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[Display omitted] • Facile and scalable self-assembly of perylene diimide polymer with carbon paper. • Effective facilitation of carrier separation by π-π built-in electric field. • Narrowed band gap and low VB due to the VB tail states induced by π-π interactions. • Enhanced photocatalytic water oxidation activity of the PDIP/CP photocatalyst sheet. • Suitability of the PDIP/CP photocatalyst sheet for large-scale applications. Photocatalytic water splitting is a highly promising future energy technology. In contrast to the extensive work on particulate photocatalysts, there is still a lack of sufficient investigation for regularized photocatalysts. Here, from perylene diimide polymer (PDIP) and commercial carbon paper (CP), we develop a self-assembled PDIP/CP photocatalyst sheet that is easily scalable and can be used for photocatalytic water oxidation. Driven by strong interfacial π-π interactions, the PDIP spontaneously adsorbs onto the CP, which leads to a narrowed band gap, down-shifted VB edge, and enhanced separation of the photogenerated charge carriers of the PDIP. Under visible light, the PDIP/CP photocatalyst sheet shows significantly enhanced photocatalytic water oxidation activity (4 h cumulative oxygen evolution is 1.7 times higher than that of the powder-suspended system) and considerable cycling stability. The PDIP/CP photocatalyst sheet has the potential for large-scale device applications. [ABSTRACT FROM AUTHOR]

This paper studies the impact of digital economy development on carbon emissions, which is a hot topic in the field of environmental economics. This topic is within the scope of the Frontiers in Environmental Science and is particularly in line with the theme of Environmental Economics and Management section in the journal. Firstly, this paper constructs the Digital Economy Development Index and its variable indicators to measure the development of the digital economy. Secondly, this paper uses urban panel data to reveal the impact of digital economy development on carbon emissions, and further adopts IV method to deal with endogeneity issues. Thirdly, this paper performs the heterogeneity analyses depending on the characteristics of the city. The results can provide a basis for formulating differentiated policies. Fourthly, this paper further explores the mechanism by which the digital economy affects carbon peaking. The results show that the digital economy may influence carbon peaking through upgrading of the industrial structure, technical innovation, and energy consumption. [ABSTRACT FROM AUTHOR]

This document is a summary of a special issue in the journal Applied Sciences titled "Feature of Review Papers in Nanotechnology and Applied Nanosciences." The special issue aims to gather review papers that highlight recent developments and applications in the field of nanosciences. The seven contributions in this special issue cover a range of topics, including the use of nanocellulose for cultural heritage preservation, protective coatings for metal-based bipolar plates in water electrolysis, carbon dioxide electrocatalytic reduction reactions using transition metal sulfide nanomaterials, plasmonic techniques for detecting micro- and nano-plastics, graphene-based perfect absorbers, nano titanium dioxide for hydrogen production and storage, and X-ray spectroscopy studies of metal-salen complexes. The special issue provides a sample of the diverse applications of nanotechnology and addresses important issues in our polluted and climate-degraded world. [Extracted from the article]

Wearable electronic energy storage devices usually require the integration of flexible mechanisms and uncompromising electrochemistry of lithium-ion batteries (LIBs). Most of the studies in this field have mainly focused on enhancing the electrochemical properties of the material, while the significance of its flexibility and mechanical properties has been relatively ignored. In this study, the 20 wt % carbon fibers (CFs) composite N-doped flexible carbon nanofiber paper (NFCFP) was prepared through a facile PFI refiner and Bauer sieve of pulping and papermaking machinery sieve-assisted methods combined with annealing technology. The NFCFP-700 with high pyridine N content shows good ion transport and storage performance, the specific capacity remained 308 mAh⸱g−1 after 100 cycles at 0.1 C, and even at 1 C, the specific capacity of the electrode material instead increases constantly at 142 mAh⸱g−1. According to density functional theory (DFT) calculations, the coexistence of pyridine N content and defects in carbon materials was found to enhance the adsorption energy (E ad) of lithium, and the N4V2 locally show the most negative electrostatic potential (ESP) distribution, which was more favorable for the adsorption of Li+ being positively charged. This insight from DFT studies combined with experimental data emphasizes the favorable impact of pyridine N content and defects on the lithium adsorption process in carbon materials, also providing valuable information for the design and optimization of materials for lithium storage applications. [ABSTRACT FROM AUTHOR]

This comprehensive review explores recent advancements in the manufacturing of cellulose nanofiber (CNF)-based cellulose nanopaper (CNP). The analysis delves into customizing CNPs through nanofiber manufacturing, mechanical refining, and chemical treatments. The report underscores the growing interest in CNPs derived from CNF due to their exceptional properties and eco-friendly attributes. CNP strength significantly enhanced through mechanical refining encompassing cellulose nanofibrillation were breaking down of cellulose into nanofibers takes place. Conversely, dense CNF network formed through filtration and casting method. Chemical treatments such as dispersion, functionalization, and coating methods followed by drying and consolidation introduce custom functionalities for diverse applications. These applications span packaging, electronics, energy harvesting, EMI shielding, optoelectronics, nanogenerators, transparent conducting films, water treatment, bioelectronics, and neuromorphic computing. The study conducts an in-depth investigation to assess CNP's effects on promoting sustainability and minimizing environmental waste, making a significant contribution to the circular economy. This investigation underscores the pursuit of innovation and aligns with the principles of progressing toward a more environmentally sustainable future. [Display omitted] • Explores CNF production, refining and chemical treatments for CNP customization. • Remarkable properties of CNP draw academic and industrial interest. • CNP applied in packaging, electronics, energy, and environmental science. • Investigates role of CNP in circular economy. • Emphasizes CNPs as eco-friendly, fostering innovation and sustainability. [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]

