Assessing the impact of energy internet and energy misallocation on carbon emissions: new insights from China

Can internet development improve carbon emission efficiency for manufacturing? The role of market integration

Improving carbon emission efficiency of manufacturing is important for promoting low-carbon development and achieving harmonious coexistence between humans and nature. In this study, we use the Global-MinDS model to measure the carbon emission efficiency of China's provincial manufacturing from 2011 to 2020. To do so, we construct a mathematical model to analyze the mechanism of the interaction among internet development, market integration, and carbon emission efficiency of manufacturing. Then, we empirically examine the carbon emission reduction effect of internet development using the Bartik instrument variable method and verify the significance of market integration. Our results show that internet development can significantly improve the carbon emission efficiency of manufacturing, promoting manufacturing low-carbon transformation. Carbon emission reduction effect of internet development is characterized by heterogeneity in market integration, environmental regulation, and policy intensity. This means that the impact of internet development is more pronounced in lower integration regions, higher environmental regulation intensity and in big data comprehensive experimental zone. Intermediate mechanism tests show that internet development can promote market integration by reducing external transaction costs, so as to play a carbon emission reduction effect in the market mechanism. Our study provides empirical evidence for the carbon emission reduction effect of the digital economy and offers valuable references for effectively promoting the low-carbon transformation of manufacturing in China from the perspective of unified market.

The effect of green fiscal policy on green technological innovation: evidence from energy saving and emission reduction fiscal policy

The "National Comprehensive demonstration of Energy Saving and Emission Reduction Fiscal Policy" (ESER policy) is a green fiscal policy to facilitate China's green sustainable development. Green sustainable development is facilitated by green technological innovation. Thus, evaluating the influence of the ESER policy on green technological innovation is essential. This study employs the difference-in-differences model to assess the ESER policy effects. The findings suggest that the ESER policy facilitates green technological innovation, but the policy effect has inhibited green technology innovation in neighboring cities. Mechanism analysis indicates that this policy effect is realized through increasing scientific research investment intensity and promoting industrial structure upgrading. Heterogeneity analysis indicates that this policy is effective in facilitating green technological innovation when performed in eastern, non-old industrial base, non-resource-based, and high green innovation level cities. In addition, the ESER policy implemented in conjunction with innovation policy can be more effective in promoting green technological innovation. These results provide valuable insights for improving the ESER policy and offer helpful guidelines for green fiscal policymaking in other countries.

Spatial-temporal pattern and spatial convergence of carbon emission intensity of rural energy consumption in China

Based on the panel data of 30 provinces (municipalities and autonomous regions) in China from 2005 to 2019, this paper uses Gini coefficient decomposition and kernel density estimation to investigate the regional differences and dynamic evolution trend of rural energy carbon emission intensity in China. Then, the convergence model is used to analyze the convergence characteristics and influencing factors of carbon emission intensity. The study found the following: (1) During the observation period, the carbon emissions of coal energy and oil energy were much higher than those of gas energy. The carbon emissions of rural energy consumption experienced three stages of development, and the carbon emission intensity showed a downward trend as a whole. The spatial distribution pattern of total carbon emissions present an "adder" distribution, and the spatial agglomeration phenomenon gradually strengthens with the passage of time. (2) The Gini coefficient of China's rural energy consumption carbon emission intensity shows a trend of "Inverted N-shaped." The Gini coefficient of carbon emission intensity in the eastern and northeastern regions shows an increasing trend, while the Gini coefficient of carbon emission intensity in the western and central regions shows a downward trend. The super variable density is the main source of carbon emission intensity difference. The peak value of the main peak of the nuclear density curve of the carbon emission intensity increased significantly, the bimodal form evolved into a single peak form, and the density center moved to the left. (3) The carbon emission intensity of rural energy consumption in the whole, central, and western regions of China has the characteristic of σ convergence, while the carbon emission intensity in the eastern and northeastern regions does not have the characteristic of σ convergence. There is a significant spatial positive correlation in the carbon emission intensity, there is also a significant β convergence characteristic, the speed of conditional β convergence is significantly higher than that of absolute β convergence, and the spatial interaction will further improve the convergence speed. Industrial structure, industrial agglomeration, and energy efficiency will increase the convergence speed. In terms of sub-regions, the conditional convergence rate of carbon emission intensity in the four regions shows a decreasing trend in the northeast, central, eastern, and western regions.

