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Toilet paper has been reported as one of the major insoluble pollutant components in the influent of wastewater treatment plants. Toilet paper fibers contribute to a large production of sewage sludge, resulting in a high treatment cost and high energy consumption. To find energy-efficient, cost-effective, and environment-friendly technologies for fiber removal and resource recovery from wastewater, a life-cycle assessment (LCA) was performed to analyze the wastewater treatment processes, including a sieving process for removing and recovering suspended solids before the biodegradation units. Based on the LCA results, it was estimated that the sieve screening process saved 8.57% of energy consumption. The construction phase of sieving consumed 1.31% energy cost compared with the operation phase. Environmental impact analysis showed that sieving reduced the impacts of climate change, human toxicity, fossil depletion, and particulate matter formation, which reduced the total normalized environmental impacts by 9.46%. The life-cycle analysis of the removal of toilet paper fibers from wastewater revealed the need to use more efficient methods to enhance the recovery of cellulose fibers. [ABSTRACT FROM AUTHOR]

Existing literature ignores to consider multiple types of pollutants when analyzing energy efficiency and its convergence. Under this background, using SuperSBM-GML model, the improved entropy method, and convergence model, this paper calculates the green total-factor energy efficiency and its evolution trend of 35 China's industrial sub-sectors considering multiple pollutants, and analyzes its convergence. The results indicate that the average score of industrial green total-factor energy efficiency is low, and there are significant differences among sub-sectors: "Utilization of waste resources" is the highest, while "Manufacture of paper and paper products" is the lowest. The green total-factor energy efficiency shows an overall upward trend from 2006 to 2021, the main driving force comes from technological progress, but numerous sub-sectors have not sufficiently caught up with existing cutting-edge technologies. Specifically, the growth rate of green total-factor energy efficiency in high-energy-consumption sub-sectors is higher than low-to-medium-energy-consumption sub-sectors. There are both σ-convergence and β-convergence in low-to-medium-energy-consumption group, indicating that development of sub-sectors is stable and outstanding. Nevertheless, the high-energy-consumption group only exhibits conditional β-convergence, revealing an imbalance in energy efficiency development. Consequently, formulating the benchmark level of energy efficiency and developing energy efficiency "leader" system are suggested for low-to-medium and high-energy-consumption sub-sectors, respectively. [ABSTRACT FROM AUTHOR]

Corporate green innovation is the crucial driving force to promote green development and realize the construction goal of "Beautiful China." Meanwhile, the development of Fintech creates a more favorable external environment for corporate green innovation. Using the panel data of China's Digital Financial Inclusion Index and Energy Poverty Index at provincial level from 2011 to 2020, this paper studies the influence of Fintech on corporate green innovation by the evidence from Chinese heavily polluting enterprises. Based on stepwise regression, this paper further examines the mediating role of energy poverty, including energy consumption level, energy consumption capacity, and energy consumption structure, in the relationship between Fintech and corporate green innovation. The results show that (1) Fintech contributes to improving the level of green innovation of heavily polluting enterprises; (2) energy poverty acts as a mediator in the process of Fintech's influence on corporate green innovation; (3) Fintech can promote green innovation of heavily polluting enterprises by improving the level of regional energy consumption level, but it fails to influence corporate green innovation through energy consumption capacity and energy consumption structure. These results provide governments and companies with implications on facilitating corporate green innovation so as to further promote green development. [ABSTRACT FROM AUTHOR]

It can be observed from the existing energy literature the previous papers investigating the influence of renewables consumption on GDP for the USA commonly ignore structural breaks in the US economy. Hence, the purpose of this paper is to examine the impact of renewable energy consumption on economic growth for the USA using quarterly data over the period 1977Q1-2019Q3 through unit root and cointegration methods based on different approaches in modelling structural breaks. Our empirical evidence confirms that all unit root tests give similar outputs and show all the variables become stationary at 1st differences. Besides, cointegration tests show highly different results in terms of the statistical significance of the coefficients. For instance, the cointegration test without structural breaks indicates that renewable energy consumption has no impact on economic growth. With sharp structural breaks in the cointegration approach, there is no cointegration between the variables. The empirical findings of the cointegration test with sharp and gradual breaks imply that renewable energy consumption has positive effects on economic growth. This paper discusses the implications of the empirical findings. [ABSTRACT FROM AUTHOR]

Transportation is the key carbon emission source after energy supply and industrial production. Under the vision of carbon peak and carbon neutralization, the pressure of reducing carbon emissions in transportation will be greater in the future. This paper constructs a model that takes transportation carbon emission as the main target and freight transportation utility value as the auxiliary target. The constructed model satisfies the constraints of freight turnover in the whole society, freight economic and social benefits, and the ecological constraints of the freight system. With MATLAB, the freight turnover of roadways, railways, and waterways (excluding ocean transportation) in 2030 is solved by using the adaptive genetic algorithm. The results indicate that (I) compared with the current freight structure of China, the roadway freight sharing rate in 2030 will decrease by 8.07%, and the railway freight sharing rate and the waterway freight sharing rate (excluding ocean transportation) will increase by 0.93% and 7.13%, respectively. (II) After optimization, the energy consumption and carbon emission are reduced by 42,471,500 tons (10.3%) and 91,379,400 tons (10.2%) of standard coal, respectively. (III) The adaptive genetic algorithm outperforms the traditional genetic algorithm in terms of convergence speed and accuracy. (IV) As the weight coefficient of carbon emission increases, the utility value of freight transportation consistently decreases, and the sensitivity increases. Meanwhile, as the carbon emission weight coefficient increases, carbon emission keeps decreasing, and the sensitivity decreases. [ABSTRACT FROM AUTHOR]

As a major part of global development governance, G20 countries account for 80% of global carbon emissions. In order to achieve the goal of "carbon neutrality" proposed by the United Nations, it is important to compare and analyze the drivers of carbon emissions in G20 countries and provide recommendations for their carbon emission reduction. Based on the data of 17 G20 countries in the EORA database, this paper compares the drivers of carbon emissions of each country from 1990-2021 using weighted average structural decomposition and K-mean model. This paper focuses on four drivers, including carbon emission intensity, final demand structure, export structure, and production structure. Carbon emission intensity and final demand structure are the main factors of carbon emission reduction, and the other two factors have little influence. Among the G20 countries, the UK is in the first category because it does the best job on the four factors of carbon emissions, yet Italy is in the last category because it does not take full advantage of the four factors. Therefore, improving supply energy efficiency and adjusting demand, export, and industrial structure have become important tools for countries to transform and achieve carbon neutrality. [ABSTRACT FROM AUTHOR]

