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Green innovation (GI) can increasingly contribute to green total factor productivity (GTFP) in the process of high-quality development transformation. However, the heterogeneous, spatial, and non-linear characteristics of GI are usually ignored when investigating its impact on GTFP. Using panel data on 275 Chinese cities from 2004 to 2022, two-way fixed, spatial Durbin, threshold, and mediation effect models are adopted to comprehensively examine how GI affects GTFP. The benchmark regression shows that GI can promote GTFP, and this result is maintained after robustness tests. The invention innovation is more likely to increase GTFP than green utility and green design innovations; furthermore, the enhanced impact driven by GI is primarily manifested via technological progress. GI can promote GTFP in neighboring regions through spillover effects under various spatial weight matrixes. Using the technological gap as the threshold variable, GI can promote GTFP through a gradually increasing feature. Furthermore, industrial upgrading, pollution reduction, and factor agglomeration are the three main mechanisms through which GI promotes GTFP. Based on the perspective of GI promoting sustainable development, the findings of this paper provide valuable recommendations for formulating GI and sustainable development policies. [ABSTRACT FROM AUTHOR]

In 2020, China pledged at the United Nations General Assembly to achieve carbon peaking by 2030 and carbon neutrality by 2060, and so far, China has made remarkable achievements in actively realizing carbon emission reduction and maintaining the international ecological environment. Among them, the role played by the technological progress bias of different elements is worth paying attention to. In addition, according to the current situation of energy consumption in China, based on the capital-labor technological progress bias, considering the introduction of the direction of technological progress of the energy factor plays a key role in analyzing the carbon productivity of China. This study utilizes panel regression to explore the paths and effects of capital-labor and factor-augmenting technological progress biases on carbon productivity. We also closely examine the regional heterogeneity and spatial spillover effects of technological progress biases. This study is based on inter-provincial panel information from China from 2006 to 2020. The study found that: (1) When the technological progress bias favors the capital factor among capital and labor, it will significantly increase the level of carbon productivity; The introduction of energy factor innovations,energy-enhanced technological progress, base on the technological progress bias of capital and labor will significantly reduce the level of carbon productivity. (2) Through the threshold model analysis, it is found that there is a nonlinear effect of technological progress bias on carbon productivity. Among them, in capital-biased and energy-enhanced provinces, the impact of capital-technology progress bias on carbon productivity shows an inverted "U" trend of first increasing and then decreasing. (3) In capital-labor technological progress, when technological progress is biased toward capital, it will significantly increase carbon productivity in the Northeast, East and West regions, while the opposite is true in the Central region, and the spillover effect of capital-labor technological progress is not significant; energy-enhanced technological progress bias has a negative impact on carbon productivity in all four major regions, and there is a significant spillover effect in all four major regions. [ABSTRACT FROM AUTHOR]

The chemical industry is one of the fundamental industries of economic development. Coordinating the relationship between economic growth and carbon emissions (EGCE) is crucial in realizing the carbon neutrality target. The Tapio model and decomposition models are used to assess the degree of decoupling within the Chinese chemical industry and identify pivotal factors impeding progress. The energy efficiency decomposition model explores the crux of failure to achieve strong decoupling. This framework further decomposed the energy intensity to uncover how technical efficiency, technological progress, and input substitution changes affect energy intensity and CO 2 emission. The paper found that the EGCE of the chemical industry were stable in a weak decoupling mode from 2009 to 2019. The reliance on technological progress to reduce energy intensity and emissions is insufficient (accounting for only 18.2%), far below the cumulative contribution from economic growth (accounting for 57.76%), which has become the crux of the strong decoupling failure. Technological advancements drive energy substitution for labour, resulting in 244.41 Mt of cumulative carbon emissions. The improper factor input allocation hinders the desired reduction in energy intensity and carbon emissions. A series of policy implications are proposed based on the insights derived from the decomposition analysis to foster sustainable practices in the chemical industry. [Display omitted] • This study focuses on the decoupling in chemical industry. • The decoupling between economic growth and carbon emissions (EGCE) is explored. • The reasons for the failure of strong decoupling from technical perspective are tested. • The decoupling between EGCE of chemical industry was in a weak decoupling mode. • Technological progress accelerated the substitution of energy for labour. [ABSTRACT FROM AUTHOR]

Climate aid is a form of official development assistance that addresses climate change mitigation and adaptation and plays a crucial role in combating climate change. However, existing empirical evidence does not suggest a clear link between climate aid and carbon lock-in. Based on country-level panel data from 77 countries spanning the period 2002–2020, this paper empirically examines the impact of climate aid on carbon lock-in and the four sub-indicators of carbon lock-in. Moreover, we investigate the mediating role of technological progress and potential impact mechanisms. We find that (1) climate aid has a significant restraining effect on carbon lock-in, and is an effective means of inhibiting the four aspects of carbon lock-in, namely, the lock-in of industry, institution, technology, and social behavior. (2) Technological progress not only directly leads to carbon lock-in eradication, but also synergizes with climate aid, suggesting that the combined influence of technological progress and climate aid can enhance the efficacy of efforts to mitigate carbon lock-in. (3) Climate aid promotes carbon lock-in mitigation by accelerating energy structure transition and industrial structure transition, which are two internal impact mechanisms in the nexus between climate aid and carbon lock-in. These findings offer concrete and practical policy implications to facilitate the development of climate aid and carbon lock-in eradication. • This paper estimates the impact of climate aid on carbon lock-in. • Climate aid significantly mitigates carbon lock-in and its four dimensions. • Technological progress can further strengthen the inhibiting effect of climate aid on carbon lock-in. • Climate aid indirectly affects carbon lock-in by promoting energy structure transition and industry structure transition. [ABSTRACT FROM AUTHOR]

Artificial Intelligence (AI), as the core driving force of industrial and technological innovation, has brought technological advances that profoundly affect energy conservation and carbon emission reduction in China. This study constructs a dynamic spatial Durbin model to empirically analyze AI's mechanism path using Chinese inter-provincial panel data as a sample. The findings show the following: (1) Spatial and temporal variations exist in AI development levels and energy conservation and carbon emission reduction. (2) AI has a significant negative impact on energy consumption efficiency and a significant negative spatial spillover effect on carbon emission efficiency, and the effects of AI development level on energy conservation and carbon emission reduction are mainly dominated short term. (3) Green technological progress on both the input and output sides has not played a determinant role in the effects of AI on energy conservation and carbon emission reduction. (4) Given the moderating effect of the degree of factor market development, the improvement of green technological advances can play a positive role in the impact of AI on energy and carbon reduction. These findings suggest the need to provide policy support for energy conservation and carbon emission reduction by improving the spatial and regional linkage mechanism to narrow spatial and temporal differences in development levels, formulating AI policies addressing regional heterogeneity to promote the full transformation of AI's short-term effects into long-term effects as well as emphasizing the negative role of green technological advances and accelerating the transformation of green technological achievements, among other measures. [Display omitted] • A dynamic indicator system for regional AI development in China is constructed. • AI effects on energy conservation and emission reduction are explored. • A dynamic spatial Durbin model shows regional and temporal heterogeneity. • Green technological progress has negative effects that should be emphasized. • Mature market element development can realize the positive green effects of AI. [ABSTRACT FROM AUTHOR]

