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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]

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]

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]

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]

With the change of climate issues and the needs of economic development, the idea of practicing green and low-carbon behaviors sinks deeper and deeper into people's hearts. This paper based on the social cost of carbon (SCC) model, this paper constructs a new carbon social cost model by adding the impact of green low-carbon behavior. Classify climate states, based on Bayesian statistical knowledge, study the posterior probability distribution of climate state transitions, and discuss the optimal carbon policy for different climate states by balancing emission utility costs and utility weighted carbon marginal products. This article also discusses the damage caused by rising temperatures and explores their impact on carbon price policies. then, the paper calculates SCC under four kinds of climate states, which will be visually displayed with graphs. Finally, we compare SCC obtained in this paper with that in other researches. The results show that: (1) Climate status has a significant impact on carbon policy, and carbon price predictions will dynamically change with climate status. (2) Green low-carbon behavior has a positive impact on climate status. (3) There are differences in the impact of the three types of damage caused by rising temperatures on carbon price policies. (4) Green development is conducive to stabilizing the value of SCC. (5) Close monitoring of the climate state helps to update the probability of damage in time so that we can precisely adjust the corresponding policies on SCC. This study provides theoretical and empirical reference for the government to formulate carbon price policies and promote the development of social green behavior. [ABSTRACT FROM AUTHOR]

Identifying the relationship between carbon neutrality initiatives and its economic impact is crucial in evaluating the cost of low-carbon transition for policy makers. In this paper, a theoretical model is built to discuss the effects of the low-carbon pilot policy in China on urban economic resilience and an empirical test is conducted to examine the relationship using the Heckman two stage model and a panel data of 277 cities from 2004 to 2020. The results show that low-carbon pilot policy significantly enhanced urban economic resilience and the stimulating effect is mainly achieved by motivating technology innovations. In addition, further analysis indicates that low-carbon pilot policy has a more pronounced effect on improving urban economic resilience of cities in the central and western regions than eastern regions. The effect is also more prominent in non-first-tier cities than first-tier cities. The results are robust to placebo test, the Propensity Score Matching Difference-in-Difference test and the test for alternative measure of urban economic resilience. The findings show that the low-carbon pilot policy is consistent with the goal of improving urban economic resilience and technology innovation is the essential pillar of sustainable development. [ABSTRACT FROM AUTHOR]

The development of green finance and the promotion of green transformation and upgrading of high energy-consuming enterprises are of great significance for China to achieve the "double carbon" goal. This paper employs a dual fixed-effects model to examine the profound ramifications and intrinsic mechanisms of green finance development on the transformative innovation of high-energy-consumption enterprises, using a sample of 462 publicly traded high-energy-consuming corporations from the period spanning 2016 to 2020. The results show that the development of green finance promotes the transformation and innovation of energy-intensive enterprises and that market-incentivized environmental regulation plays a partially mediating role; the results of heterogeneity analysis show that green finance promotes the transformation and innovation of high energy-consuming enterprises with significant differences in different low-carbon pilot regions, company ownership, and enterprise size; the mechanism analysis shows that the development of green finance can increase government subsidies and alleviate financing constraints to promote the transformation and innovation of high energy-consuming enterprises; it is also found that the development of green finance can significantly improve the financial performance of enterprises. The research findings of this paper hold significant implications for promoting the sustainable development of green finance and high-energy consumption enterprises in China. They provide valuable insights and references for facilitating the green transformation and innovation of high-energy-consuming enterprises in China as well as other developing countries. [ABSTRACT FROM AUTHOR]

Low-carbon pilot policies are an important way to achieve the goal of "peak carbon neutrality" and are of great significance to China's international commitments. Based on a sample of 282 prefecture-level cities from 2006 to 2020, this paper investigates the impact of low-carbon pilot policies on urban carbon efficiency using a quasi-natural experiment with three batches of low-carbon pilot cities in 2010, 2012, and 2017, respectively. It is found that: (1) low-carbon pilot cities can improve urban carbon emission efficiency, which is still valid after a series of robustness tests such as the parallel trend test, placebo test, PSM-DID, and counterfactual test; (2) low-carbon pilot cities can enhance urban carbon emission efficiency by promoting the level of urban innovation and advanced urban industrial structure; and (3) the impact of low-carbon pilot policies on urban carbon emission efficiency is heterogeneous across cities with different geographical locations, population sizes, and resource endowment types. The findings provide policy insights for the promotion of low-carbon pilot policies and strengthening the construction of low-carbon pilot cities. [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]