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

Simultaneously achieving economic development and environmental protection is a shared global challenge. While the positive effect of environmental regulations on protecting the environment has been widely recognized, the attention paid to low-carbon governance and corporate green transformation remains insufficient. Based on the two-stage least square regression model (2SLS) of instrumental variables, this paper utilizes panel data from China to identify the influence mechanism of government low-carbon governance on enterprise green development. It explores the effect of low-carbon governance on enterprise green development from the perspective of fiscal decentralization. The findings show that (1) Low-carbon governance significantly promotes corporate green development, primarily through improving industrial structure and technological innovation; (2) Low-carbon governance notably promotes the green development of private enterprises but has little effect on state-owned enterprises. There are also geographical differences, and the results are better in Eastern China than in the Central and Western parts of China; (3) Fiscal decentralization at both central and local levels inhibits the effect of low-carbon governance on driving corporate green development by causing a mismatch of human resources. Therefore, to promote corporate green development, low-carbon governance must prioritize green development, actively guide industrial structural upgrading and enterprise technological innovation, implement differentiated low-carbon governance measures tailored to different ownership enterprises, and optimize the assessment indicators for fiscal decentralization. This paper helps deepen the understanding of the relationship between government low-carbon governance and enterprise green development in developing countries. It can be used as a reference for government departments to formulate relevant policies. [ABSTRACT FROM AUTHOR]

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

The power sector is one of the major CO2-emitting industries in China. It is also the first key emissions control industry included in China's national carbon trading market established in 2021. Therefore, based on the data of 30 provinces and cities in China from 2015 to 2022, this study analyzes the impact of the national carbon market policy on the carbon emissions of the power industry based on the generalized Difference-in-Difference (DID) model. Based on the method of text analysis, this paper constructs the carbon market policy intensity index of each region and incorporates it into the DID model. Empirical analysis finds that the national carbon market policy can significantly inhibit the carbon emissions of the power industry. However, the heterogeneity analysis of 30 provinces and cities shows that the national carbon market policy has a significant impact on the regions that already have a carbon pilot, but not on the non-pilot regions. Therefore, this paper demonstrates the effectiveness of the national carbon market policy in the power industry emissions control, and also exposes the heterogeneity between regions, providing an important empirical basis for the inclusion of other energy-intensive industries. [ABSTRACT FROM AUTHOR]

In this paper, we select the China Carbon Market Price Index, which reflects the overall price changes in China's carbon market (CCM), and employs the TVP- VAR-BK model to examine the risk spillover effects between the carbon market and high-carbon-emission industries in China from a frequency domain viewpoint. Employing the nonparametric quantile Granger causality test, it delves further into the effects of economic policy uncertainty (EPU) in China on the degree of risk spillovers between the carbon market and high-carbon- emission industries. There are significant risk spillover effects between the carbon market and high-carbon-emission industries. During the short term, the carbon market affects the cement industry more than the electric power and steel industries. However, the carbon market is affected by the volatility of the high-carbon-emission industries over the long term. In addition, the effect of EPU on the magnitude of risk spillovers between the carbon market and high- carbon-emission industries is nonsignificant at extreme quartiles and significant at the middle quartile level, which is typically asymmetric. [ABSTRACT FROM AUTHOR]

The massive CO2 emission has caused frequent occurrence of climate problems, and a typical response to climate change has reached international consensus. Digital finance and green finance, as a subversion of the traditional financial model, have become significant drivers of global carbon emissions reduction efforts. Based on the panel data, this paper profoundly compares the effects of carbon emissions reduction, mechanisms, and heterogeneous results of two forms of finance. Research finds that technology-centered digital finance focuses on suppressing carbon emissions through technological innovation, and the higher the level of regional economic is, the stronger the role of digital finance in suppressing carbon emissions through technological innovation. The concept-centered green finance focuses on carbon emissions reduction through industrial ecologization, and government-led environmental regulation plays a positive regulatory role. Although the paths of affecting carbon emissions are different, there is a natural fit between the two in terms of the essential goal of carbon emissions reduction. Based on the consideration of the differences in geographic location and financial development level, the carbon emission reduction effects of two forms of finance show apparent heterogeneity. Based on the spatial characteristics of digital finance and carbon emissions, this paper further finds that the digital finance's carbon emission reduction effects have apparent spatial spillovers. These findings provide an essential direction to formulate a reasonable carbon emissions reduction plan and accelerate realizing the "double carbon" goal. [ABSTRACT FROM AUTHOR]

With the increasing pressure of resource decline and environmental pollution faced by the green transformation of marine fisheries, marine fishery carbon sinks are an increasingly close link to national strategic interests and economic lifelines. It is, therefore, necessary to explore paths for the enhancement and development of the carbon sink capacity of marine fisheries. Based on the economic data of marine fisheries from 2002 to 2021, this paper measures the capacity and characteristics of marine fishery carbon sinks in provincial areas, applies the kernel density estimation method to depict the dynamic evolution of the distribution of absolute differences in marine fishery carbon sinks, and at the same time, identifies the factors influencing the spatial imbalance in the development of marine fishery carbon sinks as well as the spatial spillover effects. The results show the following: (1) From the total amount, the fishery carbon sink capacity of China's three marine economic circles has fluctuated and increased over the past 20 years, with obvious differences among different circles, and the marine fishery carbon sink capacity of the eastern, northern, and southern marine economic circles has risen sequentially. This trend corresponds to the economic disparities among the three circles, demonstrating a transition from economic to industrial driving effects. (2) From the spatial point of view, the fishery carbon sink capacity shows a trend of increasing year by year, concentrating in the circles, and overflowing between the circles. (3) The results of a partial derivative test further show that among the main influencing factors of marine fishery carbon sinks, capital, labor, and market openness have direct positive effects on marine fishery carbon sinks, and the direct effect of innovation is the strongest, and the significance of the indirect effect of the three circles is weaker compared to the direct effect and total effect. As a result, the carbon sink of China's marine fisheries has a large room for improvement, and in order to promote the high-quality development of China's marine fisheries, it is still necessary to accelerate the circulation of resources within the marine economic circle, accelerate the research of fishery technology, actively develop the carbon sink fishery, and enhance the specialization of aquatic product processing. [ABSTRACT FROM AUTHOR]

This article discusses the practical applications of nanoparticles (NPs) in various fields, such as medicine, cosmetics, catalysis, and environmental protection. The properties of NPs are influenced by their size, shape, and composition, and their use in catalysis can greatly enhance their activity and efficiency. This special issue focuses specifically on the application of NPs in catalysis for environmental protection, including processes such as the oxidation of volatile organic compounds, hydrogen production, CO2 reduction, wastewater treatment, and soot oxidation. The article expresses gratitude towards the reviewers and authors who contributed to the special issue, acknowledging their time and effort in reviewing the papers and appreciating the high-quality research and review papers submitted. [Extracted from the article]