Renewable energy consumption is a crucial aspect of global sustainability efforts, particularly in light of climate change mitigation and the pursuit of energy security. Technological innovation can play a pivotal role in driving the advancement and adoption of renewable energy. However, geopolitical risks can exert profound influences on the landscape of renewable energy deployment, posing challenges to energy security and the transition to a sustainable energy future. This study contributes to the existing literature by providing new empirical evidence on how geopolitical risk, along with technological innovation, environmental taxes, and environmental degradation affect renewable energy consumption in G7 countries. The findings indicate that geopolitical risks exert a negative influence on renewable energy consumption in G7 countries, whereas environmental degradation, technological advancements, and environmental taxes have positive effects. The results further indicate that at different quantile levels, the impact of each variable on renewable energy consumption has heterogeneous characteristics. Panel Grager causality results revealed a one-way causal relationship between environmental taxes and renewable energy consumption, while other variables have a two-way causal relationship with renewable energy consumption. Based on the results, the study suggests design policies to address geopolitical tension, increased funding for research and development to drive technological innovation, and supportive regulatory frameworks that incentivize renewable energy investment and innovation to achieve Sustainable Development Goal 7 (SDG7). • Explored the determinants of renewable energy consumption in G7 countries. • Advanced panel data estimation methods are employed. • Geopolitical risk negatively affects renewable energy consumption. • Technological innovation and taxes promote renewable energy consumption. • Designed a policy framework to achieve Sustainable Development Goal 7. [ABSTRACT FROM AUTHOR]

This study introduces three production technology shocks (Energy manufactures, Brown enterprises, and Green enterprises) by constructing different models, namely, the environment sector (baseline) model, the carbon emissions trading scheme (ETS) model, and the carbon emissions rights trading mechanism. The fluctuation trend of China's macroeconomic and environmental quality before and after the establishment of carbon market is compared and analyzed. Additionally, the study examines the welfare of the implementation of carbon market policies. The carbon trading market policy can promote the synergistic efficiency of China's pollution reduction and carbon reduction using energy and green production technologies. From the perspective of social welfare, the optimal range of the initial carbon quota ratio issued by the government to enterprises is [0.7,0.8]. The findings of this study provide theoretical support and contribute toward understanding the impact mechanisms of carbon market and technological progress on synergizing the reduction of pollution and carbon emissions in China. [ABSTRACT FROM AUTHOR]

The improvement of the environmental efficiency in the power industry is crucial in promoting energy conservation and emission reduction to achieve sustainable development. This study constructs a multi-hierarchy meta-frontier BAM model to measure environmental efficiency considering technological and regional heterogeneity. Using this model, we measure and decompose the environmental efficiency of the power industry in 30 Chinese provinces during 2008–2020. The main results are as follows. (1) Beijing and four other provinces have the highest environmental efficiency among the high-technology group, while Jiangsu and Hainan have the highest environmental efficiency among the medium-technology and low-technology groups, respectively. There are significant differences in environmental efficiency among provinces within each technology group. (2) Regional and technical inefficiencies in the high-technology and medium-technology groups are the main factors influencing inefficiency. However, the inefficiency of the low-technology group is 0.36, while technical inefficiency is 0.34. (3) The environmental efficiency of all three technical groups has improved as a result of technological progress. Environmental efficiency improvement is the largest in the high-technology group but only by 1%. This study extends conventional approaches of environmental efficiency assessment and enhances the comprehension of the operation of the power industry in various Chinese provinces. The research outcomes provide insights for formulating more precise and effective strategies towards the sustainable evolution of China's power sector. • The efficiency is measured by the combined model from a new perspective. • The technology, the management, and the regional heterogeneity are studied. • Each efficiency of each province is ranked as follows, RE > TE > ME. • The environmental efficiency improved in all three technical groups. [ABSTRACT FROM AUTHOR]

Digital development is critical for achieving coordinated regional economic growth, energy conservation, and emissions reduction, which makes it a viable method for achieving carbon neutrality and peaks. This study investigates the impact of the digital economy on urban total factor productivity and carbon emissions, as well as its mechanism, from 2011 to 2019 by developing a digital economy evaluation index system. We find that the growth of the digital economy can increase urban total factor productivity while lowering carbon emissions and also has a significant spatial spillover effect on regional economic growth, energy conservation, and emissions reduction. The main influencing mechanism is that the digital economy accelerates marketization by encouraging industrial structure upgrades and technological progress, which results in higher total factor productivity and lower energy consumption. In terms of the spatial distribution, the digital economy promotes total factor productivity more in the central and western regions and large cities and promotes carbon emission reduction less in the eastern regions and smaller cities. The findings extend the benefits of the digital economy beyond economic and social welfare benefits and serve as a model for achieving a win–win situation in terms of both economic growth and carbon emissions reduction. [ABSTRACT FROM AUTHOR]

Green transformation is currently a major challenge for both developed and developing economies, while the role of environmental insurance (EI) in green productivity in developing economies remains unclear. Using firm-level data from Chinese A-shape listed companies, this study investigates the relationship between EI on green total factor productivity (GTFP) along the period 2010–2019. To do so, a slack-based measurement model integrated with Global Malmquist-Luenberger approach (SBM-GML) is applied in GTFP calculation, and then a time-varying difference-in-difference (DID) setup is employed for empirical analysis, as well as its combination with propensity score matching method (PSM-DID) to overcome the sample self-selection bias. We find that EI significantly promotes firm's GTFP by about 0.22 units, which is mainly driven by the improvement of technical efficiency rather than technological progress. Further analysis exploring channels suggests that EI promotes GTFP by alleviating financing constraints and stimulating green innovation. However, the heterogeneity analysis shows that both financing constraint mechanism and technological innovation mechanism are mainly observed in heavily polluting and non-state-owned enterprises (non-SOEs). Our findings provide a new insight for policy-makers that utilizing environmental insurance can promote green productivity, but which should be focused more on those enterprises who are difficult to absorb external financing and technological innovation resources. • The relationship between EI and GTFP in the context of China was investigated for the first time. • The promoting effect of EI on GTFP is mainly reflected in the improvement of technical efficiency. • EI promotes GTFP by alleviating financing constraints and simulating technological innovation. • Both financing constraints and technological innovation mechanisms exist in non-SOEs and heavily polluting enterprises. [ABSTRACT FROM AUTHOR]

Optimizing the green use efficiency of cultivated land in the karst region of southwest China is crucial for promoting sustainable development of land resources and achieving harmony between humans and nature. Based on the epsilon-based measure model and geographically and temporally weighted regression methods, this paper investigated the spatio-temporal variation and influencing factors of cultivated land green utilization efficiency. The results indicated that: i) Cultivated land green utilization efficiency had slightly increased from 0.842 in 2000 to 0.866 in 2020. ii) The spatial pattern of cultivated land green utilization efficiency showed a significant positive correlation, with a "hotspot-not significant-coldspot" from north to south. iii) Its spatial heterogeneity had increased during the observation period, with high-efficiency areas shifting from northeast to north. iv) The proportion of agricultural economy, general public budget revenue, per unit cultivated land value had a positive impact on the cultivated land green utilization efficiency, while urbanization rate, per capita cultivated land area, land replanting index, average altitude had a negative impact. Moreover, the driving factors exhibited significant spatiotemporal heterogeneity. Therefore, it is necessary to promote technological progress and scientific research, implement funds and policies, leverage the leading role of high-efficiency areas, formulate differentiated development strategies, and thereby improve the green use efficiency of cultivated land. • Cultivated land green utilization efficiency had slightly increased. • The high-efficiency area distribution changed from northeast to due north. • The driving factors exhibited significant spatiotemporal heterogeneity. • The differentiated policies promote the effective use of cultivated land. [ABSTRACT FROM AUTHOR]