Does digital economy curb carbon intensity? New insights from China

China is in the period of vigorously developing the "digital economy" and "low-carbon economy," facing the double pressure of realizing the "dual-carbon" target and maintaining stable economic growth. This paper tests the role of the digital economy (DIEC) in the process of carbon emission reduction for the advancement of low carbon economy based on this issue from the perspective of carbon intensity (CI) by constructing a fixed effects and mediation effects model using data from 30 areas from 2011 to 2021. The study results show that at the national level, the advancement of DIEC significantly inhibits CI, and the conclusion still holds after various robustness tests. From the geographic region level, the suppression of CI by digital economic advancement has the most substantial impact in the central region. Although the eastern and western areas have similar results, the significance level is higher in the east region. When considering the economic development level, the impact of DIEC on CI is more significant in areas with lower economic development than those with higher economic growth. In analyzing the path of the DIEC affecting CI, it is found that the DIEC mainly inhibits CI by promoting technological advancement and reducing energy consumption intensity.

Carbon neutrality along the global value chain: an international embedded carbon network analysis

Using the value-added method in the global input-output framework, embedded carbon transfers between economies are measured. Then, the international embedded carbon network (IECN) models are constructed and analyzed to reveal the real pattern of the IECN. Influential factors of the IECN are further explored with Quadratic Assignment Procedure (QAP). The main findings are as follows: first, the IECN has the characteristics of small world and scale-free. Developed economies led by the USA have high centrality indicators and always occupy the core position in the network; the network position of China and India has risen significantly with different network characteristics. Second, the subgroup relationships of the carbon network implied by international trade are becoming more and more complex and diverse, economies' participation in the global carbon chain is gradually increasing, and the number of edge nodes are decreasing. Third, the results of QAP analysis show that in addition to the negative impact of geographical distance on embedded carbon transfers between economies, inter-country trade agreement relations, differences in industrial structure, energy intensity, environmental regulation, economic size, and population size have a positive impact on embedded carbon transfers between economies. These findings can provide important practice implications for the global carbon neutrality.

Linking energy crises and solar energy in China: a roadmap towards environmental sustainability

Fossil fuels are the primary energy sources of China, which are not only expensive but have adverse environmental impacts. To cope with this situation, the Chinese government wants to fulfil 25% of its energy consumption by non-fossil fuels by 2030. In this perspective, we selected the solar sources of the country and collected solar irradiation data for one year in the six big cities of China in 2022. For the analysis of data and assessing the effectiveness of photovoltaic (PV), RETScreen and MATLAB were utilized. A further step was taken by performing the life cycle assessment (LCA) to scrutinize the different features of solar energy, including fuel consumption, price, average lifetime, maintenance and operation expenses, land requirements, and greenhouse gas emissions. Results reveal that all these cities have enormous solar power potential. However, the highest solar power (0.27 kW) is generated in Nanchang city, while the lowest power (0.21 kW) is generated in Sanya city. Solar energy is durable and has a good average lifespan but can be costly, as PV panels lose efficiency due to dust and pollution. The regular cleaning of PV panels, in turn, demands substantial cost. Based on research results, significant policy suggestions have been recommended to fulfil the country's energy demand on its way to a future of sustainable development.

All roads lead to Rome? The impact of heterogeneous green finance on carbon reduction of Chinese manufacturing enterprises

Based on the system theory and Pareto efficiency theory, this paper, based on the data of listed companies in China's A-share manufacturing industry in 2011-2022, explores the impact of market-driven green finance and government-guided green finance on the carbon emission intensity of manufacturing enterprises, and analyzes the intermediary role of debt financing cost. A negative "U" relationship exists in market-driven green finance/government-guided green finance and the carbon emission intensity of manufacturing enterprises. Further research shows that under the higher debt financing cost, market-driven green finance played a weaker carbon reduction effect. The heterogeneity analysis found that market-driven green finance can have a significant non-linear impact of "promoting growth first and weakening later" on the carbon emissions of energy-saving and environmental protection enterprises, large enterprises, and enterprises with high human capital levels. Government-guided green finance has a significant non-linear impact on non-energy-saving and environmental protection enterprises and small enterprises. This paper provides the theoretical basis and practical inspiration for the government to formulate relevant low-carbon development policies and promote the innovation of green financial tools in the financial market.

