area has experienced significant improvement, with the enhancement of technical efficiency serving as the main driving force. In addition, the GFPP exhibits a positive low-carbon spatial spillover effect, indicating it benefits ACTFP in both the pilot and adjacent areas. Originality/value: Within the framework of the dual carbon goals, the paper highlights agriculture as a significant carbon emitter. ACTFP is assessed by considering the agricultural carbon emission factor as the sole non-desired output, and the impact of the GFPP on ACTFP is investigated through the DID method, thereby providing substantial validation of the hypotheses inferred from the mathematical model. Subsequently, the spillover effects of GFPP on ACTFP are analyzed in conjunction with the spatial econometric model. [ABSTRACT FROM AUTHOR]

With the goal of "carbon peak and carbon neutrality," the need for environmentally friendly gases to replace SF6, a high greenhouse effect gas, is urgent. C4F7N, as an environmentally friendly gas with the greatest potential to replace SF6 as an arc extinguishing medium in circuit breakers, can be mixed with CO2 to greatly improve the shortcomings of its high liquefaction temperature, and the calculation of the physical parameters of the mixed gas plasma is a prerequisite for the computational simulation of the arc process in the opening of circuit breakers. Because solving the physical parameters is expensive, based on the system of differential equations, this paper adopts several machine learning algorithms by mining the relationship between the data using the known physical parameter data to predict the results of the physical parameters to be solved under certain conditions, which greatly reduces the cost of computation. The machine learning algorithms used in this paper are K-nearest-neighbor regression, decision tree, random forest, support vector machine, and gradient boosting regression, of which for the support vector machine, hyperparameters find it difficult to determine the problem of optimization using the gray wolf algorithm. The prediction results of several algorithms show that they are more accurate and that the problem can be solved better by using the method of machine learning. Finally, the comparison results show that the support vector machine exhibits better performance in most cases and that the gray wolf algorithm can make the results of the support vector machine more accurate. [ABSTRACT FROM AUTHOR]

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

Carbon Capture, Utilization, and Storage (CCUS) stands as one of the effective means to reduce carbon emissions and serves as a crucial technical pillar for achieving experimental carbon neutrality. CO2-enhanced oil recovery (CO2-EOR) represents the foremost method for CO2 utilization. CO2-EOR represents a favorable technical means of efficiently developing extra-low-permeability reservoirs. Nevertheless, the process known as the direct injection of CO2 is highly susceptible to gas scrambling, which reduces the exposure time and contact area between CO2 and the extra-low-permeability oil matrix, making it challenging to utilize CO2 molecular diffusion effectively. In this paper, a comprehensive study involving the application of a CO2 nanobubble system in extra-low-permeability reservoirs is presented. A modified nano-SiO2 particle with pro-CO2 properties was designed using the Pickering emulsion template method and employed as a CO2 nanobubble stabilizer. The suitability of the CO2 nanobubbles for use in extra-low-permeability reservoirs was evaluated in terms of their temperature resistance, oil resistance, dimensional stability, interfacial properties, and wetting-reversal properties. The enhanced oil recovery (EOR) effect of the CO2 nanobubble system was evaluated through core experiments. The results indicate that the CO2 nanobubble system can suppress the phenomena of channeling and gravity overlap in the formation. Additionally, the system can alter the wettability, thereby improving interfacial activity. Furthermore, the system can reduce the interfacial tension, thus expanding the wave efficiency of the repellent phase fluids. The system can also improve the ability of CO2 to displace the crude oil or water in the pore space. The CO2 nanobubble system can take advantage of its size and high mass transfer efficiency, among other advantages. Injection of the gas into the extra-low-permeability reservoir can be used to block high-gas-capacity channels. The injected gas is forced to enter the low-permeability layer or matrix, with the results of core simulation experiments indicating a recovery rate of 66.28%. Nanobubble technology, the subject of this paper, has significant practical implications for enhancing the efficiency of CO2-EOR and geologic sequestration, as well as providing an environmentally friendly method as part of larger CCUS-EOR. [ABSTRACT FROM AUTHOR]