With the development of urbanization, the problem of the disintegrated between industry and city became more prominent, exploring the reasons. The efficiency of new-type industry has been the crucial factor in city-industry integration. This paper constructs the measurement index system of new-type urbanization via DEA-BCC methodology, starting from the quality of urbanization to analyze the efficiency of urbanization. This paper chooses the total energy consumption, general public budget expenditure, and the proportion of employment personnel in the tertiary industry in all urban units as input variables. The total retail sales of consumer goods, urbanization rate, average annual concentration of pm2.5 (popW), and built-up area as output variables. This paper uses DEA method to measure the comprehensive efficiency value, technical efficiency value, and scale efficiency value of new urbanization in Shanghai, and analyzes the influencing factors of urbanization efficiency. The results show the following: (1) The overall level of comprehensive efficiency value, technical efficiency value, and scale efficiency of Shanghai's new-type urbanization are relatively high, especially the technical efficiency basically stays at a high level. The overall trend of scale efficiency and comprehensive efficiency is consistent, and the comprehensive efficiency is greatly influenced by scale efficiency. (2) The technical efficiency of urbanization in Shanghai is close to the optimal, and there is little space for further increasing technological input to improve the comprehensive efficiency of new-type urbanization. The scale efficiency is slightly lower than the technical efficiency, and there is still some space for optimization. (3) In terms of urbanization input indicators, Shanghai's total energy consumption and general public budget input were too much in the early years, which led to the reduction of urbanization efficiency, and the situation has been improved in recent years. In terms of the output index of urbanization, increasing the total retail sales of social consumer goods and the output of built-up area can make the urbanization efficiency of Shanghai reach the optimal efficiency. [ABSTRACT FROM AUTHOR]

In the case of China, there is a need of green energy system to boost growth and environment. However, the current growth of urbanization is putting high pressure on energy system through financial capital. Hence, it is a need to develop such path through renewable energy consumption, capital development, and urbanization to enhance the performance of development and environment. Therefore, this paper contributes to the literature by adding the asymmetries between renewable energy, urbanization, economic growth, and capital investment by covering the period from 1970 to 2021. For this purpose, we apply the nonlinear autoregressive distributed lag model to find the nonlinearities between the variables under study. The findings confirm the asymmetric short- and long-term relationships between the variables. In this sense, capitalization shows the short- and long-term asymmetric impacts on renewable energy consumption. In addition, urbanization and economic growth have long-term asymmetric and positive impacts on renewable energy consumption. At last, this paper provides applicable and practical policy implications for China. [ABSTRACT FROM AUTHOR]

New energy strategies are crucial to address energy and environmental issues, but the energy consumption transition may also affect firm behavior with unintended economic consequences. Using data from A-share listed companies from 2010 to 2019, this paper investigates the impact of energy consumption structure transformation on firms' total factor productivity (TFP) using China's new energy demonstration city (NEDC) policy as a shock. It is found that the NEDC reduces firms' TFP by about 6.4%. This conclusion still holds after a series of robustness and endogeneity tests. According to the channel analysis, NEDC reduces the efficiency of firms' resource allocation and innovation, resulting in efficiency losses. Furthermore, differences in firms' ownership and geographical location make the impact of NEDC on TFP heterogeneous. For example, the hindering effect of NEDC on TFP is more pronounced in private firms and firms in regions with lower marketization. This paper shows that the promotion and application of new energy may have certain economic costs. To better balance the benefits and costs of new energy strategies, the government and other relevant departments should increase policy flexibility and perfection. [ABSTRACT FROM AUTHOR]

As the largest energy consumer, China's control of carbon emissions from energy consumption plays a pivotal role in world climate governance. However, few studies have been conducted to explore the emission reduction pathways that promote a high level of synergy between China's economic growth and the " carbon peaking and carbon neutrality " goal from the perspective of energy consumption. Based on the measurement of energy consumption carbon emissions, this paper reveals the spatial and temporal distribution and evolution trends of carbon emissions in China at the national-provincial level. The multi-dimensional socio-economic factors such as R&D and urbanization are taken into account, and the LMDI model is used to decompose the driving effects of energy consumption carbon emissions at the national-provincial levels. Further, this paper combines the Tapio decoupling index with the LMDI model to decompose the decoupling states of China year by year and at the provincial level in four periods to explore the reasons for the change of carbon decoupling states. The results show that: (1) China's energy consumption carbon emissions grew at a high rate before 2013, and slowed down after that. There are significant differences in the scale and growth rate of carbon emissions among provinces, which can be classified into four types accordingly. (2) The R&D scale effect, urbanization effect, and population scale effect are the factors driving the growth of China's carbon emissions; while the energy structure effect, energy consumption industry structure effect, energy intensity effect, and R&D efficiency effect inhibit the growth of China's carbon emissions. (3) Weak decoupling is the most dominant decoupling state in China from 2003 to 2020, and the decoupling state varies significantly among provinces. According to the conclusions, this paper proposes targeted policy recommendations based on China's energy endowment. [ABSTRACT FROM AUTHOR]

Green finance is key in supporting industries' green transformation and helping achieve low-carbon economic (LCE) development. This paper constructs an LCE development index using panel data from 30 provinces in China from 2011 to 2020. Based on the establishment of the first five pilot green finance zones in China in 2017 as a quasi-natural experiment, the synthetic control method (SCM) is applied to explore the impact of green finance policies on the level of LCE development and to analyze the mechanism and evaluate the policy effects. The empirical results show that (1) the synthetic analysis unit better fits the development trend before the implementation of the pilot. (2) After the implementation of the pilot reform, the level of LCE development in Zhejiang, Jiangxi, Guangdong, and Guizhou provinces has a more significant enhancement effect, but the enhancement in Xinjiang is not significant, which indicates that the reform effect in Zhejiang, Jiangxi, Guangdong, and Guizhou is significantly better than that in Xinjiang to a certain extent. (3) The samples were statistically significant and passed the placebo and ranking tests. Additionally, this paper analyzes the mechanism of policy effectiveness in terms of sci-tech innovation (STI) and energy consumption structure: green finance as a grip for economic transformation can provide financial support for regional STI and energy consumption structure upgrade and promote the capital flow to green low-energy industries, ultimately achieving sustainable economic development. Based on the above findings, policy insights can be provided for the improvement of green finance pilot regions. [ABSTRACT FROM AUTHOR]

China's economic growth miracle of the past decades has been accompanied by a massive increase in fossil fuel consumption and severe environmental pollution. To control air pollution, China is implementing some green finance policies. Although they have improved the air quality, it is little known whether and how green finance affects the firm labor demand. Taking the 2012 Chinese green credit policy (GCP) as an exogenous setting, this paper adopts the difference-in-difference (DID) method to investigate the effect of green finance on firm labor demand based on A-share listed firms covering 2007–2017. We find that green finance had a significant negative impact on firm labor demand. Specifically, the high-polluting firms with stricter green finance constraints would reduce firm employment by 4.8%. This effect is especially prominent when firms are state-owned enterprises (SOEs) or workers are low-skilled employees. Further evidence indicates that there are the Compliance Cost Hypothesis and Porter Hypothesis in China. In these two effects, the effect of CCH dominates, so the overall effect of green finance is detrimental to corporate performance, which in turn leads to lower corporate employment. Our paper provides the real effect of green finance from the firm labor market. And this paper has strong policy recommendations that the government should reconcile the relationship between air pollution control and employment. [ABSTRACT FROM AUTHOR]