In this paper, we use the literature to help us better understand carbon capture costs and how these estimates fare against those of avoided costs, focusing on bioenergy carbon capture and storage (BECCS), carbon capture and storage (CCS), as well as direct air capture technologies. We approach these questions from a meta-analysis perspective. The analysis uses meta-analysis tools while applying them to numerical rather than statistical studies. Our analysis shows that avoided costs are, on average, 17.4% higher than capture costs and that the carbon intensity of the feedstock matters: the estimates for coal-based electricity generation capture costs are statistically smaller than those for natural gas or air. From a policy perspective, the literature suggests that the costs of CCS are like the 45Q subsidy of USD 50 per metric ton of carbon captured. [ABSTRACT FROM AUTHOR]

Resource-based regions support national economic development and are essential sources of basic energy and raw materials. In the post-pandemic era, however, there are practical situations to deal with, such as a fractured industrial chain, a weaker industrial structure, and a sharp reduction in economic benefits. Based on data collected from 68 cities in China, from 2010 to 2021, with 816 observations, this paper explores the industrial development process of resource-based regions in China and the change in the toughness of the industrial structure under the impact of COVID-19. The paper studies and analyzes industrial development trends, industrial structure toughness, and spatial spillover effects. The methods used are the Markov chain model and the Industrial Structure Advancement Index. By building the spatial Dubin model, the paper analyzes the spatial spillover effect of regional industrial development. It decomposes the spillover effect using the partial differential model based on regression. The results show that, during the study period, the comprehensive development level of industries in resource-based regions in China was slowly improving and tended to stabilize after entering the post-pandemic era. The evolution of an advanced industrial structure is significantly heterogeneous among regions, and each region has different toughness. The impact of COVID-19 has reduced the toughness of China's resource-based regions' industrial structure. The spatial spillover effect of regional industrial development is significant. Labor force, technology input, and industrial-structure optimization have different impacts on the industrial development of neighboring regions. In the post-pandemic era, China has used new management methods for more innovation. In order to achieve low-carbon, environmental protection, and sustainable development of resources, realize the rapid recovery of the toughness of industrial structure in China's resource-based cities, and reduce the impact of the COVID-19 pandemic, China proposes to expand the supply of resources, improve the allocation of resources, optimize the direction, promote the rational flow and efficient aggregation of various factors, and enhance the impetus for innovation and development. [ABSTRACT FROM AUTHOR]

In the context of rapid advancement in automation and increasing global warming, understanding the impact of artificial intelligence (AI) on carbon emissions (CES) is a cutting-edge research topic. However, there is limited focus in existing research on the nonlinear carbon reduction effect (CRE) of AI. This paper first theoretically elaborates the dual impact mechanisms of AI on CES and illuminates the nonlinear carbon reduction mechanisms of AI. Then, this study employs panel data encompassing 30 Chinese provinces between 1997 and 2019 to empirically test the net effect of AI on CES and the nonlinear carbon reduction effect of AI through econometric models. The results are as follows: first, although AI can both reduce and increase CES, AI primarily helps decrease CES. This conclusion holds true even after considering robustness, endogeneity, and spatial heterogeneity. Secondly, relative to the central and western regions, AI has significant achievement in reducing carbon intensity and per capita CES in the eastern region. However, there is still room for improvement in terms of reducing the total CES in the eastern region. Thirdly, improving the AI development level (AIDL) can magnify the marginal CRE of AI and lead to a nonlinear CRE of AI. Lastly, even if the AIDL remains constant, improving the level of marketization, human capital, digital infrastructure, economic development, openness, and government intervention can also amplify the marginal CRE of AI and lead to a nonlinear CRE of AI. To fully harness the potential of AI for green development, concerted efforts should be directed towards enhancing the innovation and application of AI technologies with carbon reduction potential. [ABSTRACT FROM AUTHOR]

Reducing carbon emission intensity is crucial for achieving sustainable development. Carbon emission intensity is expressively affected by the issuance of green bonds. Thus, it is imperative to assess the influence of green bond issuance on carbon emissions and examine their correlation. Such research holds great potential to expedite the overhaul and modernization of businesses and to construct a circular economy system. This paper uses the spatial Durbin model to draw empirical conclusions by using data from 26 provinces in China between 2016 and 2021. Firstly, under different spatial matrices, it has been analyzed that an increase of 1% in the issuance of green bonds leads to a reduction of 0.306% or 0.331% in carbon emission intensity. It shows that green bonds have the potential to substantially reduce carbon intensity. Additionally, the intensity of emissions in the current period is driven by the intensity of emissions in the previous period. Secondly, the analysis of mediated transmission suggests that green bonds can ultimately reduce carbon emission intensity by changing the energy consumption structure or improving the efficiency of green technology innovation. Thirdly, the analysis of heterogeneity shows that the inhibitory effect of green bond issuance on carbon emissions is stronger in less economically developed regions than in economically developed regions. There is a significant inhibitory effect of green bond issuance in neighboring provinces on local carbon emission intensity. This effect is present only in provinces in less economically developed regions and not in economically developed regions. [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]

The development of human society and the production and operation activities of enterprises have brought about global warming, resulting in frequent natural disasters. It has become the consensus of all countries in the world to develop a green and low-carbon economy. Under this background, enterprises, as the main body of economic activities, especially energy industry enterprises, should optimize and upgrade the traditional production and operation mode with high pollution, high consumption, and low output to a high-efficiency and low-pollution mode, and pay attention to the co-ordinated development of economic benefits, social benefits, and ecological benefits. Financial performance evaluation indicators have become the main basis for senior leaders of energy industry enterprises to make decisions and evaluate the low-carbon economic benefits of enterprises. This paper constructs a set of financial evaluation index systems of energy industry enterprises under the background of a low-carbon economy from four dimensions: profitability, asset quality, debt risk, and business growth. The analytic hierarchy process (AHP) is used to measure the comprehensive contribution of financial indicators of low-carbon production and operation. The purpose of this study is to provide scientific financial management decisions for energy enterprises to reduce costs and increase the efficiency and low-carbon operation under the background of a low-carbon economy. The research results show that the comprehensive evaluation index system after the traditional financial evaluation index of energy industry enterprises is integrated with the evaluation index of a low-carbon economy can help enterprises make more correct and effective financial decisions in the process of survival, development, and growth, and, at the same time, the financial evaluation index of a low-carbon economy should pay more attention to the indicators with a higher comprehensive contribution, so as to effectively promote the low-carbon operation efficiency of enterprise production, management, and sales. Compared with other research results, this paper innovatively constructs a financial management decision-making index system for measuring the low-carbon operation of energy enterprises in theory, which has important value in guiding energy enterprises to reduce costs and increase the efficiency and low-carbon operation in practice. [ABSTRACT FROM AUTHOR]