The integrated energy system considering comprehensive demand response can realize cascade utilization of energy and reduce carbon emissions. However, few studies explore the operation of Integrated energy system considering the coupling markets of electricity and carbon trading. Based on the characteristics and specific needs of the integrated energy system, this paper establishes the mathematical model of each energy supply equipment, and studies the optimal energy supply method of the system. First, demand response is categorized into price and substitution types based on load response characteristics. Second, the price demand response models are established utilizing the price elasticity matrix, and substitution demand response models are developed considering the mutual conversion of electric and heat energy on the user-side. Subsequently, a baseline method is employed to allocate carbon emission quotas to the system without charge with considering the actual carbon emissions from gas turbines and gas boilers. This results in the formulation of an improved carbon trading mechanism tailored for integrated energy system. Finally, a low-carbon optimization operational model for integrated energy system is constructed with the multi-objective functions. The results of numerical case studies are presented to validate the performance of the proposed control method. [ABSTRACT FROM AUTHOR]

Blue Carbon is increasingly popular worldwide, and it also belongs to circular economy field which would last a long period in academy. To further understand the development and characteristics of Blue Carbon, this study uses CiteSpace software to perform quantitative analysis on literature published on Web of Science and Chinese CNKI database with the main topic of "Blue Carbon." The results show that: (1) Since 2009, increasing attention has been paid to Blue Carbon research, among which the United States, Australia and China are the leading countries. (2) Keywords such as "Blue Carbon," "mangrove," "carbon sequestration" and "carbon neutrality" are the high-frequency keywords appearing both in China and the World in recent years. (3) Spartina alterniflora, soil organic carbon, livestock, trophic cascade, biodiversity and seagrass ecosystem clustering are hot topics related to international Blue Carbon research, while organic carbon, seagrass-conservation, methodology, sustainable development, climate change, carbon neutralization, coastal zone and carbon storage are hot topics related to Chinese Blue Carbon research. In addition, based on the research trends of Blue Carbon, this paper attempts to sort out the research framework from three levels: core characteristics, theoretical basis and research methods, respectively. Facing a series of challenges brought by climate change, Blue Carbon research should strengthen the accurate estimations of Blue Carbon sink and its market potential, and explore the reasonable market mechanism and protection mechanism, to respond to realistic demands, solve major concerns and promote new progress in Blue Carbon theory and practice. [ABSTRACT FROM AUTHOR]

On the basis of "Carbon Peak and Carbon Neutral" goals, carbon sequestration projects are increasing in China. The integrity of cement sheaths, as an important factor affecting carbon sequestration projects, has also received more attention and research. When CO2 is injected into the subsurface from sequestration wells, the cement sheath may mechanically fail due to the pressure accumulated inside the casing, which leads to the sealing of the cement sheath failing. The elasticity and strength parameters of the cement sheath are considered in this paper. The critical bottom-hole injection pressures of inclined well sections under anisotropic formation stresses at different depths were calculated for actual carbon-sealing wells in the X block—the CO2 sequestration target block. The sensitivity factors of the critical bottom-hole injection pressure were also analyzed. It was found that the cement sheath damage criterion was tensile damage. The Young's modulus and tensile strength of the cement sheath are the main factors affecting the mechanical failure of the cement sheath, with Poisson's ratio having the second highest influence. An increase in the Young's modulus, Poisson's ratio, and tensile strength of the cement sheath can help to improve the mechanical stability of cement sheaths in CO2 sequestration wells. This model can be used for the design and evaluation of cement in carbon sequestration wells. [ABSTRACT FROM AUTHOR]

Data centers are a major source of carbon emissions and are subsequently contributing to global carbon footprints. Keeping in view of providing a sustainable solution to society, we have analyzed various factors that can help to achieve carbon neutrality and maximum sustainability. Our study pointed towards the need to follow a sustainable approach for incoming workflow throughout the life-cycle of Data centers. We analyzed that workloads need to be segregated before assigning them to the data centers so that energy-efficient resource allocation could be done. This paper demonstrates unsupervised learning techniques to cluster the incoming cloud workloads. The heterogeneous workloads were characterized using machine learning approaches and appropriate clusters were crafted. For analysis, Google Cluster Dataset is used. In order to improve the accuracy, data were normalized, and random samples of data were selected for clustering. The machine learning algorithms applied were able to successfully determine the appropriate clusters that can further be used for energy-efficient resource scheduling. [ABSTRACT FROM AUTHOR]