Can bioenergy act as an entrepreneurial opportunity for the sustainable economic development of an emerging economy? A socio-technical approach

Challenges in adopting renewable energy have become significant roadblocks to the country's sustainable progress. There is a shortage of studies examining how adopting biogas energy plants affects entrepreneurship in Pakistan's off-grid areas. This study aims to address this gap in the literature by investigating bioenergy as an entrepreneurial opportunity for the sustainable economic development of an emerging economy. Primary data comprising 305 respondents was used in Punjab Province by employing an inclusive questionnaire survey. The partial least square structural equation modeling (PLS-SEM) technique validates the model and analyzes the designated hypotheses. Empirical outcomes reveal that enhanced social and entrepreneurial prosperity adopting biogas plants, sustainable economic development of entrepreneurial businesses adopting biogas plants, and adoption in entrepreneurship improve the standard of living positively and significantly associated with intention to enhance entrepreneurship performance through biogas energy adoption. On the contrary, the production-cost reduction of adopting biogas plants in entrepreneurial businesses had no significant effect on intention to improve entrepreneurship performance through biogas energy adoption. Meanwhile, the intention to enhance entrepreneurship performance through biogas energy adoption positively mediates the relationship among enhanced social and entrepreneurial prosperity adopting biogas plants, sustainable economic development of entrepreneurial businesses adopting biogas plants, biogas plant adoption in entrepreneurship improves the standard of living, and economic development of entrepreneurial activities adopting biogas technology. Correspondingly, social media and word of mouth significantly moderate the relationships between the intention to enhance entrepreneurship performance through biogas energy adoption and the economic development of entrepreneurial activities adopting biogas energy. The results of this study show how crucial it is to change societal norms surrounding entrepreneurship, raise entrepreneurs' awareness of these issues, reform regulatory systems, and emphasize the benefits of entrepreneurial activities offered by biogas energy plants that grow entrepreneurs' standard of living. Finally, the study's limitations and recommendations for additional studies are highlighted.

Energy and air? The impact of energy efficiency improvement on air quality in China

The global economic growth is hindered by resources shortage, energy demand, air pollution and climate. Energy efficiency can reduce some pollutants while potentially increase others. This study refers to sulfur dioxide (SO2), nitrogen oxides (NOx), and dust and smoke (DS) as primary pollutants to distinguish it from secondary ones. The influence of energy efficiency, socioeconomic, and natural climatic factors on air quality is analyzed under the theory of STIRPAT. It is highly coupled between energy efficiency and the spatial distribution of air quality. Increased energy efficiency can improve air quality by reducing SO2 and NOx, but the impact on DS is insignificant. Air pollutants decrease by about 0.531% for every 1% increase in temperature and 0.105% for every 1% increase in precipitation. Consumption will reduce air pollution, and there is an inverted U-shaped relationship between population density, economic scale, urbanization, technology innovation, and air pollution. It is worth mentioning that this work adds temperature and precipitation to the STIRPAT as natural climatic factors, analyzing the impact of energy efficiency on air pollution under the two-factor restrictions of socioeconomic and natural climatic factors. Finally, management suggestions are made to improve air quality.

The drivers of carbon emissions in China: the perspective of fiscal decentralization

Fiscal decentralization determines government behavior considerably by being a major factor influencing China's carbon emissions. We analyze the impact of fiscal decentralization on carbon emissions on basis of the dataset of 30 Chinese areas for the period 2008 to 2020. We reveal that fiscal decentralization significantly raises carbon emissions, but worsens carbon emission efficiency. The impact of fiscal decentralization on carbon emissions varies significantly by geographical location and economic development level shocks. Local governments increase the expenditure on economic services while reducing the expenditure on basic public services as a result of the fiscal decentralization scheme, which is an important reason why the carbon emission level cannot be effectively improved. As such, it is necessary to keep pace with the times, and build a service-oriented government, and capitalize on the capabilities of local governments in terms of their service duties so as to maximize carbon reduction.

The digital economy and the green and high-quality development of the industry-a study on the mechanism of action and regional heterogeneity

Consistently rising carbon emissions in the global economy make it more challenging to meet the goals of the Paris climate agreement. Knowing what factors play a role is essential to help shape strategies to reduce carbon emissions. While there is a wealth of material on how GDP expansion correlates with increases in carbon emissions, little is known about how democracy and renewable energy could improve environmental conditions in developing nations. The purpose of this article was to use fair data to assess the effect of renewable energy and green technology advances on carbon neutrality in 23 provinces across China from 2005 to 2020. The research used the dynamic ordinary least square, the fully modified ordinary least square, and the two-step GMM to determine that digitalization, industrial development, and health expenditures result in lower carbon emissions. Urbanization, tourism, and per capita income in certain Chinese provinces also drove carbon emissions. The study also showed that the impact of these factors on carbon emissions varies depending on the amount of economic growth. Environmental pollution is reduced due to the digitalization of tourist and healthcare costs, industrial development, and urbanization. According to the study's findings, we advise these nations to seek economic growth and invest in health care and renewable energy initiatives.