While carbon in itself appears as simple an element as it could possibly get, the undeniable truth is that carbon materials represent a plethora of possibilities both from the perspective of their structure and their applications. While we may believe that carbon is "just another element", one should never forget that its special ability to coordinate through different hybridizations with apparent ease grants the element properties that no other element may even match. Taking this one step further into the materials realm opens up numerous avenues in terms of materials dimensionality, surface and bulk functionalization, or degree of structural order just to mention a few examples. If these properties are translated into the properties and applications field, the results are just as impressive, with new applications and variants appearing with growingly larger frequency. This has resulted in over a million scientific papers published in the last decade in which the term "carbon" was used either in the title, abstract or keywords. When the search is narrowed down to the field "title" alone, the results drop to just over 318.000 scientific papers. These are figures that no other element in the periodic table can equal, which is a clear indicative that the story of carbon materials is still under constant evolution and development. This review will present an overview of the works published in the Frontiers in Carbon-based materials section during its 10 years of life that reflect the advancements achieved during the last decade in the field of carbon materials. [ABSTRACT FROM AUTHOR]

This paper examines the dynamic linkages among economic policy uncertainty (EPU), the green bond market, the carbon market, and the macroeconomy using the time-varying parameter vector autoregressive (TVP-VAR) model with monthly data spanning from January 2016 to December 2021. Additionally, it assesses the robustness and accuracy of the empirical results through the Bayesian vector autoregressive (BVAR) model. The findings indicate that EPU negatively affects the green bond market in the short term but has a positive impact in the medium and long term. Conversely, EPU has a positive impact on the carbon market in the short term but a negative impact in the medium and long term. Furthermore, the green bond market negatively influences the carbon market in both the short and medium to long term. These results suggest that emerging markets, such as the green bond and carbon markets, are influenced by EPU. The adverse impact of the green bond market on the carbon market, however, contributes to expediting China's attainment of its low-carbon objectives. Appropriate economic policies can play a vital role in accelerating the transition to a low-carbon economy. The study also reveals that the US-China trade war has expedited the development of green capital markets in China, despite its impact on the green economic transition in the country. These findings provide insights for the government and investors to formulate suitable strategies for risk mitigation. [ABSTRACT FROM AUTHOR]

As an unconventional resource, oil shale possesses abundant reserves and significant potential for industrial applications. The rational and efficient development of oil shale resources holds immense importance in reducing national energy demand. In-situ catalytic technology, characterized by its high efficiency, low pollution, and minimal energy consumption, represents a key direction for future oil shale development. This paper provides a comprehensive review of research progress in in-situ oil shale mining technology, oil shale pyrolysis catalysts, the pyrolysis mechanism of kerogen, and the compatibility of different heating processes and catalysts. Furthermore, the paper proposes future research directions and prospects for oil shale in-situ catalytic technology, including reservoir modification, highefficiency catalyst synthesis, injection processes, and high-efficiency heating technology. These insights serve as valuable technical references for the advancement of oil shale in-situ catalytic technology. [ABSTRACT FROM AUTHOR]

Due to the strong penetrability, long-wavelength synthetic aperture radar (SAR) can provide an opportunity to reconstruct the three-dimensional structure of the penetrable media. SAR tomography (TomoSAR) technology can resynthesize aperture perpendicular to the slant-range direction and then obtain the tomographic profile consisting of power distribution of different heights, providing a powerful technical tool for reconstructing the three-dimensional structure of the penetrable ground objects. As an emerging technology, it is different from the traditional interferometric SAR (InSAR) technology and has advantages in reconstructing the three-dimensional structure of the illuminated media. Over the past two decades, many TomoSAR methods have been proposed to improve the vertical resolution, aiming to distinguish the locations of different scatters in the unit pixel. In order to cope with the forest mission of European Space Agency (ESA) that is designed to provide P-band SAR measurements to determine the amount of biomass and carbon stored in forests, it is necessary to systematically evaluate the performance of forest height and underlying topography inversion using TomoSAR technology. In this paper, we adopt three typical algorithms, namely, Capon, Multiple Signal Classification (MUSIC), and Compressed Sensing (CS), to evaluate the performance in forest height and underlying topography inversion. The P-band airborne full-polarization (FP) SAR data of Lopè National Park in the AfriSAR campaign implemented by ESA in 2016 is adopted to verify the experiment. Furthermore, we explore the effects of different baseline designs and filter methods on the reconstruction of the tomographic profile. The results show that a better tomographic profile can be obtained by using Hamming window filter and Capon algorithm in uniform baseline distribution and a certain number of acquisitions. Compared with LiDAR results, the root-mean-square error (RMSE) of forest height and underlying topography obtained by Capon algorithm is 2.17 m and 1.58 m, which performs the best among the three algorithms. [ABSTRACT FROM AUTHOR]

Existing researches lack systematic design of the operation mechanism and overall implementation process of park oriented multi‐state energy system; The existing researches on multi‐state energy systems ignored the dynamic response characteristics of load and the coupling effect of units considering the impact of carbon emissions, and did not go deep into the collaborative management of multiple multi state energy system parks. To this end, this paper first proposes a two‐stage multi‐energy system operation architecture for low carbon parks, and establishes a mathematical model considering carbon emissions, operating costs and other objectives. The response space of load is optimized by considering the dynamic interaction characteristics of load response and the coupling characteristics of unit operation. Then, considering the problems of data security and training efficiency, F‐DDPG technology is used to conduct collaborative training for multiple campus systems. Finally, an example is given to prove the effectiveness of the method, which is not only conducive to reducing the operating cost of the system and the carbon emissions on the supply side, but also improves the convergence of model training. In the case of collaborative training in multiple parks, the method in this paper converges faster and has better economic benefits. [ABSTRACT FROM AUTHOR]