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]

Taking 30 provinces in China from 2011 to 2020 as a research sample, this paper empirically tests the impact of digital village construction on carbon emissions. This study found that there is an "inverted U" curve relationship between digital rural construction and rural carbon emissions. Agricultural planting structure and agricultural technology efficiency are important ways for digital village construction to reduce agricultural carbon emissions. The study also found that the higher the level of economic development, the stronger the carbon emission reduction effect of digital village construction. In addition, there are also significant differences in the carbon emission reduction effect of digital village construction in regions with different environmental regulation intensities. Finally, in terms of the relationship between digital economic activities and carbon emission reduction, the research conclusions of this paper have important implications. [ABSTRACT FROM AUTHOR]

This paper constructs a theoretical model of biased production decisions due to the import of environmental intermediate goods. Additionally, it analyzes the influence of these imports on CO2 emissions based on the trade and CO2 emission data of Chinese prefecture-level cities from 2000 to 2016. Furthermore, it empirically explores how environmental intermediate imports affect CO2 emissions. The study found the following: first, the import of environmental intermediate goods can effectively reduce CO2 emissions; this conclusion still holds under robustness and endogeneity tests. Second, the carbon emission reduction effect related to the import of environmental intermediate goods is affected by differences in geographical location, environmental pollution, sustainable development ability and government efficiency. Third, the mechanism test found that the import of environmental intermediate goods exerts emission reduction effects through the green technological innovation and industrial structure upgrading mechanisms. The conclusions of the research in this article provide a reference for coordinating trade development and environmental protection. [ABSTRACT FROM AUTHOR]

Background and objectives: Addressing climate change and reducing greenhouse gas emissions have emerged as shared global objectives. Enhancing the development performance of low-carbon cities has become an urgent and widely acknowledged concern for both government policy-making departments and academics. Drawing upon the complex grouping perspective and resource allocation theory, this study investigates how varying conditions related to technology, organization, and environment in Chinese low-carbon pilot cities can effectively allocate resources to shape the governance performance of low-carbon cities. Methods and data: This paper employs a comprehensive grouping analysis perspective, treating the research object as a combination of various ways between condition variables. It integrates the advantages of case studies and variable studies, and investigates the collective relationships between elemental groupings and outcomes using the fsQCA analysis method. This approach facilitates the understanding of multiple concurrent causal relationships within the technology-organization-environment (TOE) framework, accounting for different performance levels in Chinese low-carbon pilot cities, as well as addressing complex causal issues such as asymmetry and multiple scenario equivalence. Data from 30 representative low-carbon pilot cities in China were employed to validate the TOE theoretical framework. Conclusion: No single element alone can be considered a necessary condition for low-carbon city governance performance. However, environmental enhancement plays a more prominent role in the governance performance of low-carbon cities. Additionally, the presence of "multiple concurrent" technical, organizational, and environmental conditions leads to a diverse range of governance performance in Chinese low-carbon pilot cities. In other words, the driving paths of low-carbon city performance exhibit distinct pathways. Contribution: The findings of this study can assist low-carbon pilot city managers in generating effective governance ideas, facilitating the successful implementation of low-carbon city pilot projects, and drawing valuable lessons from the experience of low-carbon city development in China. [ABSTRACT FROM AUTHOR]