As the severity of global climate change escalates, carbon peak and carbon neutrality have emerged as international imperatives. Green taxation, a crucial fiscal strategy promoting the transition to a green low-carbon economy, demands thorough investigation regarding its efficacy and operational mechanisms. Predominantly, existing research has concentrated on the macroeconomic implications of green taxes, while their influence on regional green growth and innovation remains underexplored. This paper delineates green taxation in both a broad and narrow sense, elucidating its essence and potential in stimulating regional green progress and innovation. Utilizing panel data from 30 provinces in China spanning 2004 to 2021, a bidirectional fixed-effects model was developed for empirical analysis. Moreover, an impact mechanism model was constructed to delve into how green taxation specifically affects regional green development and innovation. Findings reveal that green taxation significantly fosters regional green growth and markedly enhances green innovation. Nonetheless, due to the resource crowding-out effect, it adversely impacts the comprehensive innovation capabilities of regional enterprises. This insight offers a fresh perspective on the paradoxical effects of green taxation, underscoring the necessity for a balanced approach in policy design and implementation. Drawing on these conclusions, the paper presents tailored policy recommendations. [ABSTRACT FROM AUTHOR]

The accountability audit of natural resources (AANR) is a major institutional arrangement for advancing the construction of an ecological civilization in China. Based on the panel data of 271 cities in China from 2005 to 2017, this paper investigates the relationship between the AANR and carbon dioxide (CO2) emissions using a multi-period difference-in-differences (DID) model. The results show that AANR significantly increases the CO2 emission reduction rate by 0.009 units at the 5% significance level. The results still hold after a series of robustness tests. Given all else being equal, this significant effect is 0.001. Further analyses show that AANR improves pilot cities' CO2 emission reduction rates mainly by enhancing their green innovation capability. The mediating effect of cities' green technology innovation capability accounts for 96.00%, while the AANR's direct effect only accounts for 4.00%. The AANR has significantly positive effects of 0.017% and 0.029% for western cities and cities with high fiscal pressure at the 5% and 1% significance levels, respectively. Therefore, strengthening AANR implementation by enhancing the mediating efficiency of cities' green technology innovations and implementing dynamically differentiated AANR policies in Chinese meso-cities will contribute to the achievement of China's carbon peaking and carbon neutrality targets. [ABSTRACT FROM AUTHOR]

Through extensive data research and analysis, this paper comprehensively summarizes the status and key insights of global carbon dioxide capture and storage (CCS) development. It aims to gain a comprehensive understanding of the relevant policies, technologies, and security measures adopted by major countries in their CCS development processes. Furthermore, it explores the existing status and limitations of China's offshore development efforts, while providing valuable recommendations for enhancing China's offshore CCS initiatives, as well as serving as a reference for other nations worldwide. Offshore CCS plays a crucial role for China to achieve the development target of carbon peak and carbon neutrality, due to its energy structure and industrial distribution. While China possesses significant offshore CCS potential, achieving commercialization still requires substantial efforts. To facilitate the process and draw insights from successful experiences in other countries, this paper illustrates the characteristics and generalizes the experience of offshore CCS industry practices in America, Europe and Japan, respectively. Furthermore, it is recommended that a new round of investigation into offshore CCS potential be conducted, while promoting integrated collaboration between geological surveying and marine scientific research. Additionally, further research on industrial policies and green financial strategies should be undertaken. [ABSTRACT FROM AUTHOR]

Climate change imposes tighter limits on carbon emissions, which require the development of more green electricity. Deep sea wind power has the advantages of high wind energy density, high power generation utilization hours, no land occupation, and near to power load centers for easy on-site consumption, which lead to a broad market prospect. In the foreseeable future, deep sea wind power will usher in large-scale construction and development. The initial investment and construction cost of deep sea wind power is high, subsidies are gradually decreasing, and there is a lack of full life cycle economic analysis combined with various market policies, resulting in a lack of guidance for its investment and construction. In order to promote the development of deep sea wind power, relevant cost recovery mechanisms must be found. This paper proposes a system cost allocation method based on the comparative difference method and load similarity with consideration of the transformation and operation costs of thermal power, demand-side response, and energy storage; a cost allocation method based on carbon trading and green certificate trading income is proposed; and a time sequence optimization operation simulation model is established to maximize the deep sea wind power income. A case study is proposed for a 300 MW deep sea wind farm, the results show that the cost allocation method and cost allocation model proposed in this paper have a significant effect on wind power cost recovery, and the effectiveness of the proposed method and model is verified. [ABSTRACT FROM AUTHOR]