Obtaining the most economic benefits while using the least resources and causing the least environmental damage is an urgent and key problem in achieving sustainable development. The concept of eco-efficiency provides a comprehensive perspective for observing and solving this problem. This paper proposes an extended data envelopment analysis model, named the WIN-US-SBM, as a comprehensive eco-efficiency evaluation method that can accommodate undesirable outputs, all the identification problems of decision-making units (DMUs), possible slacks of variables, and the problems of an insufficient number of available DMUs and intertemporal comparability. China's Western Taiwan Straits Economic Zone (WTS Economic Zone) is an important regional economic growth center. By applying WIN-US-SBM and ArcGIS software, we investigated data on the temporal and spatial evolution characteristics of eco-efficiency in the WTS Economic Zone for the years 2009–2016. Later, the global Malmquist–Luenberger index was used to decompose the sources of growth in eco-efficiency. Finally, the main driving factors of eco-efficiency were explored through a Tobit regression analysis. The empirical results show that: (1) The overall eco-efficiency of the WTS Economic Zone had greatly improved, increasing by 11.46% annually, and the cumulative growth rate of eco-efficiency was 110.84% from 2009 to 2016. (2) The eastern area had the highest average eco-efficiency, followed by the western area and the middle area in that order. Also, the growth rate of the middle area ranked first (16.68%), whereas the eastern area had the slowest growth in eco-efficiency (7.22%). (3) On the whole, the growth of eco-efficiency was driven mainly by technological progress and was restricted by the decrease in management level, which implies that policy makers should focus on improving management and technical levels. (4) High levels of economic development, population density, market openness, and industrial structure had positive effects on the eco-efficiency of the WTS Economic Zone, whereas energy intensity and expenditure on science and technology had negative impacts. • An extended DEA model is proposed to measure eco-efficiency more comprehensively. • The proposed model can be widely applied to input-output efficiency evaluations. • The eco-efficiency of the WTS Economic Zone was evaluated based on a novel model. • The growth of eco-efficiency was driven mainly by technological progress. • The eco-efficiency level is negatively related to energy intensity. [ABSTRACT FROM AUTHOR]

High-quality economic development focuses on achieving effective qualitative improvement and reasonable quantitative growth in the economy, which is the essential way for China to achieve sustainable development. This paper aims to investigate the role of financial development in the impact of foreign direct investment on high-quality economic development. GDP and green total factor productivity are used to measure the quantity and quality of economic development, respectively. We construct benchmark panel regression models, nonlinear interaction term models, and panel threshold models to examine the threshold effect of FDI on high-quality economic development based on the scale, structure, and efficiency of financial development. A series of tests are conducted to check the robustness of the estimates. Our results show that green total factor productivity in China is primarily driven by green technology progress. Additionally, foreign direct investment has a positive impact on China's high-quality economic development, with a threshold effect and nonlinear characteristics. Specifically, the scale of financial development affects the influence of foreign direct investment on the quantity of economic development, while the efficiency of financial development affects its influence on the quality of economic development. Furthermore, the structure of financial development affects both the quantity and quality of economic development. This study presents novel findings that contribute to understanding the role of financial development in the impact of foreign direct investment on high-quality economic development. Likewise, our research has implications for achieving high-quality development. The introduction of foreign direct investment under the high-quality development of the economy should comprehensively consider financial development. • The impacts on high-quality economic development of financial development and FDI were discussed. • The scale, structure and efficiency of financial development were considered. • Both quantity and quality of economic development were focus on. • The green total factor productivity in China was measured. • Policy implications of introducing FDI in China were proposed. [ABSTRACT FROM AUTHOR]

Ecological compensation is a critical strategy that can be used to promote regional cooperation for the improvement of air pollution control. Overall, this study considers the relationship between air pollution production and economic growth; through this, we incorporate elements such as ecological compensation, technological progress, and PM 2.5 , into the framework of sustainable development theory. Under the constraints of the air pollution control objectives, a dynamic computable general equilibrium model was constructed to analyze the efficiency of air pollution control and responsibility allocation in the Yangtze River Delta region. Overall, this study yielded several findings. First, with each 10 billion yuan allocated for ecological compensation in the Yangtze River Delta region, there was an annual average carbon emission reduction of approximately 0.26%; this equated to an annual total carbon emission reduction of approximately 8.3 million tons per 10 billion yuan of ecological compensation. Additionally, the annual average PM 2.5 concentration was determined to reduce by 0.72 μg/m3 per 10 billion yuan of ecological compensation; this indicated that effective ecological compensation can lead to a significant improvement in air pollution control. Second, the initial allocation of ecological compensation was distributed in the following order, from the highest to lowest burden: Jiangsu, Zhejiang, Anhui, and Shanghai. Third, we calculated the responsibility for air pollution control; this indicated that local contributions to the inter-regional external transmission of air pollution by the Jiangsu, Zhejiang, Shanghai, and Anhui regions were 65%, 62%, 53%, and 84%, respectively; in contrast, the external contributions to their surrounding regions were 35%, 38%, 47%, and 16%, respectively. Overall, Anhui possessed a higher responsibility for internal responsibility transfers among Jiangsu, Zhejiang, and Shanghai, highlighting the role of Anhui in the fossil fuel industry within the Yangtze River Delta region. Finally, the present study established that there were significant variations in the redistribution of ecological compensation among provinces and cities within the Yangtze River Delta region. Redistribution lead to a reduction in ecological compensation by approximately 1/4 in Zhejiang and Shanghai and approximately 4% in Jiangsu; conversely, this redistribution nearly doubled the ecological compensation allocated to Anhui. Overall, the appropriate allocation of responsibility pertaining to internal trade transfers (i.e., fossil fuels trade) in air pollution and inter-regional external transmission (i.e., air spillover) is crucial for effective air pollution control in the Yangtze River Delta region and other parts of China and, therefore, requires immediate attention. [ABSTRACT FROM AUTHOR]

Various environmental tools have been developed to assist in decision-making on waste electrical and electronic equipment (WEEE) management, including life cycle assessment (LCA). In this paper, a total of 61 previous studies were explored to gain insight on current practices, progress and challenges of LCA application in WEEE management. The collection of existing LCA studies in WEEE management has been based on previous studies published since 2005. The content analysis was employed to systematically characterize and classify the existing LCA studies in WEEE management into several groups based on its research area and scope. Various aspects on current LCA application in WEEE management were analysed and it was found that the number of the related studies increased significantly in recent years. Three main research areas of LCA studies in WEEE management were identified, with various research scopes and types of WEEE were used as research subjects. The combination of LCA methodology with other methods becomes a common practice in LCA studies in WEEE management in order to include the interpretation of different dimension such as economic. Finally, the current practices, progress and challenges of LCA application in WEEE management were discussed, and future recommendation was provided. • A total of sixty-one LCA studies in WEEE management were reviewed. • Various aspects of LCA studies in WEEE management were evaluated. • Content analysis was employed to characterize the LCA studies in WEEE management. • Current practices and challenges of LCA studies in WEEE management were discussed. [ABSTRACT FROM AUTHOR]

On the path to industrialization, the energy and environmental problems caused by the rapid growth of the manufacturing industry have attracted widespread attention. At the top scale of technological innovation, high-tech manufacturing is considered to have achieved a balance between the "Made in China 2025" strategy and energy conservation. Therefore, in this paper, we explore inter-factor substitution and the influence of different sources of technological progress on China's high-tech industries using an estimation model that incorporates a translog cost function and the 'panel seemingly unrelated regression' method. Changes in energy intensity are further decomposed into different causes including budget, output, factor substitution, and technological progress at various points throughout the period under study. The empirical findings show Morishima substitutions among three different input factors. The substitution elasticity between labor and energy is the highest, and further most sources of technological progress are biased toward saving energy. Technological progress and budget are the critical driving forces throughout the period. However, the effect of factor substitution has gradually increased in recent years. From a regional perspective, energy intensity in the Beijing-Tianjin-Hebei region shows the most apparent decline, while the smallest decline occurs in China's western region. [ABSTRACT FROM AUTHOR]