For the two emission reduction technologies of clean process (CT Mode) and end-of-pipe pollution control technology (ET Mode), this paper constructs production and low-carbon R&D decision-making models considering consumers' green preference, and discusses the impact of social responsibility on firm's decision-making, profit and social welfare. Then, the difference of optimal decision, profit and social welfare is analyzed when the firm adopt two emission reduction technologies with or without reward-penalty policy. The main conclusions of this paper are as follows: (1) Whether using clean process technology or end-of-pipe pollution control technology, consumers' green preference behavior can increase corporate profit. When consumers' green preference is small, consumers' green preference is negatively correlated with social welfare. When consumers' green preference is large, consumers' green preference is positively correlated with social welfare. (2) Corporate social responsibility is conducive to improving the level of social welfare, not conducive to the increase of corporate profits. (3) When the reward and punishment intensity is small, the reward-penalty policy cannot effectively motivate the firm to assume social responsibility. Only when the reward and punishment reaches a certain level, the mechanism can have an incentive effect on the firm, and the government can actively implement the mechanism. (4) When the market scale is small, the adoption of end-of-pipe pollution control technology is more beneficial to the firm; When the market scale is large, it is beneficial for the firm to adopt clean technology. (5) If the efficiency of end-of-pipe pollution control and emission reduction is much higher than that of clean process, the firm should choose end-of-pipe pollution control technology, otherwise choose clean process. [ABSTRACT FROM AUTHOR]

This paper explores a two-level prefabricated building closed-loop supply chain (CLSC) comprising a retailer and a prefabricated building manufacturer (PBM) under carbon cap-and-trade legislation and the government subsidies of carbon emission reduction (CER). In this CLSC, the PBM and the retailer recycle used products through their independent recycling channels. The optimum pricing and CER strategies within both decentralized and centralized systems, respectively, are analyzed. The Stackelberg game is used in the decentralized system to determine the optimum PBM's CER level and the retailer's pricing. By analysis, it concludes that increasing the carbon trading price can stimulate prefabricated construction corporations to improve their CER level, and that the government subsidy rate has a great effect on the profits of the PBM. Numerical examples with sensitivity analysis are used to further evaluate the roles of important factors in the optimum CER and pricing solutions of the prefabricated building CLSC in two dissimilar systems. [ABSTRACT FROM AUTHOR]

As the largest carbon dioxide emitter, China is working towards the direction of a green economy. As an irreplaceable part of establishing a green economy, the low-carbon city pilot (LCCP) policy is implemented in many large cities in China, and the scope of implementation will be further expanded. However, to date, there has been an absence of empirical studies basing on prefecture-level cities about the evaluation of China's LCCP policy. Evaluating and optimizing the LCCP policy is constructive to achieve the goal of China's green economic transition. In this paper, we evaluated the effect of the LCCP policy on China's low-carbon economic transition by using the difference-in-difference (DID) approach which can effectively alleviate endogenous problems and better evaluate this effect and the panel data of 210 prefecture-level cities in China from 2008 to 2016. The empirical analysis revealed that the LCCP policy inhibited China's low-carbon economic transition in general. Specifically, the policy worked well in the eastern region but failed in the central region and western region by studying the regional heterogeneity and influence mechanism. The reason is that the LCCP policy can stimulate low-carbon innovation with the help of innovation offset effects in the eastern region, but it failed to do so in the central region and western region. In addition, this paper analyzed the performance of three types of policy tools adopted by local governments to implement the policy, we found that market-economic tools are valuable to improving the low-carbon economic transition in pilot areas, but command-mandatory tools and voluntary tools have failed to achieve the expected objectives. The research results of this article can provide policy recommendations for optimizing the low-carbon policy and provide a reference for countries that are determined to develop a green economy. [ABSTRACT FROM AUTHOR]

Purpose: There is rising interest in Industry 4.0 as a factor in the competitiveness of the organization. Although many companies are aware of the importance of Industry 4.0, the development of such initiatives in Colombia is slow. Consequently, this research investigates the impact of additive technologies as part of the Industry 4.0 concept on operational effectiveness and, therefore, the competitiveness of the organization and tries to establish the factors that hinder the adequate implementation of such new, innovative technologies. Design/Methodology/Approach: Structural equation modeling was used to analyze the antecedents and outcomes of operational effectiveness. To this end, 946 usable questionnaires were collected from managers and personnel from Colombian organizations. Findings: Initial findings show that management is aware of Industry 4.0 concepts and implements strategies for such initiatives. Nevertheless, neither process innovation nor additive technologies have a significant impact on operational effectiveness and therefore on the competitiveness of the organization. Practical implications: The implementation of new innovative technologies requires the closure of the digital gap between urban and rural areas and between large and medium and small enterprises. Similarly, the concept of Industry 4.0 as a new, innovative manufacturing concept requires a transversal implementation to increase the competitiveness of the organization. Originality/Value: The value of this paper lies in discussing the current technological and human capabilities and strategies that Colombian organizations, as an example of a developing nation, should improve to leverage the benefits of Industry 4.0 to remain competitive. The results are probably generalizable to other regions in developing countries throughout the world. [ABSTRACT FROM AUTHOR]