Whether the technological finance cooperation pilot (TFCP) policy in China can promote energy efficiency remains under investigated. Using the dataset covering 284 cities in China from 2003 to 2019, this paper adopts the Super-SBM model with undesirable outputs to measure energy efficiency. Based on this efficiency, the Difference-in-Differences model (DID) and Spatial Durbin model (SDM) are employed to discuss the impact of TFCP policy on energy efficiency. Results demonstrate that TFCP policy has significantly promoted energy efficiency. And the conclusion is still valid after the robustness checks and endogenous treatment has been carried out. The impact of the TFCP policy on energy efficiency is heterogeneous, depending on the geographical, administrative, and resource characteristics of cities. To be specific, the promotion effect tends to be pronounced in east-central cities, high-ranking cities, and high-tech cities. Moreover, TFCP policy could significantly improve energy efficiency through the effects of technological innovation, industrial upgrading, and financial development. A further policy spillover analysis shows that TFCP policy has exerted a remarkable incentive influence on energy efficiency locally, while the neighboring cities are inhibitive. To sum up, this research is of important theoretical value and policy-making reference on green economy transformation for cities with differential features and energy utilization capacity, by shedding light on the impacts of such a technological finance cooperation system on energy efficiency. [ABSTRACT FROM AUTHOR]

Improving energy efficiency is an important measure of environmental governance. At present, studies on the impact of high-speed rail on energy efficiency need to be further studied. This paper constructs panel data of 285 cities at prefecture-level and above in China from 2003 to 2017, and uses the difference-in-difference (DID) to study the impact of high-speed railway on urban energy efficiency. Based on the theories of "factor flow," "knowledge spillover," and "center-periphery," this paper discusses the influence mechanism and heterogeneity of high-speed railway on energy efficiency. The empirical results show that high-speed railway can significantly improve energy efficiency, and the conclusion is still valid after parallel trend test, propensity score matching and difference-in-difference (PSM-DID) test, and instrumental variable method. The results remained true after a series of robustness tests. Mechanism analysis shows that high-speed railway can improve energy efficiency by promoting industrial structure upgrading, technological innovation, and market integration. Analysis of heterogeneity shows that the promotion effect of high-speed railway on energy efficiency is greater in central and western cities and core cities. This study provides useful enlightenment for optimizing China's high-speed rail construction planning and seizing the opportunity of high-speed rail development to improve energy efficiency. [ABSTRACT FROM AUTHOR]

This study aims to assess the performance of thermophysical materials in the construction and building industry to establish the necessary academic basis for the interpretation of trends, developments, and status in this research field. The Scopus database contains 159 papers on this topic, which were published between 1968 and 2021 and originated in 60 countries. The International Organization for Standardization published significant information on thermal insulating materials, merchandize, elements, and applications. Several forms of insulation currently exist: (i) solid-state foam insulation composed of fibers, grains, and matrix; (ii) liquid-state insulation that encloses humidity within the filling; and (iii) gasifier form, which incorporates air, steam, or alternative gases. To reduce the amount of energy demanded, thermal insulation materials must be extended, current solutions must be modified, and new materials must be developed. Because high-temperature thermal insulation materials have more complex working conditions than alternative materials, their application requires further consideration. [ABSTRACT FROM AUTHOR]

With the rapid growth rate of China's economy, the extensive pattern of economic growth of "high energy consumption and low output" has magnified the constraints of energy issues on China's economic development and environmental protection, which highlights the importance of improving energy efficiency. As one of the three major economic zones in China, the Pearl River Delta region also faces high energy consumption and pollution emissions while developing at a high speed. Hence, improving the energy efficiency of the Pearl River Delta region is needed, as it not only is conducive to driving its development of the surrounding green economy, but also promotes the subsequent sustainable economic development. However, there are few literatures on the calculation and analysis of energy efficiency in the Pearl River Delta, and lacking a systematic analysis of input–output index system of energy efficiency measurement. Therefore, this paper calculates the energy efficiencies and the Malmquist indexes based on the panel data of the nine cities in the Pearl River Delta from 2005 to 2019 through super-efficiency SBM model and Malmquist index method by using MAXDEA and MATLAB software. The result illustrates that all regions in the Pearl River Delta except Guangzhou and Shenzhen show obvious energy inefficiency, which is mainly caused by the imbalance between technical efficiency and scale efficiency. Based on the calculation results, this paper gives some relevant suggestions for the further approach of energy reform in the Pearl River Delta according to the calculation results. [ABSTRACT FROM AUTHOR]

To cope with climate change, China commits that it will strive to achieve carbon peaking by 2030. Using the Cointegration model and the Markov Chain model, this paper forecasts China's carbon emissions during 2019–2030 in six scenarios, and assesses the contribution of optimizing the energy mix to China's carbon peaking. The research obtains three main conclusions. Firstly, optimizing the energy mix will contribute to achieving China's carbon peaking. In the economic slow-growth scenario, taking China's planned target of energy mix (PTEM) into account, the carbon peaking year will be brought forward from 2028 to 2023. In the economic medium-speed-growth scenario, optimizing the energy mix will make China achieve carbon peaking in 2028. Without considering the PTEM, however, the carbon emissions will not peak before 2030. In the economic fast-growth scenario, the peaking year will not occur whether considering the PTEM or not, but the growth rate of carbon emissions with the PTEM will be far lower than that without considering the PTEM. Secondly, in all three economic growth scenarios, optimizing the energy mix will largely reduce the growth rate of carbon emissions, and thus significantly reduce the peak value of carbon emissions. Thirdly, optimizing the energy mix has a negative adjusting effect on the impact of economic growth on the growth rate of carbon emissions, and the negative effect rise as the economic growth rate increases. [ABSTRACT FROM AUTHOR]

Clean, affordable, and efficient energy sources are inevitable for a sustainable world. Energy crisis, especially the poor access and affordability, demand–supply mismatches, energy inequality, and high dependence on non-renewable energy sources, are the challenges before the attainment of clean energy goals for sustainable development. The 5-year review from the adoption of sustainable development goals (SDGs) by using bibliometric and thematic analysis was conducted in this review. This review is a synthesis of 175 scientific papers on SDG 7. Policy reforms and better funding; technology innovation and inclusion; and economic growth, rapid promotion of renewable, and alternative fuels are the recommendations for the achievement of the energy goals. Future research on energy-related goals should focus on energy justice, policy reforms, energy poverty, poor affordability, off-grid transmissions, renewable energy sources, alternative fuels, reforms in the energy supply chain, and international cooperation for better implementation of projects and for attracting foreign capital and private funds. This paper invites the attention of practitioners, academicians, funding agencies, and international agencies to collaborate in the initiatives for a clean, green, and energized world. [ABSTRACT FROM AUTHOR]