Based on the panel data of 30 provinces in China from 2006 to 2016, the Gaussian kernel density estimation was initially used to describe the characteristics of the inter-provincial differences in household energy consumption (HEC), a dynamic panel data model was established secondly to study the main factors affecting HEC, and finally the counterfactual decomposition method was used to calculate the contribution of each factor to the inter-provincial differences in HEC. The research results are shown as follows: First, the inter-provincial HEC in China shows a phenomenon of agglomeration and growth, and the HEC level of different regions presents difference and imbalance. Second, the logarithms of consumption habits, total population and residents' income have significant effects on the logarithm of HEC, the influence coefficients are 0.191, 0.073 and 0.745, respectively; HEC not only has significant inertia characteristics, but also has certain population size effect and wealth effect. Third, the logarithms of technological progress, urbanization and household energy price have significant effects on the logarithm of HEC, the influence coefficients are 0.864, 0.195 and −0.346, respectively; the HEC saved by technological transformation is not sufficient to offset the increase in HEC demand, urbanization can improve HEC significantly, but the household energy price significantly inhibits HEC. Finally, from the perspective of contribution, the total population, residents' income and urbanization contribute a lot to the inter-provincial differences, totaling 73.02%. The possible innovations of this paper are as follows: First, the contribution of the influencing factors to the difference of inter-provincial HEC is studied, which is rarely seen in the previous literature. Second, compared with traditional decomposition method, counterfactual decomposition method is more convenient for economic interpretation. Third, the divergent conclusions of scholars are pointed out in this paper, and the actual impact of influencing factors on HEC are clarified. Image 10086681 • The level of inter-provincial HEC shows difference and imbalance. • HEC has significant inertia characteristics, population size effect and wealth effect. • HEC saved by technology is not sufficient to offset the increase in HEC demand. • Total population, residents' income and urbanization contribute 73.02%. • The statistical analysis tool used in this paper is Stata15. [ABSTRACT FROM AUTHOR]

Eco-efficiency is of great significance in the attainment of a sustainable society, and is the most severe issue facing industrial sectors in China. In this work, a hybrid super-efficiency data envelopment analysis (DEA) was conducted to measure eco-efficiency and analyze the problem of inefficiency facing industrial sectors in China. DEA has been widely used in eco-efficiency analysis; however, existing DEA models focus on the evolution and comparison of eco-efficiency values, and do not consider the evolution characteristics of the input nor undesirable output inefficiency and neglect the radial and non-radial classifications of input and output indices simultaneously. Thus, this work proposes a hybrid super-efficiency DEA model which combines hybrid DEA with super-efficiency DEA, separating the input and undesirable output variables into radial and non-radial parts using variable correlations. For the panel data of the industrial sectors, the Malmquist index is introduced in this approach. Subsequently, this approach is illustrated using a real data set from 22 industrial sectors in China corresponding to the period of 2006–2015. Results show that eco-efficiencies of the 22 industrial sectors increased consistently from 2006 to 2015. Due to a lack of momentum in sustained growth, technological progress regarding the improvement of eco-efficiency requires acceleration. More and more sectors have achieved rapid enhancements in input and undesirable output inefficiencies, but 10 traditional sectors with high resource consumption and heavy emissions of pollutants remain inefficient. • A hybrid super-efficiency DEA model is proposed to measure eco-efficiency. • The Malmquist index is introduced in the DEA to deal with panel data. • The problem of inefficiency is studied by the definition of three efficiency states. • The approach is applied to measure eco-efficiencies of 22 industrial sectors in China. [ABSTRACT FROM AUTHOR]

Prior to the 21st century, China's industrialisation was mainly driven by investment; by contrast, it now relies on innovation-driven and environmentally friendly technology to achieve sustained and healthy growth. Spanning China's 11th-13th Five-Year Plans (2006–2020), chemical oxygen demand and ammonia nitrogen emissions have been the key pollutants that require monitoring for waste water pollution management. To fit well into one of the focus areas under China's government policy direction, the main objectives of this study are to measure input- and output-based technological progress and their determinants for 30 provinces and regions in China from 1999 to 2015. A green-biased technological progress model based on the directional distance function is adopted in this study. The results reveal that sustainable growth in total factor productivity was primarily due to green-biased technological progress. Most provinces and regions in China overused water resources for industrial production, as demonstrated by the high water consumption over the study period, while output-biased technological progress exacerbated the discharge of water pollutants before the implementation of China's 11th Five-Year Plan (2006–2010). Technological progress in the eastern region was more likely to promote industrial growth, while progress in the central and western regions was likely to promote increased pollutant emissions. Furthermore, industrial research and development investment, governance of waste water treatment investment, the educational level of the labour force, and water prices contributed significantly to biased technological progress in China over the study period. Overall, this study has important policy implications and can provide guidance for emissions reductions to promote cleaner production and optimise resource allocation in China's industrial sector. • The green-biased technological progress of China's industrial sector is measured. • A modified directional distance function-based data envelopment analysis model is adopted. • Sustainable growth in TFP is primarily due to green-biased technological progress. • Technological progress in the eastern region promotes industrial growth. • The central and western regions in China emit more pollutants. [ABSTRACT FROM AUTHOR]

China has developed a remarkable economic growth in the past 30 years by accompanying with undesirable outputs. The assumptions of weak and strong of undesirable outputs have become the focus discussion in data envelopment analysis (DEA) models. To have a comprehensive environmental efficiency measurement, this paper proposes three DEA models considering weak disposability, strong disposability and distinguishing weak and strong disposability of undesirable outputs, respectively. We further combine with the Malmquist-Luenberger productivity index to assess the environmental efficiency and the dynamic change trend of 30 provinces in China from 2005 to 2014. The results show that distinguishing technical features of undesirable outputs makes a significant difference to final environmental efficiency score at different regions. The environmental efficiency of the whole nation, however, does not show any increasing trend during the ten years. Enhancing environmental efficiency of central and west area is an urgent task for Chinese government. The change trend of Malmquist-Luenberger productivity index and technological change shows a similar shape. Technical progress is the main driving force to enhance the environmental efficiency. Relevant suggestions are presented for improving the regional environmental efficiency in China in the future. [ABSTRACT FROM AUTHOR]

In recent years, the constant advancement of market reform in China improves the market allocation efficiency of production factors and further promotes the rapid growth of economic aggregate output in the country. Additionally, the CO 2 emitted in China also constantly increases. Based on panel data pertaining to 30 provinces from 1998 to 2015 in China, the CO 2 emission efficiency and marketisation level of China were separately measured using a super Slacks-based measure approach and generalised principal component analysis. On this basis, by utilising a dynamic panel regression model and a panel smooth transition regression model, the influence of market reform on CO 2 emission efficiency was explored. The results show that the marketisation level exerts a significantly positive effect on CO 2 emission efficiency in both models and the results are robust. On the condition of taking energy price as a threshold variable, the influence of process of marketisation is significantly greater than that when taking technological progress as a threshold variable. It implied that although energy price and technological progress both significantly promote the marginal effect of market reform on CO 2 emission efficiency, the energy price shows a greater influence than technological progress. Infrastructure construction and urbanisation can inhibit the improvement of CO 2 emission efficiency. Additionally, the proportion of secondary industries can delay the improvement of CO 2 emission efficiency. Image 1 • Conducting the study on the influence of market reform on CO 2 emission efficiency. • Measuring the CO 2 emission efficiency by applying a super-SBM model. • Establishing a PSTR model to analyse the non-linear relationship. [ABSTRACT FROM AUTHOR]

The ecological and environmental issues caused by climate change have affected human health and social development. Accordingly, scientists have focused on addressing climate change. IAMs (Integrated Assessment Models) have been widely used to assess the effect of global climate governance. Since the US withdrew from the Paris Agreement and the UK broke away from the European Union, global economic development takes on an uncertain path. The worldwide trade war triggered by the US has shown that international trade may be weakened in the future. The deglobalization in global economic progress forces individual innovation within countries. Therefore, we constructed a new IAM under autonomous economies—EMRICES-E (Expanded Multi-Regional Integrated model of Climate and Economy System-Equilibrium), which contains a layered structure of national computable general equilibrium (CGE) model to describe an individual country's development and analyzes the effects of global reductions in cooperation based on the new global situation. Considering that technical progress is a significant factor in carbon reduction, we introduced endogenous technical progress in CGE. Simulation results show that developing countries/regions have large carbon emissions under the baseline scenario with their economic status increasing at the same time, climate change would lead to economic recession if there are no carbon reductions for countries/regions and the industrial structure of developing countries changes noticeably compared with developed countries. • An IAM under autonomous economies is proposed. • Developing countries/regions hold high proportions in the world's carbon emissions. • Production decline and even economic recession may occur due to climate change. • Global temperature would increase by 4.92 °C without carbon reductions. [ABSTRACT FROM AUTHOR]