The current developments and future prospects of solar photovoltaic industry in an emerging economy of India

Solar photovoltaic (PV) is a novel and eco-friendly power source. India's vast solar resources present tremendous solar energy use prospects. The solar PV growth in India has spanned over fifty years, with a significant increase during the past decade. To meet the requirements of the rapidly expanding PV power market in India, it is essential to define, scrutinize, and comprehend the industry's development path and features. This study comprehensively analyzes the current state of solar resources, the future growth prospects of the solar PV sector, and the major factors that influence the industry's smooth growth. The study relates to the following five major factors: technological R&D, industrial planning, rules and regulations, power pricing guidelines, and projects enticement programs. To explore these elements, a multifaceted approach consisting of an inclusive literature research, statistical data inquiry, legislation review, and regulatory and policy analysis is undertaken. Analyzing the usual occurrences, the development process, and the features of the five elements permits the growth of development route models. The findings of this study provide information regarding the current development and future prospects of PV power sector in India. In today's rapidly changing social, economic, and technological landscapes, policymakers have the opportunity to gain better understanding from the ever-evolving practices and new advances in the business paradigm.

When will China's industrial carbon emissions peak? Evidence from machine learning

The manufacture of products in the industrial sector is the principal source of carbon emissions. To slow the progression of global warming and advance low-carbon economic development, it is essential to develop methods for accurately predicting carbon emissions from industrial sources and imposing reasonable controls on those emissions. We select a support vector machine to predict industrial carbon emissions from 2021 to 2040 by comparing the predictive power of the BP (backpropagation) neural network and the support vector machine. To reduce noise in the input variables for BP neural network and support vector machine models, we use a random forest technique to filter the factors affecting industrial carbon emissions. The statistical results suggest that BP's neural network is insufficiently adaptable to small sample sizes, has a relatively high error rate, and produces inconsistent predictions of industrial carbon emissions. The support vector machine produces excellent fitting results for tiny sample data, with projected values of industrial carbon dioxide emissions that are astonishingly close to the actual values. In 2030, carbon emissions from the industrial sector will have reached their maximum level.

Influencing factors of consumers' buying intention of solar energy: a structural equation modeling approach

Due to China's massive usage of fossil fuels, climate change concerns have become serious challenges to the country's sustainable development. Despite the fact that China has effectively employed solar technology to address these problems, there is a paucity of research examining consumers' intention to adopt solar energy in the rural region of China. This study intends to fill this gap in the literature by studying consumers' buying intentions for solar energy in rural China for household purposes. Additionally, the study added to the theory of planned behavior by adding three new variables, namely, environmental knowledge, environmental concern, and beliefs about the benefits of solar energy. Primary data were collected from 847 respondents in Hebei Province using a comprehensive questionnaire survey. Structural equation modeling was employed to examine the data. Empirical results revealed that attitude, environmental knowledge, subjective norm, perceived behavioral control, and beliefs about the benefits of solar energy positively influence buying intention of solar energy. On the contrary, environmental concern had no significant effect on buying intention for solar energy. Study outcomes emphasize the critical significance of changing societal norms, boosting consumer awareness, redesigning regulatory mechanisms, and stressing the benefits provided by solar power through coherent and persistent efforts while simultaneously enhancing environmental sustainability practices.

Towards the road of eco-efficiency improvement: evidence from China's economic and technological development zone

The economic and technological development zone (ETDZ) serves an essential role in driving green development and ecological civilization. Therefore, it is crucial to investigate the impact of ETDZs on eco-efficiency for sustainable development. This paper investigates the impact of the establishment of ETDZs on eco-efficiency by constructing a differences-in-differences (DID) model on the basis of 253 cities in China from 2004 to 2017 as the dataset. This paper also explores the possible intrinsic impact mechanisms through the channels of industrial structure and technological innovation by constructing a mediating effect model, and the heterogeneous effects of ETDZs on eco-efficiency from the perspectives of regional imbalance and city class heterogeneity. Statistical results report that ETDZs significantly positively affect eco-efficiency and such effects are most significant in the first year after the establishment of ETDZs. Industrial structure upgrading and technological innovation are essential role mechanisms for ETDZs to enhance eco-efficiency. Besides, the enhancement effect of ETDZs on eco-efficiency is only observed in the eastern part of the city, with an insignificant inhibitory effect in central and western parts of the cities. However, the establishment of ETDZs in cities with higher city classes is more beneficial to improve eco-efficiency.