To fully explore the potential low-carbon and economic advantages of a virtual power plant (VPP) that aggregates multiple distributed resources, the paper proposes a VPP scheduling model that considers the carbon emission flow (CEF) and demand response (DR), which is characterized by electro-carbon coupling and source-load interaction. First, the electric-carbon characteristics of each distributed resource under VPP are modeled, and the source-load electric-carbon coupling characteristic model is modeled through the CEF theory. On this basis, a load-side multi-type DR model is established to achieve the purpose of source-load synergy to reduce carbon emissions from VPP. To this end, a two-stage scheduling model of VPP considering the source- load electro-carbon coupling relationship is established, and the implementation of the model can reduce power generation costs, carbon emissions and promote clean energy, and the simulation results of the improved IEEE-14 node system verify the effectiveness of the proposed model. [ABSTRACT FROM AUTHOR]

The paper addresses the imperative of empowering enterprises to achieve energy savings and emission reductions through digital development amidst the backdrop of peak carbon dioxide emissions and carbon neutrality. This study integrates digital empowerment and enterprise carbon risk management into a unified analytical framework, utilising panel data from listed companies spanning from 2011 to 2020 as research samples. The empirical investigation aims to ascertain whether there exist carbon risks impacting the operational performance of manufacturing enterprises and whether digital empowerment can mitigate these risks. The findings reveal that carbon intensity exerts an inhibitory influence on the enhancement of enterprise performance, indicating the presence of carbon risk issues faced by enterprises. Furthermore, it is observed that these carbon risk challenges escalate over time, a trend supported by robustness tests. Digital empowerment emerges as an effective mechanism in slowing down the carbon risks encountered by enterprises, albeit exhibiting characteristics of time lag. The study identifies notable heterogeneity in the role of digital empowerment in mitigating the carbon risks of enterprises. [ABSTRACT FROM AUTHOR]

With the shortage of fossil energy and the increasingly serious environmental problems, renewable energy based on wind and solar power generation has been gradually developed. For the problem of wind power uncertainty and the low-carbon economic optimization problem of an integrated energy system with power to gas (P2G) and carbon capture and storage (CCS), this paper proposes an economic optimization scheduling strategy of an integrated energy system considering wind power uncertainty and P2G-CCS technology. Firstly, the mathematical model of the park integrated energy system with P2G-CCS technology is established. Secondly, to address the wind power uncertainty problem, Latin hypercube sampling (LHS) is used to generate a large number of wind power scenarios, and the fast antecedent elimination technique is used to reduce the scenarios. Then, to establish a mixed integer linear programming model, the branch and bound algorithm is employed to develop an economic optimal scheduling model with the lowest operating cost of the system as the optimization objective, taking into account the ladder-type carbon trading mechanism, and the sensitivity of the scale parameters of P2G-CCS construction is analyzed. Finally, the scheduling scheme is introduced into a typical industrial park model for simulation. The simulation result shows that the consideration of the wind uncertainty problem can further reduce the system's operating cost, and the introduction of P2G-CCS can effectively help the park's integrated energy system to reduce carbon emissions and solve the problem of wind and solar power consumption. Moreover, it can more effectively reduce the system's operating costs and improve the economic benefits of the park. [ABSTRACT FROM AUTHOR]

The energy saving and emissions reduction of the construction industry are crucial for China to achieve the "carbon peaking and carbon neutrality" goals. In order to promote the green development of the life cycle of the construction industry and improve the efficiency of emissions reduction. This paper examines the spatial-temporal distribution of life cycle carbon emissions in China's construction industry (LCCECI) from 2004 to 2018. It uses the SBM-Malmquist total factor productivity (TFP) index to measure technological progress and establishes the spatial econometric model based on the STIRPAT model. The study investigates the driving factors of the LCCECI at the provincial and regional levels, aiming to provide suggestions for low-carbon development in the construction industry. The research results are as follows. © The growth in the SBM-Malmquist TFP index of the construction industry distinctly curbs the LCCECI. © Total population and urbanization level are not the primary driving factors for the LCCECI. The growth of per capita GDP significantly induces the LCCECI, while concurrently exhibiting a notable inhibitory effect on the LCCECI of neighboring regions. © The improvement of the SBM-Malmquist TFP index is conducive to the reduction of the LCCECI in the three major regions. The per capita GDP has the largest positive driving effect of the LCCECI in the eastern region, and the urbanization level the urbanization rate only significantly inhibits the growth of the LCCECI in the central region. [ABSTRACT FROM AUTHOR]