Current studies do not provide a consensus on whether digital technology innovation can reduce enterprise carbon intensity despite the rise of the digital economy. This paper examines the role and influence pathway of digital technology innovation on enterprise carbon intensity using data from A-share listed enterprises in China's manufacturing industry from 2012 to 2021. The findings indicate that (1) digital technology innovation has been found to significantly reduce enterprise carbon intensity, as confirmed by numerous robustness and endogeneity tests. However, its inhibitory effect on carbon intensity shows a marginal decreasing trend. (2) In the heterogeneity analysis, it was found that digital technology innovation significantly reduces the carbon intensity of consuming coal, coke, kerosene, and diesel. From various perspectives, including enterprise, industry, and external environment, there are significant differences in the carbon reduction effects of digital technology innovation. (3) The analysis of impact paths reveals that digital technology innovation can affect enterprise carbon intensity through three paths: improving productivity, enhancing green innovation efficiency, and adjusting energy consumption. (4) Upon further analysis, it was discovered that the spillover effect of digital technology innovation is more pronounced in the industry cohort of enterprises. Additionally, digital technology innovation plays a positive role in enhancing enterprise ESG performance. The paper's findings offer empirical evidence and decision-making references for the government to develop reasonable policies for reducing carbon emissions, promoting green and low-carbon enterprise transformation, and actively and steadily achieving the goal of carbon peaking and carbon neutrality. [ABSTRACT FROM AUTHOR]

Ensuring the safety of Arctic shipping and preserving the Arctic ecological environment are emerging as key challenges in the shipping sector. Ship collisions and getting trapped in ice are frequently occurring under dynamic ice conditions due to the Arctic environment, making research on ship navigation in Arctic routes significant. Leveraging ship networking technology, we developed an intelligent microscopic model which considered factors such as the future motion trends of multi-ships in front and the influence of pack ice, and carried out a stability analysis of the model utilizing linear and nonlinear methods. Additionally, the accuracy of the theoretical results was further validated through simulation experiments with diverse scenarios. The conclusions manifest that the model can magnify the anti-disturbance ability of traffic flow. Additionally, the problem of energy consumption due to ship speed is explored, and it is determined that the model has a positive intention in reducing speed fluctuations and ship energy consumption. This paper highlights the potential of intelligent microscopic models in studying the safety and sustainability of Arctic shipping routes, providing targeted initiatives to improve safety, efficiency, and sustainability in Arctic shipping. [ABSTRACT FROM AUTHOR]

In the context of increasing global resource and environmental problems, it is of great practical significance to accurately test the impact of various factors on energy use efficiency for maintaining national energy security and formulating relevant policies. This paper measures firms' total factor energy efficiency (TFEE) using the two-stage stochastic frontier method within the data envelopment analysis (DEA) framework, leveraging data from listed firms in China spanning 2010 to 2022. Employing the establishment of free trade zones (FTZs) as a quasi-natural experiment, we apply the staggered differences-in-differences (DID) and stacked DID methods and analyze the impact of FTZs on firms' TFEE. The results show that the establishment of FTZs significantly promotes the improvement of firms' TFEE, and it has a greater promotion effect on heavily polluting, non-manufacturing, state-owned, private, and small-scale firms. The results of the mechanistic analysis showed that the promotion effect of FTZs on firms' TFEE is mainly realized through three channels: increasing government subsidies, reducing the financing constraint effect, and encouraging the technology innovation effect. Furthermore, industry-level decomposition results indicate that the surge in industry energy efficiency primarily results from improvements within firms rather than inter-industry variations. This paper's results propose that countries can enhance energy efficiency by progressively endorsing the implementation of FTZs. [ABSTRACT FROM AUTHOR]

This paper addresses a preliminary study on the emission control of pollutants from an industrial furnace. The stack sampling technique was implemented in this study, and the quantity of pollutants released from the furnace smoke was monitored. The transverse points required to collect the data were selected based on the upstream and downstream disturbances. At first, the investigation was made with the furnace oil. A 15.28% and 5.1% of CO2 and O2 were observed in the flue gas from of regular furnace oil. Hence, by considering the emission level observed, the analysis was repeated with the low sulphur-low stack and the coal tar fuel. The emission of SO2 and N2 was reduced with coal-tar fuel compared with the regular furnace fuel. Thus, the proposed operational adjustment attenuates the pollutant emission, which also helps to reduce the unfavorable impact on the environment. In the future, the authors intend to include a design change in the furnace burner, which would help to increase fuel efficiency and reduce pollution. [ABSTRACT FROM AUTHOR]

This manuscript presents a scientometric review of recent advances in microwave pretreatment processes for sewage sludge, systematically identifying existing gaps and prospects. For this purpose, 1763 papers on the application of microwave technology to sludge pretreatment were retrieved from the Web of Science (WoS) using relevant keywords. These publications were then analyzed using diverse scientometric indices. The results show that research in this field encompasses applications based on the non-thermal effects of microwaves, enhanced effectiveness of anaerobic digestion (AD), and the energy balance of this pretreatment system. Overcoming existing technical challenges, such as the cleavage of extracellular polymers, reducing microwave energy consumption, understanding the non-thermal effects of microwaves, promoting AD of sludge in combination with other chemical and physical methods, and expanding the application of the technology, are the main scientific focuses. Additionally, this paper thoroughly examines both the constraints and potential of microwave pretreatment technology for wastewater treatment. [ABSTRACT FROM AUTHOR]

Using the new measure of the export quality of the International Monetary Fund (IMF), this paper investigates the effects of the product quality of exports on the growth rate of the per capita carbon dioxide emissions. The paper focuses on the panel dataset of 82 developing economies for the period from 1970 to 2014. Along with the index of export quality, we also consider the measures of the per capita income, per capita energy consumption, natural resource rents, and trade openness. The results indicate that there is the positive impact of the quality of exports on carbon dioxide emissions. There is also the positive relationship between the per capita income and carbon dioxide emissions. In addition, we find that the trade openness measures are positively related to carbon dioxide emissions. These results are robust to consider different income measures and to divide the developing economies, according to their income levels. [ABSTRACT FROM AUTHOR]

Environmental issues and targets to reduce greenhouse gas emissions have reinforced attempts to increase energy efficiency for all stakeholders, including the shipping industry. International maritime organization (IMO) has prescribed operational and design measures to develop energy efficiency and decrease ship emissions, and one of the effective operational measures is trim optimization, which is a feasible measure because it does not necessitate ship structural modification or engine advancement, but it can reduce the ship resistance and decrease fuel consumption. The study of trim optimization can be implemented by conducting experimental tests, but it is a difficult, expensive method and consumed more time. Therefore, the present paper proposes a numerical method to predict the optimum trim which achieves the minimum ship resistance and lower fuel consumption. The current paper investigated two types of ships as a case study, bulk carrier, and container ship. The optimization process has studied several trim conditions, ship drafts, and speeds. The results showed that positive trim (trim by bow) have an increasing effect on fuel consumption, while the negative trim (trim by stern) have a decreasing effect on fuel consumption. Fuel-saving based on using optimum trim at each speed is a significant quantity to be benefited as it would reduce the operating costs and increase the energy efficiency. [ABSTRACT FROM AUTHOR]