Modeling the economic viability and performance of solar home systems: a roadmap towards clean energy for environmental sustainability

Energy is a necessary source of economic development and social prosperity, linked with primary production and consumption activities worldwide. In this regard, solar home systems (SHSs) are beneficial in two ways, i.e., saving vitality overheads and meeting the energy demand of small enterprises. The current study aims to evaluate the performance of adopting SHS to develop the small-scale industry in Pakistan. An inclusive questionnaire survey was conducted, and respondents were selected using the purposive sampling method. As a step further, we scrutinize the moderating role of awareness and understanding of technology between the node of adopting SHS and the monetary enactment of small-scale industry. We authenticate the model using a sample of 357 respondents by applying the partial least square structural equation modeling (PLS-SEM) technique. The results indicate that low-cost energy through SHSs has a progressive and substantial linkage with the demonstration of small-scale industry and enhances the quality of energy supply in Pakistan. Similarly, awareness and understanding of SHS significantly moderate the relationships between enhanced energy supply through SHS, the quality of SHS, and the performance of the small-scale industry. These findings provide a valuable guideline to the regulation developing authorities that more attention is needed to focus on SHS to further improve the performance of small-scale industry.

The impact of local government competition and green technology innovation on economic low-carbon transition: new insights from China

The government-led Chinese economic development system determines that local government competition is a significant factor affecting the economic low-carbon transition. Driving an economic development mode with green technology innovation as the core is the critical path to realizing an economic low-carbon transition. Consequently, it is of significant practical relevance to investigate the impact of local government competition and green technology innovation on the economic low-carbon transition under the government-led Chinese economic development system. This paper systematically explores the nexus between green technology innovation and economic low-carbon transition in terms of local government competition perspective using the system generalized method of moments, panel threshold model, and geographically weighted regression on the basis of a dataset of 30 provincial administrative areas in China from a period of 2006-2019. The results indicate that green technology innovation significantly promotes the economic low-carbon transition. Local government competition not only significantly dampens the economic low-carbon transition but also considerably inhibits the positive effect of green technology innovation on the economic low-carbon transition. A significant N-shaped association is evident between green technology innovation and the economic low-carbon transition when green technology innovation is applied as a threshold, while such association is insignificant when local government competition is used as a threshold. Compared with high-competition intensity areas, green technology innovation promotes economic low-carbon transition weaker in low- competition intensity areas, while local government competition inhibits economic low-carbon transition stronger. However, local government competition significantly inhibits the positive effect of green technology innovation on the economic low-carbon transition in low-competition intensity areas, while insignificant in high-competition intensity areas. The geographically weighted regression technique as a whole also verified the above results. Therefore, policymakers should not only increase research and development investment in green technologies, but also develop a regionally linked low-carbon emission reduction system to avoid ineffective competition among governments to facilitate the earlier fulfillment of the "dual carbon" goal.

Unintended consequences of heavy air pollution control: efficiency losses, resource misallocation, and firm innovation in China

Disentangling the heterogeneous effects of environmental regulations on firms' productivity and reducing the destructive effects of policies are important for achieving the goal of sustainable development. However, there is insufficient discussion of the micro-mechanisms of regulation. This study takes advantage of the good exogenous impact of China's first action plan, the Atmosphere Ten Articles, which has been formulated and implemented to solve prominent environmental problems, and constructs a difference-in-difference model based on the data of listed companies from 2012 to 2019. Results show that the policy generally has a significantly negative impact on the companies' TFP. This finding proved to be valid after a series of robustness tests, such as replacing the explained variables, eliminating the impact of penecontemporaneous policies, using propensity score matching, and applying instrumental variable methods. Due to the resource allocation mechanism, the policy undermines the companies' TFP, especially those in PM_2.5 regulatory areas and state-owned companies. However, the strict emission reduction constraint instead pushes firms to innovate, and as a result, the policy's innovation mechanism promotes firms' productivity, which eventually offsets the negative effects arising from resource allocation distortions.

Who Needs to Save Energy and Reduce Emissions? Perspective of Energy Misallocation and Economies of Scale

With the rapid development of the economy, human survival and socio-economic development are facing the severe challenges of climate threats. Global warming is one of the greatest threats to human survival and political stability that has occurred in human history. The main factor causing global warming is the extensive use of energy; therefore, it is imperative to spend more effort in energy conservation and emission reduction. In this context, this paper provides a reference and basis for decision making on emission-reduction paths through the perspective of energy input misallocation and economies of scale of CO2 emissions. The results show that for cities with relatively low energy inputs, the impact of excessive energy input on CO2 emissions is stronger than the effect of the scale of energy input on reducing CO2 emissions. Therefore, these cities need to prioritize energy conservation and emission reduction. On the other hand, in cities with large energy inputs, the impact of the scale of energy input on reducing CO2 emissions is more significant than the effect of excessive energy input on CO2 emissions. Therefore, these areas should also focus on energy conservation and emission reduction. The results of this paper have theoretical value and practical significance for scientifically implementing energy conservation and emission reduction strategies, as well as reasonably planning energy conservation pathways.