Introduction: With the development of the energy market and the gradual rise of emerging market players, the linkage of interests between energy sources and loads in the Integrated Energy System (IES) has become increasingly complex. Additionally, the reliability of the system has been impacted by the growing proportion of renewable energy output. Methods: To address the challenges posed by the above issues. This paper first proposes an operational strategy for an integrated energy system that incorporates the uncertainty of wind and solar output using a master-slave game approach. To enhance system robustness and cost-effectiveness, the paper introduces the information gap decision theory (IGDT). Second, building on this foundation, the system operator is considered as the leader, adding a tiered carbon trading mechanism and cloud energy storage system, and building a system revenue maximization model. Then, the user is regarded as the follower, and an optimization model is developed based on integrated demand response (IDR). Finally, the two-layer model is converted into a mixed-integer linear programming problem (MILP) to be solved by the Karush-Kuhn-Tucker conditions (KKT) combined with the big M method. Results: The analysis of the example shows that according to the difference of the decision maker's attitude towards risk, different scheduling schemes can be obtained through the two perspectives of risk-seeking and risk-avoiding, which can provide guidance for the dynamic operation of the system, and at the same time, the users can be guided by the energy differentials to reasonably use the energy under this strategy. Discussion: Therefore, the proposed strategy in this paper can balance the economy and robustness of the system. [ABSTRACT FROM AUTHOR]

Integrated energy system is crucial in realizing China's "dual carbon" targets. Considering the carbon capture based electricity to gas and the interaction of multiple markets, this paper proposes a low-carbon operation optimization method of integrated energy system. In terms of market policy, a coupling trading mechanism for carbon trade and green certificates is established. This approach is intended to delve into the profound significance of utilizing green certificates in carbon emission reduction. In terms of equipment models, the coupling model of carbon capture equipment with coal-fired cogeneration unit, as well as power-to-gas equipment with renewable energy, is constructed. In addition, this equipment model is introduced into the operation optimization scheduling of the comprehensive energy systems. A low-carbon economic operational strategy is further proposed to minimize the daily operational costs, by which the integrated energy system is eco-nomically, environmental protection optimized. To verify the effectiveness and feasibility of the proposed model, this paper sets up several comparison scenarios and conducts the simulations using GUROBI solver. The results show that the proposed strategy can effectively improve the uptake rate of renewable energy, reduce the carbon emission, improve the operation economy, and realize the complementary incentive effect between markets. [ABSTRACT FROM AUTHOR]

The worsening of climate conditions is closely related to the large amount of carbon dioxide produced by human use of fossil fuels. Under the guidance of the goal of "carbon peaking and carbon neutrality goals", with the deepening of the structural reform of the energy supply side, the hybrid energy system coupled with renewable energy has become an important means to solve the energy problem. This paper focuses on the comprehensive evaluation of hybrid energy systems. A complete decision support system is constructed in this study. The system primarily consists of four components: 1) Twelve evaluation criteria from economic, environmental, technological, and socio-political perspectives; 2) A decision information collecting and processing method in uncertain environment combining triangular fuzzy numbers and hesitation fuzzy language term sets; 3) A comprehensive weighting method based on Lagrange optimization theory; 4) Solution ranking based on the fuzzy VIKOR method that considers the risk preferences of decision-makers. Through a case study, it was found that the four most important criteria are investment cost, comprehensive energy efficiency, dynamic payback period and energy supply reliability with weights of 7.21%, 7.17%, 7.17%, and 7.15% respectively. A1 is the scheme with the best comprehensive benefit. The selection of solutions may vary depending on the decision-maker's risk preference. Through the aforementioned research, the decision framework enables the evaluation of the overall performance of the system and provides decision-making references for decision-makers in selecting solutions. [ABSTRACT FROM AUTHOR]

Copyright of Low-Carbon Materials & Green Construction is the property of Springer Nature 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.)

The electric power sector is the primary contributor to carbon emissions in China. Considering the context of dual carbon goals, this paper examines carbon emissions within China's electricity sector. The research utilizes the LMDI approach for methodological rigor. The results show that the cumulative contribution of economies scale, power consumption factors and energy structure are 114.91%, 85.17% and 0.94%, which contribute to the increase of carbon emissions, the cumulative contribution of power generation efficiency and ratio of power dissipation to generation factor are -19.15% and -0.01%, which promotes the carbon reduction. The decomposition analysis highlights the significant influence of economic scale on carbon emissions in the electricity industry, among the seven factors investigated. Meanwhile, STIRPAT model, Logistic model and GM(1,1) model are used to predict carbon emissions, the average relative error between actual carbon emissions and the predicted values are 0.23%, 8.72% and 7.05%, which indicates that STIRPAT model is more suitable for medium- to long-term predictions. Based on these findings, the paper proposes practical suggestions to reduce carbon emissions and achieve the dual carbon goals of the power industry. [ABSTRACT FROM AUTHOR]