Early periods of history have demonstrated that enhanced economic development is fostered in instances where natural resources are abundant, hence averting the resource curse. In this vein, accelerated economic advancement is driven by a rigorous and proficient financial sector that efficiently utilises and allocates the economy's natural resources. A strong financial system that transforms resources into advantages rests on an advanced technological innovation base, superior human capital, distinct foreign direct investment, powerful trade, and sustainable energy consumption. While this paper investigates the nexus of these factors, the specific purpose of this research is to examine the interactive impact of financial development and natural resource rents on carbon emissions in the new BRICS economies for the duration of 1990 to 2019. The panel data generalised least squares (GLS) and the panel-corrected standard error (PCSE) techniques are adopted. The Dumitrescu and Hurlin technique is used to establish causality. The study found a U-shaped association between economic growth and emissions. The findings prove that the financial development of financial institutions and the financial development of financial markets' relationships with emissions are significantly positive. Natural resource rents, energy consumption, and human capital create a significantly positive relationship with emissions (mostly just positive for technological innovation). Conversely, the connection involving trade and carbon emissions is significantly negative (but mostly just negative for FDI). The interaction (s) intervening financial development of financial institutions and financial development of financial markets with natural resource rent significantly lowers emissions, respectively. The interaction parameter (financial development of financial institutions, natural resource rent, and financial development of financial markets) mixed with trade significantly adds emissions (positively insignificant with energy consumption). Contrarily, this factor mixed with human capital and technological innovation, respectively, is significantly negative (just negative for FDI). The Dumitrescu–Hurlin panel Granger causality outcomes are also outlined. [ABSTRACT FROM AUTHOR]

Due to the expansion of residents, the consumption of non-renewable energy increased enormously, thus indirectly increasing pollution and affecting the surroundings. To reduce pollutions in the surroundings, it is recommended to choose non-conventional energy sources. By satisfying this, we can probably decrease the non-renewable sources of energy, by consuming the solar power in day-to-day life in the application of food drying process. In this review article, we have discussed the classification of solar dryer and the impact of design modifications performed in the components of solar dryer and assessed the various types of solar dryer performance, cost estimations and designs performed in solar dryer of food applications which were not discussed in the earlier research. The primary and critical task in designing the solar dryer is to achieve higher efficiency at minimum cost. Hence, proper analysis of drying application, selection of suitable components and suitable design must be carried out to attain efficient dryer. Considering these characteristics, this paper primarily focuses on the effective design parameters incorporated with various efficiency enhancement processes of the solar dryer in the applications of food drying techniques. Thus, this review paper delivers the various classifications, design parameters, performance enhancement methods, properties and valuable assets of solar dryer, which helps to develop the sustainable green eco-friendly environment most primarily, in the application of food drying process. This review article concreted the way for upcoming considerations and provided the techniques for the studies to convey the work for promoting method enhancements. [ABSTRACT FROM AUTHOR]

China has abundant agricultural and forestry waste resources that are crucial sources of energy for substituting fossil fuels and achieving the carbon peaking and carbon neutrality goals. These resources play an essential role in reducing carbon dioxide emissions and promoting sustainable development. This paper presents an estimation of the number of biomass resources that can be used for energy in 2020 by using parameters such as the grass-to-grain ratio coefficient and excretion coefficient. Moreover, the potential for conversion of biomass resources into biomass energy is evaluated by using parameters such as lower heating value and gas production coefficient. Finally, based on the whole life cycle theory, the potential of biomass energy utilization to reduce carbon dioxide emissions and its impact on carbon peaking is calculated. It was found that the total amount of fossil fuels that can be replaced by biomass energy is 256 million tons of standard coal. Utilizing biomass energy can reduce carbon dioxide emissions by approximately 520 million tons, with a peak impact of 4–6% on carbon peaking. The research results presented in this article can provide valuable data to support the promotion of green transformation in various regions. The findings can serve as a useful reference for formulating localized biomass utilization plans and designing effective emission reduction policies. [ABSTRACT FROM AUTHOR]

Urban carbon emissions are one of the most important areas contributing to the growth of carbon emissions, and resource-dependent cities with natural resource extraction and processing as their leading industries tend to have higher carbon emissions. Ordos is the city with the highest coal production in China, and its economic development is dominated by coal, oil and gas, and other resource extraction and processing industries, with industrial activities making a large contribution to carbon emissions. At the same time, Ordos has undergone rapid industrialization in recent years, but still faces the problem of environmental pollution, epitomizing a typical resource-dependent city in China. Therefore, this paper takes Ordos as an example and uses the Generalized Divisa Index Method (GDIM) to study the drivers of industrial carbon emissions in Ordos from 2005–2020, a typical resource-dependent city in China, and further analyzes are conducted in relation to the three phases of development. Based on the key drivers, the Monte Carlo method is used to forecast industrial carbon emissions from 2021 to 2030. The results show that the most important factors driving the growth of industrial carbon emissions are the scale of industrial output and industrial energy consumption, while the intensity of industrial energy investment is the most important factor mitigating industrial carbon emissions, and that energy efficiency and carbon intensity of energy consumption can also mitigate carbon emissions after economic transformation. At the same time, investment is the factor with the greatest potential for optimization on the path to emissions reduction. [ABSTRACT FROM AUTHOR]

This paper investigates biomass and solar energy's present and future perspectives in low/zero energy and carbon emissions. Its data source is published articles indexed in the Scopus database. By analyzing the articles extracted in Vos viewer software, four main areas of research are found: sustainable development, economic and managerial issues, methods, algorithms, modeling technologies, and renewable energy and its sources and types. In all four sections, research gaps were observed in the field of the third generation of photovoltaics (semi-transparent solar cells)organic)) and algae. As part of the study, advanced bibliometric analysis was carried out by VOS viewer software, and 34129 articles were examined from Scopus, alongside a patent analysis using Google patents, in addition to the bibliometric analysis. It has been shown by machine learning that about 9% of future articles in all energy fields will consist of building articles, and a quarter of these articles will be in the field of renewable energy. While residential and commercial sectors are the dominant areas of renewable energy utilization and commercialization research, the potential of new generations of renewable energy technologies will create significant opportunities to achieve low/zero energy-carbon emission buildings. The paper concludes by predicting the increasing rate of renewable energy and building articles compared to energy articles by 2030, emphasizing the critical role of research in advancing sustainable energy solutions. This data mining analysis helps to identify the current gaps and opportunities. Therefore, great potential will be created to develop and commercialize a new generation of technologies in this industry. [ABSTRACT FROM AUTHOR]

There have been several strategies developed to increase the diversified supply of energy so that it can meet all of the future demands for energy. As a result, to ensure a healthy and sustainable energy future, it is imperative to warrant reliable and diverse energy supply sources if the "green energy economy" is to be realized. The purpose of developing and deploying clean energy technologies is to improve our overall energy security, reduce our carbon footprint, and ensure that the generation of energy is secure and reliable in the future, making sure that we can spur economic growth in the future. In this paper, advancements in alternative sources of energy sustainability and strategies will be examined to ensure there will be enough fuel to supply all the future demands for energy. Several emerging clean energy technologies rely heavily on the availability of materials that exhibit unique properties that are necessary for their development. This paper examines the roles that rare earth and other energy-critical materials play in securing a clean energy economy and the development of clean energy economies in general. For the development of these technologies to be successful and sustainable, a number of these energy-critical materials are at risk of becoming unavailable. This is due to their limited availability, disruptions in supply, and a lack of suitable resources for their development. An action plan focusing on producing energy-critical materials in energy-efficient ways is discussed as part of an initiative to advance the development of clean and sustainable energy. [ABSTRACT FROM AUTHOR]