The low-carbon city pilot policy is an environmental regulation aimed at reducing carbon emissions at the municipal level. Previous research mostly focused on evaluating its environmental performance and discovered it could enhance pilot cities' low-carbon innovation. However, the effects of the low-carbon city pilot policy on firm-level low-carbon innovation and their economic impact have yet to be investigated. This research uses a sample of Chinese A-share listed firms and the difference-in-difference method to examine the effect of the low-carbon city pilot policy on firms' low-carbon innovation. The baseline regression showed that the low-carbon city pilot policy could greatly encourage low-carbon innovation among firms in pilot cities. The mechanism analysis demonstrated that this improvement effect is attained by easing these firms' financing constraints. According to the heterogeneity analysis, we discovered that state-owned firms and firms situated in pilot zones with municipal secretaries who have larger promotion incentives are more susceptible to this policy. Additionally, the research on this policy's economic impact revealed that, following its adoption, the market value and comparative advantages of the firms in the pilot areas also increased. The findings of this study have implications for the enhancement and national expansion of low-carbon policies adopted at the city level. [ABSTRACT FROM AUTHOR]

Emission trading scheme (ETS), the most popular market-based instrument, is widely used to solve carbon emission problems in the world. With the development of carbon market, carbon asset has been a popular financial product to invest and the risk management becomes important for government, regulated enterprises and other investors. As carbon prices have tail characteristics, this paper explores the extremal risks between carbon markets in US, Europe and China using tail dependence correlation coefficients. The empirical analysis demonstrates the tail dependence structure between carbon markets in US. and Europe is the same sign, which indicates that it is unwise to hold these two carbon assets as a portfolio. Moreover, the co-movements between European Union Emission Trade Scheme (EU ETS) and China's carbon markets are partly significant, and the operation mechanisms in China should be improved. In addition, the tail dependence test among the carbon pilots in China shows diversity. Hubei carbon trading pilot, located in central China, has extremal dependence with all other selected pilots for its regulatory program operation. The findings give insight to the carbon market regulars to improve the operation mechanism and are also useful for the investors to manage their portfolios, policymakers to make practically applicable regulations, and relevant organizations to develop procedures. [ABSTRACT FROM AUTHOR]

Global climate change has caused a series of environmental problems, green technology innovation is necessitating strategic responses, but the impact of low-carbon city pilot policy on urban green technology innovation is unclear. Based on panel data from 285 Chinese cities during 2005–2022, this study employs the Difference in Difference method to examine the impact of low-carbon city policy on urban green technology innovation. The results show that (1) The low-carbon city pilot policy promotes urban green technology innovation. (2) The low-carbon city pilot policy promotes urban green technology innovation through government green input and public engagement. (3) New infrastructure enhances the impact of low-carbon city pilot policy on quantity of green technology innovation. (4) Compared with the Yangtze River Economic Belt, the low-carbon city policy has a greater influence on urban green technology innovation in the Yellow River Basin.The findings provide policy insights for the construction of low-carbon pilot cities. [ABSTRACT FROM AUTHOR]

Can the information technology revolution lead to carbon emission reduction for firms? This study extends the limited evidence in the literature and investigate the role and mechanism of digital inclusive finance on enterprises' carbon emissions using panel data of 247 prefectural-level cities and 6019 industrial enterprises in China. Our findings indicate that digital inclusive finance can promote enterprise carbon emission reduction, and this effect remains significant after the instrumental variable estimation test. The effect has regional heterogeneity and the development of digital inclusive finance in the area east of Hu Huanyong line has a significant impact on reducing enterprise carbon emission. The role of digital inclusive finance is heterogeneous in enterprise ownership, with a remarkable effect in non-state-owned enterprises. Sub-dimension analysis indicates that the breadth of coverage, depth of use, and degree of digitalization of digital inclusive finance have differential effects on reducing enterprise carbon emissions. The stepwise regression method shows that the impact of digital inclusive finance on enterprise carbon emissions can be passed through effect of technological progress, environmental protection investment and financing constrain. This study has significant reference value for evaluating the impact of financial inclusion and policy implications in formulating differentiated strategies for achieving carbon emission reduction efficiency in enterprises. [ABSTRACT FROM AUTHOR]