Low carbon operation of power systems is a key way to achieve the goal of energy power carbon peaking and carbon neutrality. In order to promote the low carbon transition of energy and power and the coordinated and optimized operation of distributed energy sources in virtual power plants (VPP), this paper proposes a framework for collaborative utilization of pumped storage–carbon capture–power-to-gas (P2G) technologies. It also constructs a multi-time scale low carbon economic dispatch model for VPP to minimize the internal resource operation cost of VPP in each time period. During the intraday scheduling stage, the day-ahead scheduling results as the planned output and the energy flow is then dynamically corrected at a short-term resolution in the framework. This allows for the exploration of the low-carbon potential of each aggregation unit within the virtual power plant. The results of the simulation indicate that the strategy and model proposed in this paper can effectively encourage the consumption of renewable energy sources, promote the low-carbon operation of power system power, and serve as a valuable reference for the low-carbon economic operation of the power system. [ABSTRACT FROM AUTHOR]

Typical public institutions such as government offices, hospitals, and schools play important leading and exemplary roles in the green and low-carbon development of the whole society. This paper analyzes the business and energy consumption characteristics of public institutions, as well as the characteristics of personnel travel, and constructs a carbon accounting model for public institutions. It innovatively proposes a methodology for carbon accounting of personnel travel related to public institutions and validates and analyzes it using a comprehensive hospital as an example. The paper analyzes the carbon emission characteristics of various energy types, systems, and types of travelers in hospitals, provides schemes for the transformation of main energy systems, and corresponding emission reduction effects, thereby providing technical support for the full-chain carbon accounting of public institutions. Additionally, this paper explores the carbon reduction pathways for hospitals to support the peak carbon and carbon neutrality goals of public institutions, and promote the high-quality development of public institutions in China. [ABSTRACT FROM AUTHOR]

Accurately identifying changes in carbon trading prices can provide reasonable reference indicators for a government's macrocontrol and can also help companies more effectively avoid risks brought by carbon emissions and increase the income of carbon assets. Based on the Prophet model, LSTM neural network model, and backpropagation (BP), this paper proposes a method to predict carbon trading prices using the ensemble learning model and uses the Hubei carbon trading market data to predict carbon trading prices. Results show that in terms of accuracy, the Prophet-LSTM-BP ensemble learning model achieves better predictive ability than existing models; its RMSE, MAE, and MAPE are 1.479, 0.951, and 2.135, respectively, which are markedly smaller than the Prophet model's 5.631, 4.471, and 9.661, and the LSTM model's 3.352, 3.105, and 6.880, respectively. Compared with the traditional time series ARIMA model, the MAPE of ARIMA reaches 12.933, which is nearly 1.5 times that of the Prophet model, nearly 2 times that of the LSTM model, and nearly 7 times that of the ensemble learning model. In terms of applicability, when the model is applied to the national carbon trading market, the difference in MAPE compared with the Hubei carbon trading market is only 0.6%, and the other parameters are not more than 16%. The model improves the relevant research on carbon trading price predicting, and concurrently, this method provides ideas for carbon trading price predicting in other carbon trading markets and promotes the sustainable development of the national carbon trading market. [ABSTRACT FROM AUTHOR]

In order to improve the consumption of renewable energy and reduce the carbon emissions of integrated energy systems (IESs), this paper proposes an optimal operation strategy for an integrated energy system considering the coordination of electricity and hydrogen in the context of carbon trading. The strategy makes full use of the traditional power-to-gas hydrogen production process and establishes a coupling model comprising cogeneration and carbon capture equipment, an electrolytic cell, a methane reactor, and a hydrogen fuel cell. Taking a minimum daily operating cost and minimal carbon emissions from the system as objective functions, a mixed-integer nonlinear optimal scheduling model is established. This paper designs examples based on MATLAB R2021b and uses the GUROBI solver to solve them. The results show that compared with the traditional two-stage operation process, the optimization method can reduce the daily operation cost of an IES by 26.01% and its carbon emissions by 90.32%. The results show that the operation mode of electro-hydrogen synergy can significantly reduce the carbon emissions of the system and realize a two-way flow of electro-hydrogen energy. At the same time, the addition of carbon capture equipment and the realization of carbon recycling prove the scheduling strategy's ability to achieve a low-carbon economy of the scheduling strategy. [ABSTRACT FROM AUTHOR]