Can carbon emission trading pilot policy drive industrial structure low-carbon restructuring: new evidence from China

Industrial structure low-carbon restructuring is an essential channel to accelerate China's economic growth and fulfilling carbon emission reduction goals. Whether carbon emission trading pilot policy, as an influential carbon reduction instrument, fosters industrial structure low-carbon restructuring is of major significance to green economic development. This paper empirically investigates the shock of the carbon emission trading pilot policy on industrial structure low-carbon restructuring using the differences-in-differences (DID) and synthetic control method (SCM). Statistics reveal that sectors with low carbon productivity, such as electricity, steam, and hot water production and supply, ferrous metal smelting and pressing, etc., and sectors with high carbon productivity, such as electrical equipment and machinery, electronics and telecommunication equipment, etc. The industrial structure did not develop a stable trend of change before the 12th Five-Year Plan, but a stable trend of low-carbon restructuring emerged after such a period. Carbon emission trading pilot policy significantly facilitates industrial structural low-carbon restructuring. Carbon emission trading pilot policy inhibits energy-intensive industries in the industrial sector significantly, which promotes industrial structure low-carbon restructuring. Therefore, policymakers need to develop a nationwide carbon emission trading market that includes more industries to guide production factors to industrial sectors with high carbon productivity for industrial restructuring and dual carbon goals.

Effects of ICT diffusion on environmental pollution: analysis of industrial reallocation effects in China

The development of information and communication technology (ICT) has brought about fundamental changes in social progress worldwide. Using panel data from 288 Chinese cities for the period from 1999 to 2019, this study evaluates the effect of the pilot Broadband China Strategy (BCS) program on environmental pollution. We find that BCS significantly reduces environmental pollution, and that this effect is stronger in eastern China and in Chinese cities with higher financial progress or broadband development. Interestingly, the negative effect of BCS on environmental pollution decreases with the improvement of human capital in the cities. We further discuss industrial efficiency and reallocation mechanisms and ascertain that BCS affects environmental pollution in pilot cities not only through the efficiency mechanism as established in the existing literature but also through the industrial scale change and labor transfer between different industries, which we refer to as the industrial reallocation mechanism in this study. Specifically, via the industrial efficiency and reallocation mechanisms, the implementation of the BCS increases the scale and efficiency of the primary and tertiary industries but decreases the scale and efficiency of the secondary industry. This reduction in the secondary industry results in a decline in environmental pollution. It indicates that promoting the balanced development of a country's ICT infrastructure and pushing forward ICT diffusion can help alleviate environmental pollution by industrial reallocation and efficiency improvement, especially in nations with significant regional economic and technological differences.

Spatial-temporal differentiation and dynamic spatial convergence of inclusive low-carbon development: evidence from China

Promoting green and low-carbon development has become a global consensus. However, few studies have explored the scientific connotation and influencing factors of inclusive low-carbon development (ILCD). Based on the perspective of inclusive growth and sustainable development, this paper constructs an economic growth-social inclusion-low carbon development (ESC) analytical framework and uses the improved entropy weight method to estimate the ILCD level of 30 provinces in China from 2006 to 2020. Kernel density estimation, Moran's I index, and Dagum Gini coefficient decomposition are used to characterize the spatial and temporal variation patterns, and the variation coefficient and the dynamic spatial Durbin model are used to explore the dynamic spatial convergence characteristics. The results show that (1) ILCD in China is increasing steadily overall, but there is a significant spatial non-equilibrium characteristic of high in the east and low in the west. (2) The overall difference in ILCD shows a trend of fluctuation and narrowing, and the imbalance between regions is the primary source of the overall difference. (3) ILCD has significant path dependence and dynamic spatial convergence characteristics in the whole country and the three regions, and the spatial spillover effect tends to be good neighborliness. The rate of convergence shows a trend of national (4.77%) > western (2.33%) > eastern (1.97%) > central (0.96%), and the spatial convergence of the club is gradually becoming prominent. (4) The factors including economic development, technological innovation, urbanization level and human capital significantly affect ILCD, which also has regional heterogeneous. Therefore, it is necessary to break down administrative and market barriers, strengthen cross-regional cooperation and resource interconnectivity, and bring into play policy synergy to provide decision-making reference for achieving inclusive low-carbon development.