Under the background of global climate change, China has been confronted with the dual pressure of CO 2 emissions reduction and PM 2.5 pollution control. This research aims to explore the mechanism of changes in PM 2.5 emissions, which are the key airborne pollutants causing haze. Furthermore, it quantifies the impacts of CO 2 emissions reduction activities on PM 2.5 emissions reduction. This study takes aggregate PM 2.5 emissions instead of PM 2.5 concentration index as the research object. Based on an extended kaya identity, LMDI approach is first performed to decompose the changes of PM 2.5 emissions during 1998–2014, taking into consideration the synergistic effect of carbon emissions on PM 2.5 emissions. Furthermore, following LMDI decomposition, this study adopts the econometric methods to quantify the synergistic effect of CO 2 emissions reduction on PM 2.5 emissions reduction over the period 1999–2014. The empirical results are as follows: (1) the LMDI decomposition results specify that the synergistic emissions reduction accounts for the most of the reduction in PM 2.5 emissions. In addition, energy intensity changes also contribute to the reduction in PM 2.5 emissions; (2) by contrast, it is found that the economic development effect is the main factor resulting in the increase of PM 2.5 emissions, while the contributions of the energy emission intensity effect and population effect to PM 2.5 emissions changes are relatively little; (3) all the models show CO 2 emissions reduction activities will significantly contribute to PM 2.5 emissions reduction; (4) for every 10,000 t increase in CO 2 emissions reduction, PM 2.5 emissions reduction will increase by 3.3 t, and the potential for synergistic emissions reduction of PM 2.5 differs distinctly among different provinces; (5) technological progress and population density positively influence PM 2.5 emissions reduction, while coal consumption rate has a negative impact on PM 2.5 emissions reduction, in addition, there is an inverted U-shaped curve relationship between per capita GDP and PM 2.5 emissions reduction. • Considering the synergistic effect of CO 2 emissions in an extended Kaya identity. • LMDI decomposition is performed to study PM 2.5 emissions changes in China. • Furthermore, five proxy variables are introduced in econometric analysis. • CO 2 emissions reduction will significantly contribute to PM 2.5 emissions reduction. • EKC hypothesis is confirmed for per capita GDP and PM 2.5 emissions reduction. [ABSTRACT FROM AUTHOR]

Smartphones offer a wide spectrum of features and functions, are subject to fast technological progress, and have short production and replacement cycles. Prolonging their use-times through modular design can have a significant effect on their environmental impact. This cannot be achieved solely by producing robust and durable devices, because smartphone use-times are closely linked to their functional performance and symbolic meaning. Modularity strategies change the technological principles of existing devices, but also the human-object relationship between users and their smartphones. Maintaining continuous functionality and reinforcing attachment to the device can go hand in hand, but could also lead to drawbacks and rebound effects. In this interdisciplinary paper, we discuss the environmental potential and risks of modular smartphones, based on three specific scenario designs (Fairphone 2, PuzzlePhone, and Google ARA), taking users' functionality aspirations and practical needs into account. [ABSTRACT FROM AUTHOR]

Abstract Manufacturing industry is an important part of economic development. Recognizing the sustainable development of regional manufacturing has an important guiding role in the formulation of environmental policies. Based on the meta-frontier Malmquist-Luenberger (MML) productivity index, this paper uses Chinese provincial panel data (2003–2015) to measure the green total factor productivity (TFP) of China's manufacturing. It is decomposed into the following: efficiency change (EC), change of the best practice gap ratio (BPC) and change of technical gap ratio (TGC). We compared the regional differences in green TFP growth in manufacturing in all provinces, analyzed regional and time differences in green TFP and the decomposition of manufacturing between regions and identified innovative regions. The results show that: (1) The average annual growth rate of green TFP in Chinese manufacturing is 0.85% with technological progress playing a key role. (2) There are differences in the causes of the increase in green TFP in all regions. The eastern region and the western region are driven by technological progress while the central region depends on technology catch-up effects. (3) Guangdong and Qinghai are two different types of global innovation regions with Guangdong driven by technological innovation and Qinghai driven by strict environmental protection systems. [ABSTRACT FROM AUTHOR]

Abstract China's most important three urban agglomerations, the Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD) and Pearl River Delta (PRD), are expected to play a leading role in energy saving and emissions reduction in China. Based on the biennial Malmquist productivity index and the non-radial direct distance function, this study improved the data envelopment analysis (DEA) model to evaluate the energy-saving and emissions-reduction performance (EEP) of these three urban agglomerations. The empirical results indicated that BTH did not show improvement in performance, whereas YRD and PRD showed a significant improvement. The annual growth rate of performance was higher in the PRD than in the other two urban agglomerations. The "catch-up effect" of the three urban agglomerations vanished after 2010, and the possible reasons for this change are the large-scale economic stimulus plan adopted by the government to address the global crisis and the recent decline of economic growth. The technical progress level increased at first, then decline, and increased again. This study also found that β convergence of performance existed in BTH and YRD. However, there was no β convergence of performance in PRD. Highlights • The non-radial directional distance function is adopted to evaluate the EEP. • The "catch-up effect" and technical progress do not always exist in 2005–2016. • Pearl River Delta makes a significant improvement in EEP. • There exists β convergence of performance in BTH and YRD, while not in PRD. [ABSTRACT FROM AUTHOR]

Abstract Global offshore wind technology shows increasing progress evidenced in the recent reports of wind power capacity, expectations of market expansion and international research projects. Colombia is privileged with several types of natural resources (e.g. wind, sun, water) but there is not a clear legal context to regulate sustainable and safe exploitation of the offshore wind energy considered non-conventional. The development of offshore wind technology in Colombia could attend the energy demand when the hydroelectric system presents low electricity generation during dry hydrological conditions and El Niño – South Oscillations events. This paper analyses international actions that have motivated different countries to establish strategies to reduce CO 2 , and their advances and challenges in implementing offshore wind technology. The review of the administrative framework of renewable energy in Colombia proved the lack of information for implementing offshore wind technology. Furthermore, the analysis of several studies of marine energies showed the need to increase the knowledge of offshore wind energy. The local applying projects to generate electricity from non-conventional renewable energies are not considering offshore wind energy projects. Hence, this research analysed wind speed and calculated wind power density at different height levels, what evidenced magnitudes and positive trends what justify to increase the research in offshore wind energy in Colombia. As a result, the present document compiles technical, economic, administrative and legal information of the renewable energies in Colombia that may be used for taking decisions of different stakeholders and evidences the potential implementing offshore wind farms in areas near to the Colombian Caribbean coast. Colombia has great resources to implement offshore wind energy technologies, reducing the dependence on fossil fuels and substituting other systems when they cannot guarantee the energy offer. Graphical abstract Image 1 Highlights • Advances and challenges of the offshore wind energy around the world. • Legal and administrative framework of the renewable energy of Colombia. • Wind speed trends and power density results justify offshore wind energy research. • El Niño (2015–2016) put at risk to the Colombian electric system. [ABSTRACT FROM AUTHOR]