"green" + "innovation" has become a new concept of development. The integration of the two can bring win-win for the environment and economy. This paper selects the annual data of 14309 A-share companies in Shanghai and Shenzhen Stock Exchange from 2012 to 2020 as the research sample. And it uses the two-way fixed effect model to empirically test the impact of green finance on enterprise innovation performance. The study found that the development of green finance can promote the improvement of enterprise innovation performance. The analysis of influence mechanism shows that the development of green finance can reduce the financing constraints of enterprises, and then improve the innovation performance of enterprises; the development of green finance can increase the R&D investment of enterprises, and then improve the innovation performance of enterprises; green finance development can increase corporate investment in environmental protection, which in turn can improve corporate innovation performance. The results of heterogeneity test analysis show that compared with the western region, private enterprises, small and medium-sized enterprises, and high energy consumption and high pollution enterprises, the development of green finance in the central and eastern regions, state-owned enterprises, large enterprises, and non double high enterprises has more obvious role in promoting enterprise innovation performance. Therefore, the government should issue relevant policies and actively promote green finance policies that can help improve environmental and economic issues. [ABSTRACT FROM AUTHOR]

The bi-fluid photovoltaic thermal (PVT) collector was introduced to provide more heating options along with improved cooling capabilities for the PV module. Since its introduction, this type of PVT system has been investigated thoroughly in various original works. In this review paper, we intend to put the concept and applications of this technology into question and revise the main achievements and discoveries through research and development with a focus on climatic and operational parameters. The paper encompasses a critical review of the discussed research and future directions for PVT collectors. The main utilized operational modes are discussed in detail, which are (i) water used in both channels, (ii) water in one channel and air in the other, and (iii) air in both channels. The modes were found to lead to different enhancement and performance effects for the utilized photovoltaic modules. The impact of mass flow rate was also taken by keeping one working fluid constant while varying the other to obtain its impact on the energy and exergy efficiency of the collector. In some cases, the fluids were run simultaneously and, in other cases, independently. [ABSTRACT FROM AUTHOR]

The distributed driven agricultural vehicle platform studied in this paper is a basic carrying platform that can be used for a variety of agricultural activities (pesticide spraying, weeding, and other plant protection operations). It does not need to rely on traditional fuel engine to drive but is driven by electric power, which is more environmentally friendly and conducive to the development of ecological agriculture in the future. In this paper, according to the driving and structure characteristics of distributed driving electric agricultural vehicles, in order to ensure the vehicle trajectory tracking ability, under conditions of agricultural operation, the driving attitude and drive coordination control of electric agricultural vehicles are taken as the key research objectives. In this way, the driving path of the vehicle platform can be accurately controlled during the operation of pesticide spraying and herbicide, so as to reduce the excessive use or misuse of pesticides and herbicides and greatly reduce the field pollution. Considering the specific driving environment as well as complex and changeable motion patterns of agricultural vehicles, when a single motion model is used to track and estimate the driving state, there will be low filtering accuracy or even loss of the target during vehicle maneuvering. In this paper, interactive multiple model (IMM) algorithm is combined with extended Kalman filter to effectively track changes of the target's motion mode, thereby avoiding low filtering accuracy or serious state estimation inaccuracy. Finally, through the distributed electric drive agricultural operation experimental platform developed by the research group, the working conditions close to the actual agricultural production activities was set up according to the needs of actual agricultural production activities in this paper, and applicability and accuracy of the algorithm state estimation are verified by experiments. [ABSTRACT FROM AUTHOR]

Improving green energy efficiency is crucial to promoting China's high-quality economic development and reducing the environmental pollution. In this paper, the Malmquist-Luenberger index measures the green energy efficiency of 30 provinces in China from 2004 to 2019. Based on the measurement results, the spatial Durbin model is used to empirically study the impact of environmental regulation on green energy efficiency and its spatial spillover effects. The results show that China's green energy efficiency is low, and its growth mainly comes from technological progress (TECH) rather than technological efficiency (EFFCH). The eastern region has the highest efficiency of green energy, followed by the West and the lowest in the Central region. The estimation results of the spatial Durbin model show that both environmental regulation and green energy efficiency have a significant spatial correlation. Environmental regulation can improve the green energy efficiency in the local province but inhibit green energy efficiency in the adjacent provinces. Finally, this paper puts forward relevant policy suggestions according to the research results. [ABSTRACT FROM AUTHOR]

The renewable energy sources are considered as the important factor to decrease the level of carbon emissions and to promote the global green economy. Understanding the dynamics of renewable energy consumption, this paper analyzes whether there is a unit root in renewable energy consumption in 54 countries over the period 1971–2016. To this end, the unit root test of Narayan–Popp with two endogenous (unknown) breaks is implemented. The paper finds that renewable energy consumption series are stationary around a level and the time trend in 45 of 54 countries. In other words, renewable energy consumption follows a unit root process only in nine countries: Brazil, China, Colombia, India, Israel, Japan, the Netherlands, Spain, and Turkey. The evidence implies that renewable energy demand policies, which aimed to decrease the carbon emissions, will only have permanent effects in those nine countries. [ABSTRACT FROM AUTHOR]

This paper comprehensively examines passive and active energy retrofit strategies as a highly effective approach for reducing building energy consumption and mitigating CO2 emissions while enhancing comfort and sustainability. The paper further examines energy simulation software and assesses the integration of renewable energy systems in building to improve energy efficiency. The review used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology, ensuring a rigorous and comprehensive analysis. In addition, the study utilized bibliometric analysis with VOSviewer to provide valuable insights into the research trends and influential publications in building energy retrofits. Bibliometric analysis reveals strong collaboration among 17 authors, emphasizing their significant contributions. Keywords like energy retrofitting and efficiency are prominent, indicating their importance in academic literature. Findings show passive strategies are more effective in reducing energy consumption, though a combined approach with active strategies can yield optimal results. Retrofitting presents challenges, such as substantial initial costs and regulatory barriers. User acceptance is crucial, considering potential disruptions. The review highlights the importance of energy simulation software, with tools like EnergyPlus, eQUEST, and IES VE identified for evaluating and identifying cost-effective retrofit measures in building performance. By providing comprehensive insights into the various strategies and tools available for retrofitting buildings to achieve energy efficiency and sustainability goals, this review serves as an authoritative resource for building owners, managers, and professionals in the building industry. It offers invaluable guidance for informed decision-making and facilitates implementing effective, energy-efficient, and sustainable building retrofitting practices. [ABSTRACT FROM AUTHOR]