This study is aimed at investigating the asymmetric and time-frequency co-movements and the hedge or safe-haven properties of carbon efficient indices, the MSCI ACWI Sustainable Impact, and MSCI World EGS indices, in relation to technology and innovation-themed investments. In doing so, the ADCC-GJR-GARCH and wavelet coherence techniques are applied to a daily return series ranging from January 2019 to January 2023. Findings of the ADCC-GJR-GARCH model show negative and insignificant asymmetric linkage among underlying indices during the sample period. The S&P 500 carbon efficient index (CEI) acts as a strong hedge or safe-haven for technology and innovation-themed indices during tranquil and tumultuous periods. The MSCI ACWI Sustainable Impact, MSCI World EGS, and carbon efficient indices except for S&P 500 CEI exhibit weak hedge or safe-haven attributes. Wavelet coherence reveals negative (positive) co-movements between the thematic and carbon efficient indices in short-term (medium-term and long-term) horizons with consistent leading behavior of thematic indices to carbon efficient indices outcomes. It justifies the presence of short-lived hedging or safe-haven characteristics in the thematic domain for investors. These strong and weak hedge or safe-haven characteristics of low carbon and sustainability indices reveal that adding low carbon efficient and sustainable investments to a portfolio result in considerable diversification benefits for investors who tend to take minimal risk in both tranquil and tumultuous periods. The current findings imply that financial institutions, thematic investing companies, and governments need to encourage carbon efficient technology transfer and innovation-themed investments by increasing the fund allocations in underlying asset classes. Policy-making and regulatory bodies can encourage investors to make carbon-efficient and thematic investments and companies to issue carbon-efficient stocks or investments to safeguard social and economic risks during fragile periods. These investments can offer greater opportunities to combat the intensity of economic shocks on portfolios for responsible or sustainable investors. [ABSTRACT FROM AUTHOR]

In tropical dry forests, studies on wood anatomical traits have concentrated mainly on variations in vessel diameter and frequency. Recent research suggests that parenchyma and fibers also play an important role in water conduction and in xylem hydraulic safety. However, these relationships are not fully understood, and wood trait variation among different functional profiles as well as their variation under different water availability scenarios have been little studied. In this work, we aim to (1) characterize a set of wood anatomical traits among six selected tree species that represent the economic spectrum of tropical dry forests, (2) assess the variation in these traits under three different rainfall regimes, and (3) determine the relationships between wood anatomical traits and possible functional trade-offs. Differences among species and sites in wood traits were explored. Linear mixed models were fitted, and model comparison was performed. Most variation occurred among species along the economic spectrum. Obligate deciduous, low wood density species were characterized by wood with wide vessels and low frequency, suggesting high water transport capacity but sensitivity to drought. Moreover, high cell fractions of carbon and water storage were also found in these tree species related to the occurrence of abundant parenchyma or septate fibers. Contrary to what most studies show, Cochlospermum vitifolium, a succulent tree species, presented the greatest variation in wood traits. Facultative deciduous, high wood density species were characterized by a sturdy vascular system that may favor resistance to cavitation and low reserve storage. Contrary to our expectations, variation among the rainfall regimes was generally low in all species and was mostly related to vessel traits, while fiber and parenchyma traits presented little variation among species. Strong functional associations between wood anatomical traits and functional trade-offs were found for the six tree species studied along the economic spectrum of tropical dry forests. [ABSTRACT FROM AUTHOR]

This study narrows its focus to the Yangtze River Delta, an important region in China known for its advancements in both digital economy and low-carbon technology. In contrast to previous studies, we also examine the heterogeneous effects between central and non-central cities, as well as the role of local financial development, when analyzing the impact of the digital economy on low-carbon innovation. Based on the data of 41 cities from 2011 to 2019, we find a significant direct promoting effect of the digital economy on low-carbon innovation. Furthermore, the development of the digital economy indirectly enhances low-carbon innovation through local financial development. The heterogeneous analysis reveals a positive impact of the digital economy on low-carbon innovation in both central and non-central cities, with a stronger effect observed in non-central cities. These findings suggest several policy recommendations, including promoting digital economy and finance, green finance, and fostering regional integration in the Yangtze River Delta. [ABSTRACT FROM AUTHOR]