Abstract This paper explores the determinants of the development of the new energy vehicles (NEVs) industry in China, which is important to the government in controlling the environmental pollution associated with the urbanization process. Urban governance policies have played an important role in promoting the sustainable development of cities. In this study, we investigate the dynamic effects of such policies and of financial support on the relationship between firm size and efficiency in the NEVs industry. These policies include subsidies from state and local governments during the production and promotion of NEVs. The sample includes an unbalanced panel data set of 148 firms closely related to the automobile industry in the Zhongguancun Science Park from 2005 to 2015. A data envelopment analysis model and a random effects model are used to test the hypotheses, and the results show that both government policies and financial support are beneficial in increasing the efficiency of large NEVs firms. However, small firms cannot benefit from these policies. To promote the technological progress of the NEVs industry, it is highly important to provide further government support for the small NEVs firms that play a leading role in the development of emerging technologies. Only in this way can the government create a healthy market environment for the future of NEVs industry, and reduce the pollution in urban areas. Graphical abstract Image 1011 Highlights • This study focuses on the asymmetric effects of environmental governance policies. • Policies have different impacts on efficiency of NEV firms with different size. • Small firms can benefit from neither government policy nor financial support. • The sample includes an unbalanced panel data of 148 NEVs firms from 2005 to 2015. [ABSTRACT FROM AUTHOR]

Abstract Energy rebound effect is a major issue in energy economics. Global energy and environmental problems have compelled the need for simultaneous attainment of economic development and energy conservation. Technological progress increases energy efficiency and saves energy, but it also causes energy rebound effect which discounts the expected energy conservation. China's transport sector is energy-intensive. Therefore, investigating rebound effect in China's transport sector has a very important significance for energy conservation and the formulation of related policies. Taking China's transport sector as a case study, we used translog production function to measure the contribution rate of technological progress to output growth, and estimated the rebound effect. The results show that the average rebound effect was about 68.3% during 1981–2015. Finally, we provided relevant policy recommendations on the rebound effect based on the characteristics of energy use in China's transport sector. Highlights • We use the translog model to measure the contribution rate of technological progress. • The ridge regression method is used to estimate the model parameters. • We calculate the rebound effect from the perspective of technological progress. • The average rebound effect is about 68.3% during 1981–2015. [ABSTRACT FROM AUTHOR]

Abstract To clarify the spatial characteristics of CO 2 emissions, economic externalities of spatial units are transplanted into CO 2 emissions research. Furthermore, to identify emissions reduction pathways, spatial econometric models are constructed based on the patent data about energy conservation and emissions reduction. The key results are: (1) The kernel density plot of China's CO 2 emissions shows an obvious right-averse state, and the peak is getting lower. Therefore, we can conclude that CO 2 emissions in China are increasing, and polarisation of CO 2 emissions is serious; (2) Due to the similarity and connectivity exist in spatial units, China's CO 2 emissions have shown a stable spatial agglomeration effect from global and local perspectives; (3) Based on adjacent, geographic, and economic distance matrices, energy technological progress has played a positive emissions reduction role on China's CO 2 emissions from the perspective patent data about energy saving and emissions reduction. Finally, on the basis of the above conclusions, some policy implications have been proposed accordingly. Highlights • Polarisation of CO 2 emissions is serious in China, spatial agglomeration is recognised. • Spatial econometric model and patent data (represent technology progress) are applied. • Emissions reduction effect of technology on CO 2 emissions is identified. • CO2 Mitigation technologies development policy implications have been proposed. [ABSTRACT FROM AUTHOR]

This study aims to examine how carbon trading policies impact total factor carbon productivity and subsequently provide recommendations for sustainable regional development. Through analyzing the trends in total factor carbon productivity and its mechanisms, this paper suggests that carbon trading policies can significantly enhance total factor carbon productivity. Additional mechanistic tests reveal that carbon trading can promote technological progress, factor accumulation, scale allocation and energy substitution effects; all contributing towards a low-carbon economic transition. These four effects serve to both promote economic growth and contribute towards carbon reduction targets. Therefore, to encourage low-carbon and high-quality development of the region's economy, policymakers must focus not only on constructing and expanding carbon markets, but also emphasize the synergies between these different effects. [ABSTRACT FROM AUTHOR]

Under the background of "carbon peak" and "carbon neutrality", China's cities are at the heart of climate change mitigation. To fulfill the commitments, the potential drivers of China's low-carbon economy at the city level should be explored. Thus, this study estimated the quality of low-carbon economy from the perspectives of carbon emissions and sequestration. Subsequently, spatial econometric approach was adopted to analyze the direct and spatial spillover effects of drivers on low-carbon economy. Moreover, to explore more potential variables, this study combined machine learning algorithms with different weight matrices to assess the importance scores of neighbouring cities' potential variables. The results show that (1) GDP per capita, emissions reduction technological progress, terrestrial vegetation's net primary productivity and the ratio of forest land cover improved cities' low-carbon economy; (2) land urbanization reduced nearby cities' low-carbon economy (especially those with high human footprint index at the inter-city border), which was caused by its negative spatial spillover effects on forest net primary production; (3) based on importance analysis, this study found that the characteristics of different sectors (e.g., the ratio of labor to fixed capital stocks, employment and fixed asset investment expenditure) also significantly influenced nearby cities' low-carbon economy. • China's city-level quality of low-carbon economy (reo) was estimated based on carbon intensity and sequestration. • The importance of 72 variables' spatial spillover effects were ranked based on machine learning algorithms. • Terrestrial vegetation's net primary productivity and the ratio of forest land cover greatly improved the reo. • The spatial spillover effect of land urbanization was negative in nearby cities. [ABSTRACT FROM AUTHOR]

This study aims to investigate the effects of technological advancements, energy efficiency, and renewable energy utilization in Türkiye's fossil fuel sector on CO 2 emissions and to test the applicability of the Environmental Kuznets Curve (EKC) hypothesis. The EKC hypothesis has been confirmed for Türkiye, revealing an inverse U-shaped relationship between CO 2 absorption and per capita income. Furthermore, all variables display negative coefficients and show statistical significance in the long term. Thus, it has been established that technological progress, energy efficiency, and the adoption of renewable energy have a positive impact on reducing CO 2 emissions. Given Türkiye's status as an energy importer heavily dependent on fossil fuels, prioritizing technological advancements in the energy sector is crucial since complete abandonment of fossil fuels in the near future is unlikely. Moreover, efficient energy utilization plays a vital role in reducing energy imports, a substantial contributor to Türkiye's current account deficit. Furthermore, an increase in renewable energy will have a positive effect on Türkiye's economic and energy outlook. The uniqueness of these findings lies in the utilization of these significant variables, which have not been previously employed in the context of the Türkiye economy. [Display omitted] • Energy technology, energy efficiency and the use of renewable energy reduce CO2 emissions in Türkiye. • The efficient use of energy is the most important factor in improving environmental quality in Türkiye. • This study uses both standard and Fourier-based methods to analyze the data. • The Environmental Kuznets Curve (EKC) is valid for Türkiye. [ABSTRACT FROM AUTHOR]