Solid-state hydrogen storage technology has emerged as a disruptive solution to the "last mile" challenge in large-scale hydrogen energy applications, garnering significant global research attention. This paper systematically reviews the Chinese research progress in solid-state hydrogen storage material systems, thermodynamic mechanisms, and system integration. It also quantitatively assesses the market potential of solid-state hydrogen storage across four major application scenarios: on-board hydrogen storage, hydrogen refueling stations, backup power supplies, and power grid peak shaving. Furthermore, it analyzes the bottlenecks and challenges in industrialization related to key materials, testing standards, and innovation platforms. While acknowledging that the cost and performance of solid-state hydrogen storage are not yet fully competitive, the paper highlights its unique advantages of high safety, energy density, and potentially lower costs, showing promise in new energy vehicles and distributed energy fields. Breakthroughs in new hydrogen storage materials like magnesium-based and vanadium-based materials, coupled with improved standards, specifications, and innovation mechanisms, are expected to propel solid-state hydrogen storage into a mainstream technology within 10–15 years, with a market scale exceeding USD 14.3 billion. To accelerate the leapfrog development of China's solid-state hydrogen storage industry, increased investment in basic research, focused efforts on key core technologies, and streamlining the industry chain from materials to systems are recommended. This includes addressing challenges in passenger vehicles, commercial vehicles, and hydrogen refueling stations, and building a collaborative innovation ecosystem involving government, industry, academia, research, finance, and intermediary entities to support the achievement of carbon peak and neutrality goals and foster a clean, low-carbon, safe, and efficient modern energy system. [ABSTRACT FROM AUTHOR]

In this paper, we develop a two-level supply chain model with low carbon emissions for defective deteriorating items under learning in fuzzy environment by using the double inspection process. Carbon emissions are a major issue for the environment and human life when they come from many sources like different kinds of factories, firms, and industries. The burning of diesel and petrol during the supply of items through transportation is also responsible for carbon emissions. When any company, firm, or industry supplies their items through a supply chain by using of transportation in the regular mode, then a lot of carbon units are emitted from the burning of petrol and diesel, etc., which affects the supply chain. Carbon emissions can be controlled by using different kinds of policies issued by the government of a country, and lots of companies have implemented these policies to control carbon emissions. When a seller delivers a demanded lot size to the buyer, as per demand, and the lot size has some defective items, as per consideration, the demand rate is uncertain in nature. The buyer inspects the received whole lot and divides it into two categories of defective and no defective deteriorating items, as well as immediately selling at different price. The fuzzy concept nullifies the uncertain nature of the demand rate. This paper covers two models, assuming two conditions of quality screening under learning in fuzzy environment: (i) the buyer shows the quality screening and (ii) the quality inspection becomes the seller's responsibility. The carbon footprint from the transporting and warehousing the deteriorating items is also assumed. The aim of this study is to minimize the whole inventory cost for supply chains with respect to lot size and the number of orders per production cycle. Jointly optimizing the delivery lot size and number of orders per production cycle will minimize the whole fuzzy inventory cost for the supply chain and also reduce the carbon emissions. We take two numerical approaches with authentic data (from the literature reviews) for the justification of the proposed model 1 and model 2. Sensitivity observations, managerial insights, applications of these proposed models, and future scope are also included in this paper, which is more beneficial for firms, the industrial sector, and especially for online markets. The impact of the most effective parameters, like learning effect, fuzzy parameter, carbon emissions parameter, and inventory cost are shown in this study and had a positive effect on the total inventory cost for the supply chain. [ABSTRACT FROM AUTHOR]