The impact of environmental information disclosure quality on green innovation of high-polluting enterprises

With the gradual increase of social awareness of environmental protection, environmental information disclosure has become the key for enterprises to accept social supervision and fulfill their social responsibility. This study examines the high-polluting enterprises that were listed on Chinese A-shares between 2008 and 2021. The influence of environmental information disclosure quality on green innovation is examined using ordinary least squares (OLS) as a benchmark model. The results show that the improvement of environmental information disclosure quality of high-polluting enterprises can significantly improve the quantity and quality of green innovation of enterprises and are mediated by alleviating financing constraints and enhancing cash reserves. Moreover, improving the quality of environmental information disclosure of highly polluting enterprises has a more significant contribution to the quantity and quality of green patents of non-state-owned enterprises, enterprises located in central and eastern China, and large enterprises. The findings of this paper provide theoretical support for achieving a "win-win" situation of environmental protection and green innovation.

Impact of Internet Development on Carbon Emissions in Jiangsu, China

Based on STIRPAT and panel threshold models, this study empirically tested the impact of Internet development on carbon emissions using panel data of Jiangsu Province from 2007 to 2020. The results showed that the carbon emissions intensity of the Internet development level had a significant promotion effect, while the carbon emissions intensity of technological progress showed a significant inhibition effect, but this inhibition effect is less than the promotion effect brought about by internet development. Considering the threshold effect, the development of the Internet had a double-threshold effect on carbon emissions in northern and central Jiangsu. Jiangsu Province should further accelerate the pace of Internet development and cross the threshold value as soon as possible. Finally, this study constructed a prediction model of emissions reduction to predict the future emissions reduction potential of Jiangsu Province and found that there was still much room for improvement regarding carbon emissions reduction in Jiangsu Province.

Does industrial intelligence improve resource misallocation? An empirical test based on China

Resource misallocation has become a new threat to China's high-quality economic development, and industrial intelligence may play an important role in optimizing resource allocation. Using panel data of 30 Chinese provinces from 2010 to 2020, the relationship between industrial intelligence and resource misallocation is studied using the spatial Durbin (SDM) model. To further explore the indirect effect of environmental pollution on resource misallocation, the interaction term between industrial intelligence and environmental pollution is added to test how environmental pollution affects the relationship between industrial intelligence and resource. The research results show that industrial intelligence in China has significant spatial correlation. Local industrial intelligence can improve the local resource allocation, but the intelligence of neighboring industries will intensify the resource misallocation in the region. The interaction between environmental pollution and industrial intelligence also further affects resource allocation, and the interaction term can intensify local capital allocation to improve local labor allocation, and the interaction term in the surrounding area will also improve capital and labor misallocation in the region. Heterogeneous results find that industrial intelligence exacerbates resource misallocation in regions with insufficient capital allocation, and the mediating effect of environmental pollution is not significant. However, in places with excess capital allocation, the development of industrial intelligence helps improve resource misallocation, while the mediating effect of environmental pollution is also present, and industrial intelligence can improve resource misallocation through the indirect effect of improving environmental pollution. Therefore, the policies of local industrial development policies need to fully consider the resource allocation situation in the region. At the same time, it needs to smooth the capital circulation mechanism, reduce the cost of capital allocation, establish a sound employment mechanism, and improve labor misallocation.

The nexus between digital finance and carbon emissions: Evidence from China

Finance is significant support for the low-carbon transformation of the real economy, in which digital finance as a new direction of financial development exerts a significant influence on carbon emissions. Therefore, it is crucial to investigate the association between digital finance and carbon emissions in order to develop carbon reduction strategies from the financial side. For this purpose, using the sample set covering 30 provincial areas during 2011–2020, this paper investigates the direct, indirect, and non-linear effects of digital finance on carbon emissions by applying fixed effects, mediating effects, and threshold effects analysis techniques. The results indicate that: (1) digital finance can significantly mitigate carbon emissions at the national level. (2) Digital finance inhibits carbon emissions as it drives green technological innovation and industrial structure upgrading. (3) Significant regional heterogeneity is observed in the effect of digital finance on carbon emissions, i.e., the effects of digital finance on carbon emissions are higher in the east-central region than in the overall sample, while the opposite is true in the western region. (4) The dampening effect on carbon emissions steadily increases as digital finance levels cross the first and second thresholds, respectively. Based on the above considerations, policymakers shall not only develop differentiated digital finance initiatives, but shall also fully unleash carbon emission reduction potential by rationalizing and optimizing industrial layout and strengthening financial subsidies for green technology innovation.