Five national urban agglomerations are selected according to the Fourteenth Five-Year Plan, namely the Yangtze River Delta, the Pearl River Delta, Beijing-Tianjin-Hebei, the Middle reaches of the Yangtze River, and Chengdu-Chongqing. The study on synergistic effects of such national strategic planning urban agglomerations, defined as coordinated degrees, and their time-series trends from 2016 to 2021 is significant for the practice of the national "double carbon" goal. Spatial differentiation of coordinated degree in five agglomerations is analyzed based on the Theil Index, along with regional linkage strength of coordinated degree under the gravity model. Conclusions include: (1) a downward trend is shown from 2016 to 2021 for the coordinated degree, along with the Pearl River Delta is the best among the five agglomerations; (2) the Middle reaches of the Yangtze River is the highest, followed by the Pearl River Delta and the Yangtze River Delta of coordinated degree in 2021; (3) the main cause of downwards in coordinated degree combined by a stable decline in carbon emissions and fluctuating increase in pollutants; (4) intra-regional differences in the Yangtze River Delta and the Middle reaches of the Yangtze River are relatively large, compared with the smallest in the Pearl River Delta measured by Theil Index; (5) coefficients of variation are relatively higher in the Middle reaches of the Yangtze River and the Yangtze River Delta, followed by the Beijing-Tianjin-Hebei, the Pearl River Delta and Sichuan-Chongqing urban. Consequently, countermeasures are proposed from the perspective of government, including technology and regional cooperation, policy innovation by overall coordination, synergy promotion by technological innovation, and regional synergy by win-win cooperation. [ABSTRACT FROM AUTHOR]

We calculate the embodied carbon emissions of China's through the multiregional input–output (MRIO) method, then we construct the interprovincial embodied carbon flow networks of China's exports based on the mean threshold, and the application of complex network analysis to conduct a detailed examination of the overall characteristics, key nodes and edges, and community structure of China's interprovincial embodied carbon flow network. We extended the embodied carbon flow network analysis at the provincial level. The results demonstrated the following: (1) The interprovincial embodied carbon flow network of China's exports has small-world and scale-free characteristics. The node degree probability distribution curves for the networks obviously conformed to a decreasing power law distribution, indicating that a few industrial sectors carry a large amount of embodied carbon and suggesting that reducing the embodied carbon of China's exports could yield twice the results with half the effort as long as attention is paid to a few sectors. (2) The key nodes and edges in the networks show that industrial sectors and production chains such as the power and heat production and supply industry, the petroleum processing, coking, and nuclear fuel processing industry, and the metal smelting and calendering industry play the role of key "bridges" in the entire network, among which Guangdong, Hebei, Jiangsu, Inner Mongolia, and Shanxi are important node provinces and the main flow paths for the generation of embodied carbon in national exports. These industrial sectors and production chains should bolster their policies to encourage the innovation of carbon emission reduction technologies and decrease carbon emissions, so as to reduce the embodied carbon of national exports on a large scale. (3) The number of communities firstly increased then decreased from 2007 to 2017, while the aggregation coefficient of the node and correlation density within first community displayed firstly downward then upward trends, reflecting firstly decentralization then centralization of the interprovincial embodied carbon flow. [ABSTRACT FROM AUTHOR]