The research on constructed wetland (CW) and microbial fuel cell (MFC) has been separate studies worldwide with crucial achievements being made in both fields. Due to environmentally friendly feature (of CW) and rich microbial population and excellent electrode catalytic activity (of MFC), CW and MFC have their own anticipated application prospect in wastewater purification and biological electricity generation. More significantly, the idea of embedding MFC into CW to form CW-MFC expands the scope for both of them and this has received much interest in recent years due to its striking features of sewage treatment efficiency, electricity generation, sustainability, and environmental friendliness. The increasing interest and the lack of soul of CW-MFC emerging to the new researchers reflect the need to recall the idea and summarize its development with regard to achieving its reality via some key issues This forms the basis of the paper. The paper also includes how to enhance the efficiency of electricity generation and supplement energy consumption, the degradation of emerging pollutants, and the degradation mechanism as well as the potential joint application of CW-MFC with other treatment technique. A mass of CW-MFC design parameters has been synthesized from the literature. Challenges and potential directions of CW-MFC in the future are prospected. It is expected that the paper can serve as a linkage for bridging knowledge gaps for further studies of CW-MFC. [ABSTRACT FROM AUTHOR]

One of the increasingly common methods to counteract the increased fuel consumption of vehicles is start-stop technology. This paper introduces a methodology which presents the process of measuring and creating a computational model of CO2 emissions using artificial intelligence techniques for a vehicle equipped with start-stop technology. The method requires only measurement data of velocity, acceleration of vehicle, and gradient of road to predict the emission of CO2. In this paper, three methods of machine learning techniques were analyzed, while the best prediction results are shown by the gradient boosting method. For the developed models, the results were validated using the coefficient of determination, the mean squared error, and based on visual evaluation of residual and instantaneous emission plots and CO2 emission maps. The developed models present a novel methodology and can be used for microscale environmental analysis. [ABSTRACT FROM AUTHOR]

With China's economy entering the stage of high-quality development, manufacturing energy carbon emission efficiency has become the focus of academic attention. It is of great significance to study the convergence of manufacturing energy carbon emission efficiency for realizing high-quality development of manufacturing in China. Based on the panel data of China's manufacturing sub-sectors, this paper measures and analyzes the evolution trend of manufacturing energy carbon emission and its efficiency. On this basis, this paper uses the coefficient of variation and convergence model to test the convergence of manufacturing energy carbon emission efficiency. The results show that China's manufacturing energy carbon emissions and its efficiency demonstrate an increasing trend. Coal was the main source of manufacturing energy carbon emissions. The manufacturing energy carbon emission efficiency does not have σ convergence, but has β convergence, and its convergence has industry heterogeneity. The manufacturing energy carbon emission efficiency exits scale effect and technology effect, but not the effect of opening to the outside world and institutional effect, and its effect exists industry heterogeneity. By reducing carbon emissions, adopting differentiated policies, adjusting the industry scale, and enhancing the industry technology intensity, China's manufacturing can improve the energy carbon emission efficiency and promote high-quality economic development. [ABSTRACT FROM AUTHOR]

To assess the characteristics of household carbon emissions per capita (HCPC), this paper divided China's provinces into 4 groups based on the decoupling relationship between household consumption and related emissions. This classification helped to analyze the correlation and reflected the decoupling status between carbon emissions and household consumption and explored the effect of consumption growth on carbon emissions. Then, according to logarithmic mean divisia index (LMDI) model, HCPC in China's provinces was decomposed into four drivers including carbon coefficient, energy structure, energy consumption, and population structure effect. Through multi-regional (M-R) analysis, temporal evolution and spatial differences of these four drivers in both national and provincial level were studied. This comparison method introduced temporal and spatial decomposition results into the same framework, which may provide a new perspective for analyzing carbon emission trends. The results showed that (a) the HCPC in all 30 provinces increased significantly especially in Inner Mongolia, Tianjin, Xinjiang, Heilongjiang, and Beijing. Energy consumption effect was the leading factor promoting HCPC growth. Energy structure and population structure also promoted HCPC growth slightly, and carbon coefficient was the effect which had inhibitory effect on HCPC growth at regional level. (b) Spatial differences of HCPC between regions narrowed during this period. This is mainly due to the rapid growth of HCPC in region IV. Energy consumption effect was the dominant factor for the spatial differences. Based on the results, this paper proposed to adopt more effective measures to improve energy efficiency, develop clean energy, and optimize energy structure, especially in the provinces with faster growth in carbon emissions. [ABSTRACT FROM AUTHOR]

In order to explore practical ways to test the eco-efficiency of low-carbon tourism and its drivers in Jiangsu Province, this paper empirically tests the effects of selected driving variables on the eco-efficiency of low-carbon tourism using a spatial lag model. It measures the eco-efficiency of low-carbon tourism in 13 prefecture-level cities in Jiangsu Province based on a modified two-stage network SBM model. According to the direct effect test results, per capita tourism income (PTI) had the most significant effect on the eco-efficiency of low-carbon tourism, with an impact coefficient of 0.5437, environmental pollution governance (EPG) had the second most significant effect, energy consumption intensity (ECI) and carbon emission intensity (CEI) had adverse effects with effect coefficients of − 0.3815 and − 0.4415, respectively, and R&D input intensity (RDII) had the slightest effect on the eco-efficiency of low-carbon tourism, with an impact coefficient of – 0.0836. According to indirect effect test results, RDII has the most significant positive effect with a coefficient of 0.3848, PTI has the second most significant adverse effect on the eco-efficiency of low-carbon tourism with a coefficient of − 0.3245, ECI has the third most significant adverse effect with a coefficient of − 0.2567, EPG has the fourth largest positive effect with a coefficient of 0.2162, and CEI has the slightest adverse effect with an impact coefficient of − 0.2147. [ABSTRACT FROM AUTHOR]

The Clean Heating Policy aims to solve the problems of excessive energy consumption and severe air pollution caused by central heating in northern China. Whether this policy can effectively reduce carbon emissions remains unexplored. Using panel data representing 65 cities in northern China from 2010 to 2019, this paper constructs a dynamic spatial DID model to empirically study the carbon reduction effect of the Clean Heating Policy and its influence channels. The results are summarized as follows. First, the Clean Heating Policy can significantly reduce carbon emissions, and this conclusion holds after multiple robustness tests. The policy has a lag effect, but its spatial spillover effect and long-term effect are not significant. Second, the carbon reduction effect of the Clean Heating Policy is mainly achieved by optimizing the energy structure and improving the thermal efficiency of heat consumer terminals. Third, the carbon reduction effect varies by city and emission field. It is significant only in low-subsidy cities, high-carbon cities, and household fields. Fourth, there is a synergistic reduction relationship between the Clean Heating Policy and the low-carbon city policy. Based on the results of this paper, we propose policy implications, such as promoting policies in multiple ways and improving subsidy efficiency, and provide a reference for other countries. [ABSTRACT FROM AUTHOR]

Under the policy background of "joint prevention and control" of global greenhouse gas emission reduction and regional air pollutants, the power industry, as an important target industry of energy conservation and emission reduction policies, has become an effective choice to release dual pressures. In this paper, the "bottom-up" emission factor method was used to measure the emission of CO2 and NOX from 2011 to 2019. Then, the contributions of six factors to NOX emission reduction in China's power industry were identified using the Kaya identity and logarithmic mean divisia index (LMDI) decomposition methods. The research results show that (1) there is a significant synergistic emission reduction effect between CO2 emission reduction and NOX emission reduction; (2) the factor that inhibits the growth of NOX emissions reduction in the power industry is economic development factor; and (3) the main factors that promote the reduction of NOX emission from the power industry are synergy effect, energy intensity, power generation intensity, and power production structure factors. Several suggestions are proposed, which are the power industry should adjust its structure, improve energy intensity, focus on applying low-nitrogen combustion technology, and improve the air pollutant emission information disclosure system to reduce NOX emissions. [ABSTRACT FROM AUTHOR]