Digital input, as an important engine for high-quality development, has provided new impetus for green transformation and development of manufacturing enterprises. In this study, unique panel data samples matched from the Global Multi-regional Input-output Database from 2000 to 2014, the Chinese Industrial Enterprise database, and the Chinese Industrial Enterprise Pollution Database are used to estimate the green productivity of Chinese manufacturing enterprises by adopting a non-radial and non-angular SBM model that considers unexpected outputs. Furthermore, a panel Tobit model is adopted to empirically test the impact of digital input on the green productivity of manufacturing enterprises. The research results indicate that: (1) Digital input has a significant positive impact on the green productivity of manufacturing enterprises, and a series of robustness tests have confirmed this conclusion. This research conclusion provides micro evidence and empirical support for empowering the green transformation of manufacturing enterprises with digital economic development. (2) The heterogeneity analysis indicates that, for different enterprises, digital input contributes more significantly to green productivity in foreign-funded enterprises, state-owned enterprises, and larger-scale enterprises. Regarding industry types, digital input positively contributes to green productivity only in labor-intensive and knowledge-technology-intensive manufacturing enterprises. In terms of regions, the contribution of digital input to the green productivity of enterprises in the east and central regions and regions with higher levels of industrial agglomeration is more significant. Heterogeneity analysis from different perspectives can help optimize enterprise choice behavior and green transformation development strategies, thus achieving better digital empowerment. (3) Further mechanism tests reveal that digital input promotes the improvement of green productivity of manufacturing enterprises through the effects of technological progress, factor structure optimization, and innovation, thereby providing a feasible path for relying on digital transformation to promote the improvement of green productivity of manufacturing enterprises. • The World Input-Output Database, Chinese Industrial Enterprise Database, and Chinese Industrial Enterprise Pollution Database from 2000 to 2014 are matched as a set of panel data to empirically test the impacts of digital input on green productivity of Chinese manufacturing enterprises. • Digital input has a significant positive impact on the green productivity of manufacturing enterprises in China. • Digital input promotes the green productivity of manufacturing enterprises in China through exerting technology effects, factor structure optimization, and innovation effects. • The promotion effects of digital input on green productivity of Chinese manufacturing enterprises present heterogeneity characteristics. [ABSTRACT FROM AUTHOR]

This study evaluates the effects of military expenditures (MEX) on environmental pollution, as well as the moderating role of factors such as financial development and technological progress for 15 NATO member countries under the environmental Kuznets curve (EKC) hypothesis. Using the CS-ARDL estimator, the study analyzes the effects of MEX, income, energy consumption, financial development, and technical progress on carbon emissions spanning the period from 1991 to 2018. Additionally, interaction terms are employed to regularize the moderating effects of financial development and technical advancement. The results show that income, energy consumption, and MEX all contribute to a rise in emissions. It is also found that the financial sector does not eradicate the detrimental ramifications of MEX on the environment, but that technological progress has a moderating effect. A 1% increase in the interaction of technological progress with the military sector reduces environmental degradation by 0.36, but a 1% augment in the interaction of the financial sector with the military sector increases carbon emissions by 0.41%. For this reason, it is imperative to evaluate and revise the financing of MEX of NATO countries from an environmental perspective for sustainable development. Furthermore, as long-run income elasticity in NATO countries is lower than the short-run one, the EKC hypothesis is valid. Based on the overall findings, the study suggests that NATO allies should incorporate the benefits of income growth and technological development into their environmental policies to offset the negative effects of MEX. [Display omitted] • Employs second-generation panel data approaches for NATO countries. • Examines the moderating role of technological progress and financial development. • NATO countries damage the environment with their military expenditures. • Technological progress has an environmental moderating role in the military sector. [ABSTRACT FROM AUTHOR]

Sustainable economic growth relies on an increase in total factor productivity (TFP). To upgrade the core competitiveness and support the sustainable growth and high-quality development of China's economy, ascending TFP in China's manufacturing industry counts. This study analysed the impact of biased technological progress on TFP, which was estimated by using the relevant data of 27 subsectors of China's manufacturing industry from 1980 to 2019. The results revealed that from the early industrialisation period (1980–2000) to the mid-industrialisation period (2001–2012) and then to the middle and late industrialisation period (2013–2019), the mean value of TFP in China's manufacturing industry grew from 0.291 to 0.394 and then to 0.555, embodying a continuously upwards advancing tendency. Technological progress was capital biased from 1981 to 2011 and labour biased during the rest of the sample period. In addition, its direction was heterogeneous among various industries. To some extent, the growth of TFP has been hindered by biased technological progress and factor allocation. The per unit increase in them has led to 1.495 and 1.017 unit decreases in the TFP. Upon examining the factor efficiency and the factor structure, we found that the estimated coefficients of biased technological progress dropped to −1.516 and −1.719, preventing TFP from growing to a greater extent. Consequently, there is room for their optimisation in China's manufacturing industry. [ABSTRACT FROM AUTHOR]

This paper establishes a translog cost function model with productivity growth equations to study the influence of technological progress and price changes on electricity production factors and consumption. Within a unified analytic framework, regression is applied to the panel data for seven regions in China during the period 1997 to 2013. The functions of production costs on factor substitution are analyzed based on the regression. The influence of electricity price and technological progress on electricity productivity and the rebound effect of electricity are discussed. Electricity price can significantly and positively influence electricity productivity (expressed by the total value of output consumed by unit electricity); however, the stimulation of technological progress is not notable. The rebound effect of electricity computed based on an electricity price breakdown showed that values of the rebound effect in Southwestern China and Central China were higher than 100% while annual average values of the rebound effect in Northeastern China and Southern China were −60.39% and −81.47%, respectively. The area with the lowest annual average value for the rebound effect was Northwestern China at 14.96%. [ABSTRACT FROM AUTHOR]

The aim of this work is to evaluate how the environmental impacts of the Romagna Compost composting plant (central Italy) have changed as a consequence of its expansion and adaptation. This led to a considerable evolution of the plant, from a traditional composting process to an integrated anaerobic-aerobic system. For this purpose, the Life Cycle Assessment (LCA) methodology was chosen. Inventory analysis was completed using mostly primary data supplied by the company. Plant performances were evaluated for each year of operation and by grouping data to analyze the main stages (storage and pretreatment of the organic waste, anaerobic fermentation, composting, etc.). The modelling was performed using SimaPro software and the ReCiPe analysis method. Seven scenarios were created to simulate the seven-year process. The aim of the study was to assess whether and how the introduction of anaerobic fermenters to produce energy from biowastes has led to a real improvement of the process sustainability with an overall decrease in environmental impacts. After analyzing in detail the performances of the plant, biowaste transportation and the avoided landfill disposal were also assessed. The main problems connected with transportation, and environmental benefits resulting from the avoided disposal of waste, were identified and in order to evaluate the robustness of the model, a sensitivity analysis using the Monte Carlo method was performed. [ABSTRACT FROM AUTHOR]

This paper deconstructs industrial green transformation into two aspects, industrial efficiency green transformation and industrial structure green transformation. We examine the impact of digital finance development on industrial green transformation using data from Chinese cities and listed companies. The results showed that: (1) digital finance can contribute to the green transformation of industrial structure distinctly but has an inhibiting effect on the green transformation of industrial efficiency. (2) Digital finance can promote capital-using technological progress and support industrial green transformation with its price effect and scale effect. (3) Higher government environmental preferences and governance capacity can strengthen the green transformation effect of digital finance. Strengthening financial supervision and narrowing the digital divide will help digital finance better support industrial green transformation. Digital finance development can more effectively promote the industrial green transformation of non-SOEs and enterprises with high financing constraints and high financial dependence. (4) Considering the financial attributes and highly polluting characteristics of real estate, digital finance exacerbates the pollution of the real estate industry. This study helps clarify the mechanism of digital finance supporting green development and provides some ideas for China's digital finance development and green economy transformation. • Deconstructing the industry green transformation (IGT) into EFFI and STRU. • Analyzing the synergistic effects of digital finance on the EFFI and STRU of the industry green transformation. • The positive impact of digital finance on the industry green transformation is statistically significant and robust. • The green transformation incentive effect of digital finance has significant heterogeneity. [ABSTRACT FROM AUTHOR]

As an important attempt to promote intensive development, new-type urbanization (NU) pilot programs have received increasing attention. However, most related literature does not clarify the relationships between the NU pilot, paths of technological progress, and carbon emissions. Thus, we constructed a difference-in-differences model to compare the differences in carbon emissions between NU-pilot and non-NU areas before and after implementing the pilot, with significant results. The NU pilot policies primarily affected carbon emissions through domestic R&D activities and intercity and FDI technology spillover. A sub-sample analysis considering city heterogeneity confirmed that the NU pilot had heterogeneous impacts on cities with different locations, administrative levels, population sizes, and sea front conditions. The pilot policies' technological action paths varied with changes in urban characteristics. The results imply that policymakers should tailor policies to pilot policy action paths and cities' local conditions. [ABSTRACT FROM AUTHOR]