Purpose: Immobilization of skeletal muscles causes muscle atrophy, muscle contracture, and muscle pain, the mechanisms of which are related to macrophage accumulation. However, muscle contractile exercise through a belt electrode device may mitigate macrophage accumulation. We hypothesized that such exercise would be effective in preventing myofiber atrophy, muscle contracture, and muscular pain. This study tested this hypothesis in immobilized rat gastrocnemius muscle. Materials and methods: A total of 32 rats were divided into the following control and experimental groups: immobilization (immobilized treatment only), low-frequency (LF; immobilized treatment and muscle contractile exercise with a 2 s (do) /6 s (rest) duty cycle), and high-frequency (HF; immobilized treatment and muscle contractile exercise with a 2 s (do)/2 s (rest) duty cycle). Electrical stimulation was performed at 50 Hz and 4.7 mA, and muscle contractile exercise was applied to the lower limb muscles for 15 or 20 min/session (once daily) for 2 weeks (6 times/week). After the behavioral tests, the bilateral gastrocnemius muscles were collected for analysis. Results: The number of macrophages, the Atrogin-1 and MuRF-1 mRNA expression, and the hydroxyproline content in the HF group were lower than those in the immobilization and LF groups. The cross-sectional area (CSA) of type IIb myofibers in the superficial region, the PGC-1α mRNA expression, and the range of motion of dorsiflexion in the HF group were significantly higher than those in the immobilization and LF groups. The pressure pain thresholds in the LF and HF groups were significantly higher than that in the immobilization group, and the nerve growth factor (NGF) content in the LF and HF groups was significantly lower than that in the immobilization group. Conclusion: Muscle contractile exercise through the belt electrode device may be effective in preventing immobilization-induced myofiber atrophy, muscle contracture, and muscular pain in the immobilized rat gastrocnemius muscle. [ABSTRACT FROM AUTHOR]

Soft and pliable conductive polymer composites hold promise for application as bioelectronic interfaces such as for electroencephalography (EEG). In clinical, laboratory, and real-world EEG there is a desire for dry, soft, and comfortable interfaces to the scalp that are capable of relaying the μV-level scalp potentials to signal processing electronics. A key challenge is that most material approaches are sensitive to deformation-induced shifts in electrical impedance associated with decreased signal-to-noise ratio. This is a particular concern in real-world environments where human motion is present. The entire set of brain information outside of tightly controlled laboratory or clinical settings are currently unobtainable due to this challenge. Here we explore the performance of an elastomeric material solution purposefully designed for dry, soft, comfortable scalp contact electrodes for EEG that is specifically targeted to have flat electrical impedance response to deformation to enable utilization in real world environments. A conductive carbon nanofiber filled polydimethylsiloxane (CNF-PDMS) elastomer was evaluated at three fill ratios (3, 4 and 7 volume percent). Electromechanical testing data is presented showing the influence of large compressive deformations on electrical impedance as well as the impact of filler loading on the elastomer stiffness. To evaluate usability for EEG, pre-recorded human EEG signals were replayed through the contact electrodes subjected to quasi-static compressive strains between zero and 35%. These tests show that conductive filler ratios well above the electrical percolation threshold are desirable in order to maximize signal-to-noise ratio and signal correlation with an ideal baseline. Increasing fill ratios yield increasingly flat electrical impedance response to large applied compressive deformations with a trade in increased material stiffness, and with nominal electrical impedance tunable over greater than 4 orders of magnitude. EEG performance was independent of filler loading above 4 vol % CNF (< 103 ohms). [ABSTRACT FROM AUTHOR]

Effective methods for delivering bioprobes into the cells of intact plants are essential for investigating diverse biological processes. Increasing research on trees, such as Populus spp., for bioenergy applications is driving the need for techniques that work well with tree species. This report introduces vertically aligned carbon nanofiber (VACNF) arrays as a new tool for microdelivery of labeled molecules to Populus leaf tissue and whole plants. We demonstrated that VACNFs penetrate the leaf surface to deliver sub-microliter quantities of solution containing fluorescent or radiolabeled molecules into Populus leaf cells. Importantly, VACNFs proved to be gentler than abrasion with carborundum, a common way to introduce material into leaves. Unlike carborundum, VACNFs did not disrupt cell or tissue integrity, nor did they induce production of hydrogen peroxide, a typical wound response. We show that femtomole to picomole quantities of labeled molecules (fluorescent dyes, small proteins and dextran), ranging from 0.5–500 kDa, can be introduced by VACNFs, and we demonstrate the use of the approach to track delivered probes from their site of introduction on the leaf to distal plant regions. VACNF arrays thus offer an attractive microdelivery method for the introduction of biomolecules and other probes into trees and potentially other types of plants. [ABSTRACT FROM AUTHOR]