With the development of global clean energy and the implementation of carbon emission reduction policies, the direct purchase of electricity by large consumers has been increasingly promoted as a special form of electricity trading. Therefore, on the basis of the completion of low-carbon emission reduction targets in each country, how to rationalize the electricity purchase by large consumers in the electricity market so as to reduce their electricity purchase costs has become the main target of attention in each country. Currently, there are fewer studies in existing research on the direct electricity purchase strategy of large consumers under the consideration of the weight of consumption responsibility and risk. Based on this, this paper constructs a dual-game model for direct electricity purchase by large consumers based on the Stackelberg game and non-cooperative game theory. The concept of value at risk is further introduced, and the optimal strategy of direct electricity purchase by large consumers is proposed. The results of this study show that when market players make decisions on the purchase and sale of electricity, power suppliers will increase their biddings to obtain the highest returns, and large consumers can reduce the transaction costs by combining the medium- and long-term market with the spot market to purchase electricity. In the choice of electricity purchase market, with the increasing risk factor, large consumers shift from the risky spot market to the less risky medium- and long-term market and option market. This paper provides a reference for the issues of power suppliers' contract bidding and large consumers' electricity purchase strategy in the medium- and long-term contract transactions. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to explore the impact of carbon neutral announcements on "stock market value" of publicly listed companies in China. Design/methodology/approach: The event study approach is adopted. Market, market-adjusted, Carhart four-factor model and a cross-sectional regression model are employed to examine the impacts of carbon neutral announcements on "stock market value" of Chinese companies based on data from 188 carbon neutral announcements. Findings: Carbon neutral announcements positively impact Chinese shareholder value. Carbon neutral announcements at the strategic level have a more positive and significant impact on Chinese stock market value. Innovative carbon neutral announcements do not significantly cause Chinese stock market reactions. Companies have more positive and significant stock market reactions when the companies make carbon neutral announcements that reflect high supply chain network resilience and heterogeneity and strong supply chain network relationships. Practical implications: The findings uncover the business value of carbon neutral activities and provide operations managers in developing countries insights into how to improve enterprises' market value by actively implementing carbon neutral activities. Originality/value: This paper is the first trial to apply an event study to examine the relationship between carbon neutral announcements and Chinese stock market value from the perspective of announcement level and type and supply chain networks. This paper introduces corporate reputation theory and enriches the application of corporate reputation theory in the field of low-carbon environmental protections and supply chains. [ABSTRACT FROM AUTHOR]

In the context of the global low-carbon energy development strategy, the massive influx of renewable energy leads to the instability of the power system, so it is necessary to carry out effective scheduling strategy and management mechanism for energy. On this basis, the Integrated Energy System including Electricity/Heat/Storage (EHSIES) is discussed in this paper. First, an ordered clustering method using a combination of simulated annealing and improved profile coefficients for load evolution number approximation is proposed. Second, a hybrid load clustering algorithm based on hierarchical clustering algorithm and K-means++ is presented and four types of load scenarios are obtained. Third, an Improved Harris Hawk Optimization (IHHO) algorithm based on the hybrid strategy is proposed and solved to the model of EHSIES. Finally, under the premise of the dynamic carbon trading mechanism considering historical compliance and load aggregator management, the scheduling strategies of flexible electric loads and thermal loads participating in EHSIES are discussed and solved by CPLEX. The results show that the solution time of IHHO is 50% and 33.3% lower than that of particle swarm optimization (PSO) and Harris hawk optimization (HHO), and the number of iterations is 76.6% and 56.25% lower than that of PSO and HHO, respectively. In addition, considering a flexible load aggregator and a compliance-based dynamic carbon trading mechanism in EHSIES scheduling can effectively reduce the actual operating cost by 27.37%, the source-side energy spill rate by 68.75%, and the carbon emission by 51.92% and improve the operating efficiency and economic benefits of EHSIES. [ABSTRACT FROM AUTHOR]

In the context of global carbon neutrality, ports face significant electricity demand for cargo handling and pressure to reduce carbon emissions. The abundant wind energy resources in port areas make wind power highly promising for port applications. The optimal selection of site and turbine types for wind power systems can effectively reduce emissions in ports, achieving sustainability and improving economic benefits. The practical implementation of wind energy systems considering practical constraints holds significant research significance. Taking Ningbo-Zhoushan Port as an example, this paper analyzes the wind energy resources in the port area and provides an overview of wind power system construction sites. Based on the actual conditions of the port area, this paper comprehensively reviews the site selection of wind turbines from the perspectives of wind resources, specific climates, and noise impacts. With the consideration of engineering preferences, this paper selects performance indicators based on the four mainstream turbine models and proposes a comprehensive weight determination method using the entropy weight method and analytic hierarchy process (AHP) to determine the weights of the indicators. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method is then employed to score and compare four turbine plans, enabling the turbine selection process to consider both engineering preferences and objectivity, thereby enhancing the accuracy and reliability of wind turbine planning and achieving significant ecological and economic benefits through benefit analysis. [ABSTRACT FROM AUTHOR]