Our paper investigates the association of renewable energy, financial development, urbanization, and growth in China along with technology. The newly developed econometric techniques (asymmetries) have been applied to explore short and long-run nonlinear relation among variables by utilizing annual data for the period of 1965–2021. In nonlinear cointegration, findings highlight the importance of renewable energy consumption for growth and development. Urbanization also confirms a positive association with growth and development where positive shocks were more dominant to support the growth process. The stock of technology brings a positive impact on growth and development whereas financial development results reveal to consider policy carefully. Asymmetric causality supports a uni-directional causal association between renewable energy, financial development, and growth. Policy recommendations are also highlighted according to the results. [ABSTRACT FROM AUTHOR]

Stimulating the shift to low-carbon energy and decreasing energy intensity are crucial strategies for green growth. Reducing energy intensity is an important measure to achieve the goal of "double carbon" and building a beautiful new China. Based on the provincial panel data of China from 2011 to 2020, this paper empirically tests the relationship among digital financial inclusion, industrial structure distortion, and energy intensity by using the spatial Durbin model and the intermediary effect method. The results show that the development of digital financial inclusion can promote the decline of energy intensity, and industrial structure distortion has a partial intermediary effect in the relationship between digital financial inclusion and energy intensity. Because of this, it is important to speed up the development of digital financial inclusion, increase the innovation of digital financial inclusion products and services, strengthen the supervision of digital financial inclusion, and reduce the distortion of the industrial structure so that digital finance can play its full role in reducing energy intensity. [ABSTRACT FROM AUTHOR]

Low-carbon transition has gradually become the focus of research on environmental issues. This paper takes China's eight major economic regions as the entry point. First, carbon emissions are measured according to United Nations' baseline methodologies. Second, the stochastic nonparametric data envelope analysis (StoNED) model is used to measure energy efficiency to improve the accuracy of the measurement. Finally, considering the temporal and spatial nonstationarity of carbon emission data, this paper constructs geographically and temporally weighted regression-stochastic impacts by regression on population, affluence, and technology (GTWR-STIRPAT) model, which can accurately analyze the impact of each driving factor of carbon emissions. This paper also explores efficient emission reduction paths in conjunction with the forcing mechanism. According to the study, China's carbon emissions show a decreasing trend from coastal areas to inland areas. In addition, there are significant problems with carbon emissions in China: some regions focus on improving energy efficiency but neglect increasing energy consumption; some regions focus on industrial development but neglect long-term emission reductions. Among the driving factors, energy efficiency, foreign trade, environmental regulations, and industrial structure have the effects of spatiotemporal heterogeneity, spatial heterogeneity, and time lag on carbon emissions, respectively. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to determine the spatial spillover effects of renewable energy on carbon emissions in China's less-developed areas. However, few studies have considered this issue from the perspective of less-developed areas. Based on panel data of 21 provinces in China from 2000 to 2017, this paper analyzes the spatial spillover effects of renewable energy on carbon emissions using Moran's I and Spatial Durbin Model (SDM). The results suggest that, first, Moran's I ranges from 0.378 to 0.519, Moran scatter plot presents that provinces are located in the high–high (HH) and low-low (LL) quadrants, indicating provincial carbon emissions in the study area have a significant spatial correlation and agglomeration. Second, under the three matrices, the direct effect coefficients of renewable energy are -0.2522, -0.2639 and -0.2601, this shows that renewable energy is beneficial to local carbon emissions reduction. In contrast, the indirect effect coefficients of renewable energy are 0.0605, 0.1012 and 0.1125, which means higher renewable energy consumption in a single area is conducive to the improvement of carbon emissions to neighbouring areas. Third, urbanization, industrialization, physical capital and other variables have different impacts on local and nearby carbon emissions. This study provides empirical evidence to achieve carbon emission reduction targets by government policymakers. [ABSTRACT FROM AUTHOR]

Energy is an essential factor for the survival of industries. Energy can affect the industrial productivity related to the economic activities, and the fluctuation of energy price will influence the final energy consumption level. In this paper, we use the input–output price model to study the relationship between the fluctuation of energy price and the change of economic level under different price control scenarios. The results show that the energy price fluctuation has high conduction efficiency on the general price index in the non-price-regulated scenario. Comparing the simulation results obtained from different years, this paper found that the magnitude of price conduction effect is closely related to the proportion of energy consumption. When the energy price is regulated by the government, the conduction effect of the energy price is limited. The policy effectiveness of regulation is related to the extent of price volatility of energy sources located at the upstream of the production chain of the regulated object. Through the SVAR model, this paper also found that the conduction effect of energy price fluctuation has obvious hysteresis, and the lag period of conduction effect on PPI is longer than that on CPI. [ABSTRACT FROM AUTHOR]

The sustainable development of China's economy is bottlenecked by resource shortage and environmental pollution. As the leading resource consumer and pollutant source, the industrial sector needs to improve its energy efficiency. This paper establishes a super epsilon-based measure (Super-EBM) model with bad outputs like environmental cost and evaluates the industrial green total-factor energy efficiencies (IGTFEEs) of 30 provinces in China during 2000–2017. Unlike previous research, the main contribution of this paper is to choose four environmental pollutants as bad outputs (industrial carbon dioxide, industrial sulfur dioxide, industrial chemical oxygen demand, industrial solid waste). By contrast, the previous studies mostly only take one environmental pollutant as bad output, i.e., the bad outputs are not fully measured. Then, the spatiotemporal dynamics and spatial correlations of the IGTFEEs were analyzed, and the influencing factors of IGTFEE were examined empirically with a spatial econometric model. Finally, this paper adopts generalized method of moments (GMM) to solve the endogenous problem, trying to assure the robustness of estimation results. The results show significant provincial differences in IGTFEE. Most eastern coastal provinces achieved satisfactory IGTFEEs, while most inland provinces had undesirable IGTFEEs. Eastern region achieved the highest IGTFEE, followed by central region; western region had the lowest IGTFEE. The IGTFEE improved over time in some provinces while worsened greatly in some provinces. The IGTFEE in most provinces need to be further improved. Global Moran's I values indicate that the provincial IGTFEEs were clustered in space, rather than randomly distributed. Local indication of spatial association (LISA) map reflects significant local spatial clustering of provincial IGTFEEs. In addition, IGTFEE is significantly promoted by industrial structure, technological innovation, human capital, opening-up, and energy structure yet significantly suppressed by ownership structure and environmental regulation. Considering the endogeneity, GMM results show that the estimation results of the model were robust. Specific policy recommendations include vigorously developing high-tech industries, deepening state-owned enterprises reform, diverting more funds to research and development, cultivating versatile talents, introducing environmentally-friendly foreign capital, accelerating the implementation of clean energy development strategy, and widening the fund channels of pollution control investment. [ABSTRACT FROM AUTHOR]