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

The serious consequences of climate warming have increasingly become a globe agenda in recent decades. China has been actively participating in various initiatives to address global climate change and has made commitments to reduce carbon emissions. Although the logistics industry is regarded as the "new driving force of national economic development", its carbon intensity is relatively high. Therefore, whether the logistics industry can develop in a green and low-carbon way is very crucial. This paper takes the green logistics efficiency of China's provincial logistics industry as the research object. The Super-SBM model is used to measure the China's green logistics efficiency, then the general dynamic characteristics is depicted by kernel density analysis. With the GML (Global Malmquist-Luenberger) index model, the reasons for the changes in green logistics efficiency are explained. Finally, Moran's I index is used to analyze the spatial correlation of green logistics efficiency in each province. The results show that the green logistics efficiency in China is at a low level, but with an upward trend. China's green logistics efficiency has a significant positive spatial correlation, showing a zonal pattern of high in the east and low in the west, and a polarization phenomenon. In addition, the bottleneck of the overall development of green logistics efficiency in China depends on the level of green technology. Furthermore, the results also imply that green technology advancement is an inherent key factor for green logistics efficiency to achieve growth. [ABSTRACT FROM AUTHOR]

Constructing a new energy-based power system is not only an important direction for the transformation and upgrade of China's power system, but also a key to achieving peak carbon and carbon neutrality. How to fully utilize situation awareness technology to adapt to diverse and differentiated scenarios has become a crucial breakthrough point for ensuring the reliable, safe, high-quality, low-carbon, and economical operation of the new power system. Starting from the distribution network demand resources, this paper proposes a dynamic aggregation method for load aggregators considering the user deviation quantity, to deal with the current situation that the adjustable load-side resource points are multi-faceted and wide, and the operating subjects are complex and difficult to participate directly in the grid dispatch. First, considering there is subjectivity in the electricity behavior of users under the jurisdiction of the load aggregator, a deviation amount may be generated during the actual aggregation process, which reduces the profit of the load aggregator. Therefore, a load aggregator-level user deviation dynamic volume forecasting method based on the Markov chain is proposed, which is used to predict the deviation quantity of users during the dispatch cycle and achieve a dynamic status estimate on the load side of the new power system. On this basis, a dynamic aggregation model for load aggregators based on the deviation volume was constructed with the objective of maximizing the revenue of load aggregators. The examples, by comparing the aggregation results of users under three scenarios, show the proposed method can effectively guarantee the income of load aggregators, verify the effectiveness of the proposed dynamic aggregation strategy, and provide technical support for the operation situation awareness of the load side of the new power system. [ABSTRACT FROM AUTHOR]

Carbon price prediction is of great importance to regulators and participants in the carbon trading market. It is the basis for developing policies related to the carbon trading market and stabilizing that market. Considering the numerous factors that influence carbon prices in China, dimensionality reduction is needed to improve the prediction accuracy and efficiency. However, the traditional dimensionality reduction methods fail to fully consider the role of influencing factors, which has certain limitations. In this paper, a new dimensionality reduction method, namely scaled principal component analysis (s-PCA), is employed to improve the prediction accuracy of carbon prices. Firstly, a factor library that influence carbon prices is constructed from three perspectives: technical indicators, financial indicators and commodities indicators. Then, the s-PCA method is used to reduce the dimensionality of factors influencing carbon price. Next, two different methods are used to predict carbon prices, including traditional regression method and Long Short-Term Memory (LSTM) method. Finally, the economic value of the s-PCA method is examined by constructing investment portfolios. The empirical results of the Hubei Emissions Exchange show that the s-PCA model outperforms other competing models both in- and out-of-sample. In addition, the LSTM model could improve the performance of the s-PCA model in carbon price prediction. From a market timing perspective, investors can achieve a greater return and a larger Sharpe ratio using the s-PCA method than using other comparative methods and buy-and-hold strategy. Therefore, the s-PCA method is effective and robust in predicting carbon price. [ABSTRACT FROM AUTHOR]

From the perspective of configuration, this paper takes the region of manufacturing efficiency as the explanatory variable, selects eight antecedent conditions, and applies fuzzy set qualitative comparative analysis (fsQCA) to study the paths and methods of improving manufacturing emission efficiency. The results of the study show that there are two configuration paths of carbon emission efficiency in manufacturing industry, namely, research frontier and technological innovation level and labour force structure, R&D investment, science and technology innovation level, manufacturing output value, and environmental regulation synergistic path. [ABSTRACT FROM AUTHOR]

This paper analyzes the theoretical mechanism by which urbanization and consumption structure upgrading exert an impact on carbon emissions in the context of promoting higher quality and efficiency in urbanization, advancing the transition and upgrading of consumption structure, and achieving carbon peaking and carbon neutrality (“dual carbon”) goals. By establishing an extended STIRPAT model and an intermediary model, this paper takes nine prefecture-level cities in Fujian Province from 2011 to 2021 as samples to investigate the effects of urbanization and consumption structure upgrading on carbon emission reduction in Fujian Province, revealing the interrelationship and transmission mechanism among the three. The results of this study show that: (i) The relationship between urbanization and carbon emissions in Fujian Province from 2011 to 2021 shows an inverted U-shaped curve, i.e. urbanization accelerated carbon emissions in the early stage and inhibited carbon emissions in the later stage; (ii) the regional heterogeneity analysis shows that under the current urbanization background, the upgrading of consumption structure in western and southern Fujian can significantly reduce carbon emissions, while the relationship between consumption structure upgrading and carbon emission reduction in eastern Fujian is not significant; (iii) the upgrading of consumption structure can help achieve and promote carbon emission reduction through increasing the proportions of the tertiary industry and immaterial consumption and enhancing the level of culture and education, while exerting little effect on carbon emission reduction through consumption in transportation, communication and health care. [ABSTRACT FROM AUTHOR]