The road to green development: How can carbon emission trading pilot policy contribute to carbon peak attainment and neutrality? Evidence from China

Carbon emission trading is not only a market-based instrument but also one of the government's macro-policies, which is extremely crucial to fulfilling both carbon peak attainment and carbon neutrality goals. For this purpose, this paper adopts a 30-region dataset for the period from 2008 to 2020 in China and employs the difference-in-difference (DID) method to quantify the effect of the carbon emission trading pilot policy (CETP) on carbon emissions on the basis of introducing industrial structure upgrading and green technology innovation as moderating variables. The results show that (1) CETP has a statistically significant dampening effect on carbon emissions, while its carbon emission reduction effect follows a significant strengthening trend as the policy year of CETP implementation is delayed. (2) CETP has a significant carbon emission reduction effect. However, its effect demonstrates a gradual decrease from the eastern to the central and finally to the western regions. (3) CETP can inhibit carbon emissions depending on industrial structure upgrading to a certain extent, and this dependence is significant in the national and eastern regions but not in the central and western regions. (4) CETP's carbon emission reduction effect is dependent on green technology innovation, which is only revealed in the western region and performs as a dampening effect in the national, eastern, and central regions, but not significantly.

The Impact of Financial Development and Green Finance on Regional Energy Intensity: New Evidence from 30 Chinese Provinces

Energy efficiency and energy intensity are gradually gaining attention, and it is now an important proposition to reconcile financial development, green finance, and regional energy intensity. Using Chinese mainland provincial panel data (except Tibet) from 2007 to 2019, this paper applied the spatial econometric model and the panel threshold model to investigate the effects of financial development and green finance on regional energy intensity. The paper discovered that financial development raises regional energy intensity, while green finance reduces it. Based on the panel threshold perspective, in different stages of green finance development, the effect of financial development on regional energy intensity presents an inverted U-shaped effect that first promotes and then inhibits. Meanwhile, green finance has a significant positive spatial transmission effect on regional energy intensity. Based on the spatial weight matrix reflecting regional economic relations, the increase in energy intensity has a significant negative spatial autoregressive effect on itself, and the spatial spillover effect of financial development is negligible.

Towards sustainable development in China: How do green technology innovation and resource misallocation affect carbon emission performance?

Green technology innovation is an effective way through which to achieve carbon neutrality and sustainable development. Based on provincial panel data of 30 provinces in China from 2005 to 2018, this work examines the tripartite relationship among green technology innovation, resource misallocation, and carbon emission performance by constructing panel regression models and a dynamic threshold panel model. The research results show that green technology innovation significantly improves carbon emission performance. Further analysis shows that both capital and labour misallocation have a negative impact on carbon emission performance and hinder the contribution of green technology innovation to the improvement of carbon emission performance. The regression results show that there is a threshold effect of green technology innovation on carbon emission performance: as the degree of resource misallocation increases, the positive impact of green technology innovation on carbon emission performance gradually decreases. This study provides an important reference for policy-makers in implementing policies to improve carbon emission performance. Policy-makers should continue to promote the level of green technology innovation and improve the efficiency of labour and capital allocation.

Analysis of the Impact of Livestock Structure on Carbon Emissions of Animal Husbandry: A Sustainable Way to Improving Public Health and Green Environment

Carbon emissions of animal husbandry have been gaining increasing attention due to their high share in global carbon emissions. In this regard, it is essential to assess the regional differences, dynamic evolution patterns, convergence characteristics, and the impact of livestock structure on carbon emissions of animal husbandry. Using data from 30 provincial administrative regions from 2000 to 2018 in China, this study employs the Thiel index method, kernel density analysis, and convergence analysis to quantify the impact of livestock structure on carbon emissions of animal husbandry. The statistical results reveal that carbon emissions of animal husbandry exhibit a rising and declining trend. Specifically, the carbon emissions of animal husbandry are highest in agricultural areas (with a declining trend), followed by agro-pastoral areas (with a declining trend), and the pastoral areas (with a rising trend). It is further revealed that there are no δ convergence and β convergence of carbon emissions of animal husbandry. Finally, essential and useful policy recommendations are put forward to inhibit carbon emissions of animal husbandry.

Does the Construction of National Eco-Industrial Demonstration Parks Improve Green Total Factor Productivity? Evidence from Prefecture-Level Cities in China

This study conducted quasi-natural experiments based on the panel data of 239 prefecture-level cities in China from 2005 to 2017. The difference-in-difference (DID) and mediation effect model are used to test the impact and mechanism of the construction of national eco-industrial demonstration parks (NEDP) on green total factor productivity (GTFP). The results show that: (1) The construction of NEDP has significantly improved the urban GTFP, and the conclusion is still valid after running the robustness test. (2) Mechanism analysis shows that the construction of NEDP has improved GTFP through technological innovation and industrial structure upgrading. (3) The heterogeneity results reveal that NEDP has a significant positive effect on GTFP in the central and western regions, while the effect was insignificant in the eastern region. Moreover, NEDP significantly contributes to GTFP in resource-based and non-resource-based cities, while the contribution of resource-based cities is greater than that of non-resource-based cities. This study provides a reference for China to further promote the construction quality of NEDP and green development.