Improving China's high-quality development efficiency represents a key lever for the development of new productivity and successfully achieving the "dual carbon" goal. Starting from the nonparametric production theory, this paper addresses the issues of infeasible solutions and technical heterogeneity by employing the total-factor non-radial directional distance function and a metafrontier non-radial Malmquist model. The static total-factor high-quality development efficiency index (THEI) and its dynamic metafrontier non-radial Malmquist high-quality development efficiency index (MNMHEI) are measured for 31 provinces in China from 2008 to 2021. Given that high-quality development efficiency is led and driven by talent, we use labor of different ages and levels of education as four inputs instead of single labor for the study of THEI. The MNMHEI is divided into three indices for measuring efficiency change (EC), best-practice gap change (BPC), and technology gap change (TGC). The empirical results demonstrate that labor with higher education is the main lever of static high-quality development efficiency; there is a 5.3% decrease in China's dynamic high-quality development efficiency as a whole, and a lack of technological innovation remains a significant constraint on its improvement. The results of the heterogeneity analysis, which classified all provincial areas into low-carbon and high-carbon regions, indicate that the former exhibits a higher dynamic high-quality development efficiency than the latter, which still lacks innovation and technology leadership. It is recommended that the Chinese government consider the talent management system, investments in upgrading technologies, energy conservation, and emission reduction for high-carbon regions to improve their high-quality development efficiency. [ABSTRACT FROM AUTHOR]

Chemical molecular structures are a direct and convenient means of expressing chemical knowledge, playing a vital role in academic communication. In chemistry, hand drawing is a common task for students and researchers. If we can convert hand-drawn chemical molecular structures into machine-readable formats, like SMILES encoding, computers can efficiently process and analyze these structures, significantly enhancing the efficiency of chemical research. Furthermore, with the progress of educational technology, automated grading is gaining popularity. When machines automatically recognize chemical molecular structures and assess the correctness of the drawings, it offers great convenience to teachers. We created ChemReco, a tool designed to identify chemical molecular structures involving three atoms: C, H, and O, providing convenience for chemical researchers. Currently, there are limited studies on hand-drawn chemical molecular structures. Therefore, the primary focus of this paper is constructing datasets. We propose a synthetic image method to rapidly generate images resembling hand-drawn chemical molecular structures, enhancing dataset acquisition efficiency. Regarding model selection, the hand-drawn chemical molecule structural recognition model developed in this article achieves a final recognition accuracy of 96.90%. This model employs the encoder-decoder architecture of EfficientNet + Transformer, demonstrating superior performance compared to other encoder-decoder combinations. [ABSTRACT FROM AUTHOR]

As the main contributor of carbon emissions, the low-carbon transition of the industrial sector is important for achieving the goal of carbon dioxide peaking. Hydrogen-enabled industrial energy systems (HIESs) are a promising way to achieve the low-carbon transition of industrial energy systems, since the hydrogen can be well coordinated with renewable energy sources and satisfy the high and continuous industrial energy demand. In this paper, the long-term capacity expansion planning problem of the HIES is formulated from the perspective of industrial parks, and the targets of carbon dioxide peaking and the gradual decommissioning of existing equipment are considered as constraints. The results show that the targets of carbon dioxide peaking before different years or with different emission reduction targets can be achieved through the developed method, while the economic performance is ensured to some extent. Meanwhile, the overall cost of the strategy based on purchasing emission allowance is three times more than the cost of the strategy obtained by the developed method, while the emissions of the two strategies are same. In addition, long-term carbon reduction policies and optimistic expectations for new energy technologies will help industrial parks build more new energy equipment for clean transformation. [ABSTRACT FROM AUTHOR]

Introduction: In the digital era, new digital infrastructures (NDIs) play a pivotal role in fostering economic growth and technological innovation. However, their ecological impact, particularly on carbon dioxide emissions, remains underexplored. Addressing this gap holds significant practical and theoretical value. Methods: Utilizing panel data from 283 Chinese cities spanning 2009 to 2020, this study employs a two-way fixed-effects model to empirically assess the influence of NDIs on urban carbon emissions (UCE). Additionally, a mediation effect model is used to examine the mechanisms of this influence. Results: The findings reveal that: (1) NDIs significantly mitigate UCE levels, a conclusion supported by robustness tests involving instrumental variables and the exogenous policy shocks of smart city pilot programs; (2) NDIs primarily impact UCE through two channels: the digital economy and green technology innovation; and (3) heterogeneity analysis indicates that NDIs predominantly curb carbon emissions in cities with lower administrative levels, while positively contributing to UCE intensity in higher administrative level cities. Notably, NDIs substantially reduce UCE in non-old industrial cities, with a negligible effect in old industrial cities. Discussion: This research expands the understanding of the economicenvironmental implications of NDIs, offering valuable insights for policymakers regarding NDIs' environmental impacts. It also provides strategic guidance for urban low-carbon transitions in the big data era. [ABSTRACT FROM AUTHOR]

The new development pattern has identified two key avenues for the sustained advancement of high-quality agricultural and rural development: digitalisation and low-carbon development. The measurement of the digital economy and the agricultural carbon emission performance, and their spatial and temporal heterogeneity, is a crucial step in promoting the spatial coordination and sustainable development of digitalisation and low-carbon agriculture. This paper employs the entropy value method, SBM model, and coupling coordination degree model to investigate the coupling coordination measurement and spatial-temporal heterogeneity of the performance of the digital economy and agricultural carbon emissions. The data used are provincial panel data from 2013 to 2021. The simulation results demonstrate that, between 2013 and 2021, the digital economy of all provinces exhibited varying degrees of growth, yet the development of the digital economy between provinces exhibited a more pronounced tendency to diverge. Concurrently, the agricultural carbon emission efficiency in China exhibited a fluctuating upward trend. The development of the digital economy and the efficiency of agricultural carbon emission were found to be highly coupled. Their coupling and coordination relationship showed a downward trend followed by an upward trend. In general, it is suggested that we should increase investment in digital economy infrastructure and technology, promote digital agricultural applications, strengthen policy guidance and financial support, establish a coupling coordination mechanism and strengthen farmers' digital literacy and environmental awareness. [ABSTRACT FROM AUTHOR]

Flexible conductive films are a key component of strain sensors, and their performance directly affects the overall quality of the sensor. However, existing flexible conductive films struggle to maintain high conductivity while simultaneously ensuring excellent flexibility, hydrophobicity, and corrosion resistance, thereby limiting their use in harsh environments. In this paper, a novel method is proposed to fabricate flexible conductive films via centrifugal spinning to generate thermoplastic polyurethane (TPU) nanofiber substrates by employing carbon nanotubes (CNTs) and carbon nanofibers (CNFs) as conductive fillers. These fillers are anchored to the nanofibers through ultrasonic dispersion and impregnation techniques and subsequently modified with polydimethylsiloxane (PDMS). This study focuses on the effect of different ratios of CNTs to CNFs on the film properties. Research demonstrated that at a 1:1 ratio of CNTs to CNFs, with TPU at a 20% concentration and PDMS solution at 2 wt%, the conductive films crafted from these blended fillers exhibited outstanding performance, characterized by electrical conductivity (31.4 S/m), elongation at break (217.5%), and tensile cycling stability (800 cycles at 20% strain). Furthermore, the nanofiber-based conductive films were tested by attaching them to various human body parts. The tests demonstrated that these films effectively respond to motion changes at the wrist, elbow joints, and chest cavity, underscoring their potential as core components in strain sensors. [ABSTRACT FROM AUTHOR]

This study investigates the competitive issues of the newsvendor problem with product substitution under the carbon cap-and-trade system. Building on existing research, this paper introduces the carbon cap-and-trade system under uncertain market demand and considers that the original equipment manufacturer (OEM) can choose to procure raw materials from the contract manufacturer (CM), with both final products being substitutable. Furthermore, we explore the different substitution relationships between OEM and CM products under both pure competitive and co-opetitive modes. For this problem, decision models are developed for various scenarios, and optimal solutions satisfying given conditions are provided. We find that in one-way substitution, under pure competition, an increase in the OEM's (or CM's) green investment and substitution rate only leads to an increase in OEM's (or CM's) yields, while an increase in the OEM's (or CM's) green investment does not necessarily reduce CM's (or OEM's) yields. In the co-opetitive mode, an increase in the substitution rate and green investments of both manufacturers may lead to an increase in the yields of both manufacturers. Furthermore, an increase in carbon trading prices does not necessarily inhibit the manufacturer's yields. Moreover, we find that under the same competition mode, under certain conditions, two-way substitution between OEM and CM can bring better profits to both manufacturers and the entire supply chain. When the two modes are in the same substitution scenario, and the CM cannot substitute for the OEM, the optimal decisions and total supply chain profits of the two modes are equal. Finally, through numerical analysis, we find that neither mode is necessarily optimal when CM can substitute for OEM. Additionally, it is observed that when the same mode is in different substitution scenarios, total supply chain profits may be enhanced in the presence of product substitution. [ABSTRACT FROM AUTHOR]

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

Carbon nanofibers (CNFs) and graphene nanosheets (GNs) are introduced to obtain nano-sized TiC particles in a novel additive manufactured Ni-Co-based superalloy. The double strengthening effects of reaction-induced TiC and remaining CNFs/GNs are conceptualized in the present paper. The CNFs and GNs act as heterogeneous nucleation sites for the formation of uniformly distributed TiC nanoparticles, which inhibits the crack and homogenize the microstructure. Interestingly, the existence of remaining GNs/CNFs is revealed via 3D atom-by-atom tomographic reconstruction technology for the first time. This unique combination of nanoparticles and residual CNFs/GNs nanofillers has great potential to develop superalloys with excellent properties. The formation of nano-sized dispersion TiC particles is induced by the introduction of carbon nanofibers and graphene nanosheets in additive manufactured superalloy, which inhibits the crack and homogenizes the microstructure. [ABSTRACT FROM AUTHOR]

Amid China's pursuit of a green and low-carbon transition, corporate social responsibility (CSR) is facing new challenges. Our research delves into the influencing factors and mechanisms for CSR reputation under green and low-carbon transition and provides practical enlightenment for enterprises to achieve sustainable development. This paper constructs a comprehensive index system of CSR from five dimensions (innovation, coordination, sustainability, openness, and sharing), and CSR reputation of China's A-share listed companies is comprehensively estimated by using an entropy method and data from 2013 to 2021. Then, from the perspective of external supervision and internal governance, we discuss the influence factors of CSR reputation, with an emphasis on the impact of public environmental concerns. Finally, the realization mechanism of CSR is further revealed. It is found that public environmental concern and the expansion of the enterprise scale boost the enhancement of CSR reputation. However, a higher proportion of female managers tends to hinder CSR reputation. Furthermore, public environmental concern plays a more prominent role in improving CSR reputation of non-state-owned and eastern enterprises. Additionally, public environmental concern significantly enhances CSR reputation through green technology innovation and executive environmental awareness. This research provides valuable insights for improving CSR reputation and optimizing regulatory compliance and governance practices. [ABSTRACT FROM AUTHOR]

The NASICON-structured Na3MnZr(PO4)3 compound is a promising high-voltage cathode material for sodium-ion batteries (SIBs). In this study, an easy and scalable electrospinning approach was used to synthesize self-standing cathodes based on Na3MnZr(PO4)3 loaded into carbon nanofibers (CNFs). Different strategies were applied to load the active material. All the employed characterization techniques (X-ray powder diffraction (XRPD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), energy-dispersive X-ray spectroscopy (EDS), thermal gravimetric analysis (TGA), and Raman spectroscopy) confirmed the successful loading. Compared to an appositely prepared tape-cast electrode, Na3MnZr(PO4)3/CNF self-standing cathodes demonstrated an enhanced specific capacity, especially at high C-rates, thanks to the porous conducive carbon nanofiber matrix. Among the strategies applied to load Na3MnZr(PO4)3 into the CNFs, the electrospinning (vertical setting) of the polymeric solution containing pre-synthesized Na3MnZr(PO4)3 powders resulted effective in obtaining the quantitative loading of the active material and a homogeneous distribution through the sheet thickness. Notably, Na3MnZr(PO4)3 aggregates connected to the CNFs, covered their surface, and were also embedded, as demonstrated by TEM and EDS. Compared to the self-standing cathodes prepared with the horizontal setting or dip–drop coating methods, the vertical binder-free electrode exhibited the highest capacity values of 78.2, 55.7, 38.8, 22.2, 16.2, 12.8, 10.3, 9.0, and 8.5 mAh/g at C-rates of 0.05C, 0.1C, 0.2C, 0.5C, 1C, 2C, 5C, 10C, and 20C, respectively, with complete capacity retention at the end of the measurements. It also exhibited a good cycling life, compared to its tape-cast counterpart: it displayed higher capacity retention at 0.2C and 1C, and, after cycling 1000 cycles at 1C, it could be further cycled at 5C, 10C, and 20C. [ABSTRACT FROM AUTHOR]

The severe global warming issue currently threatens humans' existence and development. Countries and international organizations have effectively implemented policies to reduce carbon emissions and investigate low-carbon growth strategies. Reducing carbon emissions is a hot topic that academics and government policy-making departments are concerned about.Through necessary condition analysis (NCA) and fuzzy set qualitative comparative analysis(fsQCA), this paper investigates local governments' configuration linkage effect and path choice to improve carbon emission performance from six dimensions: energy consumption, industrial structure, technological innovation, government support, economic development, and demographic factors. The research findings include the following: (1) Individual condition does not represent necessary conditions for the government's carbon performance. Among the two sets of second-order equivalence configurations(S and Q) (five high-level carbon performance configurations), those dominated by economic development or low energy consumption can produce high-level carbon performance. Therefore, the six antecedent conditions dimensions work together to explain how the government can create high levels of carbon performance. (2)According to the regional comparison, China's eastern, central, and western regions exhibit similarities and differences in the driving forces behind high carbon emission performance. All three regions can demonstrate carbon emission performance when all the factors are combined. However, when constrained by the conditions of each region's resource endowment, the eastern region emphasizes the advantage of economic and technological innovation, the central region favors government support and demographic factors, and the western region prefers upgrading industrial structure based on a specific level of economic development. [ABSTRACT FROM AUTHOR]

Lightweight and low-cost one-dimensional carbon materials, especially biomass carbon fibers with multiple porous structures, have received wide attention in the field of electromagnetic wave absorption. In this paper, graphene-coated N-doped porous carbon nanofibers (PCNF) with excellent wave absorption properties were successfully synthesized via electrostatic spinning, electrostatic self-assembly, and high-temperature carbonization. The obtained results showed that the minimum reflection loss of the absorbing carbon fiber obtained under the carbonization condition of 800 °C is −51.047 dB, and the absorption bandwidth of reflection loss below −20 dB is 10.16 GHz. This work shows that carbonization temperature and filler content have a certain effect on the wave-absorbing properties of fiber, graphene with nanofiber, and the design and preparation of high-performance absorbing materials by combining the characteristics of graphene and nanofibers and multi-component coupling to provide new ideas for the research of absorbing materials. [ABSTRACT FROM AUTHOR]

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

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

Given the challenges we face of an ageing infrastructure and insufficient maintenance, there is a critical shift towards preventive and predictive maintenance in construction. Self-sensing cement-based materials have drawn interest in this sector due to their high monitoring performance and durability compared to electronic sensors. While bulk applications have been well-discussed within this field, several challenges exist in their implementation for practical applications, such as poor workability and high manufacturing costs at larger volumes. This paper discusses the development of smart carbon-based cementitious coatings for strain monitoring of concrete substrates under flexural loading. This work presents a physical, electrical, and electromechanical investigation of sensing coatings with varying carbon black (CB) concentrations along with the geometric optimisation of the sensor design. The optimal strain-sensing performance, 55.5 ± 2.7, was obtained for coatings with 2 wt% of conductive filler, 3 mm thickness, and a gauge length of 60 mm. The results demonstrate the potential of applying smart coatings with carbon black addition for concrete strain monitoring. [ABSTRACT FROM AUTHOR]

This paper presents a fuel injection rate predictive model based on zero-dimensional correlations from experimental results. This model estimates the fuel injection rate behavior with varying parameters such as fuel injection pressure-injector energizing, the injection nozzle geometrical characteristics, and fuel viscosity. The model approach was carried out with diesel fuel. Then, the model was applied to the use of two alternative low-carbon fuels without diesel. An experimental methodology was used under controlled conditions, employing an injection rate indicator to measure the injection parameters in real time. The setup was carried out on a pump test bench using a common rail injection system. The results show that the model can be adapted to different injection conditions and fuels. [ABSTRACT FROM AUTHOR]

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

Process Intensification (PI) is an effective way to enhance process efficiency and sustainability at affordable costs and efforts, attracting particular interest in the European area, as one of the most important chemical production areas in the world. PI primarily contributes by developing and testing new processing technologies that once integrated within a process improve the overall process performance substantially but as a result, it may alter the overall process (flowsheet) structure and its dynamic behavior. As such PI plays a key role in improving energy efficiency, optimizing resource allocation, and reducing environmental impact of industrial processes, and thereby leading to a cost- effective, eco-efficient, low-carbon and sustainable industry. However, along with opportunities, the PI new technologies have challenges related to failures in longer-term performance. In this respect, Process Systems Engineering (PSE) stance is more on integration aspects of new PI technologies into processes by making process (re)designs, doing operability studies, and performance optimizations within a supply chain setting. PSE contributes to overcoming the challenges by providing systematic approaches for the design and optimization of PI technologies. This perspective paper is a lightly referenced scholarly opinion piece about the status and directions of process intensification field from a PSE viewpoint. Primarily, it focuses on PSE perspectives towards sustainable lower energy usage process systems and provides a brief overview of the current situation in Europe. It also emphasizes the key challenges and opportunities for (new) PI technologies considering their integration in a process in terms of process synthesis and design, process flowsheet optimization, process and plantwide control, (green) electrification, sustainability improvements. Potential research directions on these aspects are given from an industrial and academic perspective of the authors. [ABSTRACT FROM AUTHOR]