The present trend of rapid expansion in the textile industry is highly polluting and energy intensive, and the government intervention is necessitated. This study develops a Data Envelopment Analysis (DEA) model, examines the green technology innovation of listed textile enterprises, and explores its determining factors in order to address the issue of carbon emission reduction in the textile sector. The research sample for this study is obtained from 42 listed textile enterprises from 2017 to 2020. The research demonstrates: (1) the green technology innovation efficiency of domestic listed textile enterprises remains marginal; (2) from 2017 to 2020, the mean value of total factor productivity (TFP) and its decomposition index of listed enterprises in China's textile industry exhibit a downward trend, primarily as a consequence of the slowdown of technological progress; (3) the green technology of the entire industry is in recession from 2017 to 2020; (4) green technology innovation efficiency is inversely correlated with government subsidies, but positively correlated with net profit and asset size of enterprises. In light of the above information, enterprises should boost their ability to innovate with green technologies and implement a research and development (R&D) management development strategy that gives equal consideration to both economic and environmental benefits. [ABSTRACT FROM AUTHOR]

The carbon tax, as one of the environmental regulation tools, is likely to promote technological progress, which is ignored in previous works when evaluating the economic impact of a carbon tax. This study uses the Generalized Method of Moment model to investigate the effect of an environmental tax on total factor productivity and energy efficiency, and takes the effects as approximations of the effects of carbon tax on technological progress into the computable general equilibrium model as well as considering technology diffusion, to analyze the dynamic impact of carbon tax on China's economy growth. A carbon tax policy negatively impacts GDP at the early stage, but technological progress would make GDP impacts "turn negative into positive" in the late stage. With a carbon tax rate of 100 Yuan/ton, the GDP impact becomes positive from the 4th year and rises to 0.3% in 2030. Not all industries can realize the output of "turning negative into positive," only low-carbon-intensity industries can achieve a clean transition. Overall, this study discusses the dual effects of a carbon tax on technological progress and increasing fossil energy costs, which provides a new perspective for an in-depth discussion of a carbon tax. [ABSTRACT FROM AUTHOR]

Adoption and improvement of energy efficiency is one of the recommended pathways to tackle the problems of growing energy demand and greenhouse gas emissions. However, studies show that rebound effects from energy efficiency improvements can erode anticipated energy savings. This paper elucidates the rebound effect arising from energy efficiency initiatives in Kenya. The study uses Index Decomposition Analysis to assess the drivers of Kenya's total primary energy supply. The paper then adopts the neoclassical growth model in the empirical analysis of energy and carbon rebound effects at the macro-economic level. Cobb-Douglas production function is further applied using Solow growth model and energy as a factor of production to approximate technological progress. Results of decomposition of energy supply show that energy intensity and affluence are the drivers with the most significant effect on energy supply while population has less critical effect. Average energy and carbon rebound effects show partial rebounds of 15.64% and 31.41%, respectively. These results imply that there is need to accelerate the pace of transitioning to green energy as the ultimate solution to minimizing environmental impacts arising from energy use and tackling climate change. • Carbon and energy rebound effects of energy efficiency initiatives is studied. • Decomposition analysis is used to investigate drivers of energy supply. • Energy intensity and affluence have most significant influence on energy supply. • Average estimates of carbon and energy rebound effects are partial rebound effects. [ABSTRACT FROM AUTHOR]

Low-carbon agriculture is a crucial component of sustainable development; technological innovation is the cornerstone of the agricultural transformation towards low-carbon production. This study developed a tripartite evolutionary game model for agricultural enterprise, university, and the government. It examined the low-carbon technology innovation of the agricultural innovation from an innovation consortium's perspective, considering the dilemma that China's low-carbon agriculture development faces owing to the lack of a single subject's innovation capability. The simulation's outcomes indicated: (1) The increase in collaborative innovation revenue, default costs (three–six times), and additional social benefits of collaborative innovation effectively promoted the evolutionary game results to (1,1,1), which means agricultural enterprises and universities choose collaborative innovation, and the government chooses to provide subsidies; (2) Enhancing innovation subsidies influenced game outcomes to a certain degree, but the effect was limited. The findings provide theoretical basis for government to enact policies to promote scientific and technological progress and to develop low-carbon agriculture. • This study adopts the research perspective of an innovation consortium. • A tripartite evolutionary game model is developed to examine low-carbon innovation. • Increased collaborative innovation revenue promotes ideal evolutionary results. • Enhancement of innovation subsidy can influence game outcomes to a certain degree. • Governmental policies in low-carbon agriculture must be strengthened. [ABSTRACT FROM AUTHOR]

Considering the environmental deterioration challenges and a sharp decline in the quality and quantity of natural resources, the need for capitalizing on renewable energy sources and environment-friendly practices has increased a lot. The United Nations also has urged firms to shift their reliance on fossil fuels to renewable and eco-friendly practices. Several nations have begun shifting from economic growth to green productivity practices, such as green finance, green innovation, etc., which signifies collaboration between the economy, resources, and ecological development to achieve sustainable development goals (SDGs). This study is based on a comprehensive index of green finance development. Using the nonparametric data envelopment analysis and directional distance function (DEA-DFF) model, it examines the impact of green finance, financial development and green technology innovation (GTI) on green total factor productivity (GTFP) in 28 Chinese provinces from 2011 to 2021. The findings indicate that green finance raises the degree of green productivity significantly. Other elements, such as financial development and technological innovation, contribute significantly to green production. It is also found that establishing green finance legislation can help accelerate the growth of green finance. The empirical findings in this study have policy implications for China's environmental and green finance planning. This study is among the pioneer investigations integrating green finance, financial development, and green technology innovation into a unified research framework. [Display omitted] • Green technological innovation strengthens Chinese green total factor productivity. • Financial development is a significant positive predictor of Chinese green total factor productivity. • Green finance makes a significant positive impact on Chinese green total factor productivity. • Green technological innovation, financial development, and green finance help in achieving green economy objectives. [ABSTRACT FROM AUTHOR]

This study developed a climatic-economic-technological integrated assessment model named CIECIA-TD-F. Based on model, the implementation effects of low carbon technology financing on climate mitigation, technology promotion, and economic development in the context of climate change cooperation were studied. The results indicate that carbon reduction, under the current pledged climate financing scale, is limited. Global surface warming in 2100 is still around 2.38 °C even when the technologies are globally shared. Low carbon technology financing improves technology R&D and absorptive capacities of the least developed countries. Their carbon reduction rates reach 50 percent under the capacity principle. However, donations impair the R&D inputs of developed countries and delay their advanced technological progress, leading to 1 percent more carbon emissions. This limits the imitations of China and Russia in turn by decreasing their imitation numbers by 1–2 percent. Collecting 800 billion USD per year from 2030 to 2100 is a climatically effective means. It holds global warming to 1.99 °C. However, the donors suffer more than 1 percent of economic losses. That indicates the economic feasibility of this means is weak. On this basis, we proposed a Pareto-improvement scheme which combines financing with technology sharing and national R&D improvements. This policy mix both achieves the 2 °C goal and protect the economic benefits of all countries. Thus, policy mix combining different measures will be more suitable for improving reduction effects and achieving multiple goals. Compared with sole technology financing, it has more significant global carbon governance meanings and is noteworthy in future climate negotiations. • Nine combinations of typical collection and dispensation principles were assessed. • The current scale of climate financing pledge was insufficient. • 2 °C goal can be achieved by improving financing scale dramatically in short term. • Advanced technology innovation was delayed for the economic losses of the funding donors. • A Pareto improving scheme was proposed. [ABSTRACT FROM AUTHOR]

Green total factor productivity (GTFP) under resource and environmental constraints is becoming increasingly important. This study constructed a new productivity indicator to calculate urban GTFP growth and identify whether large cities have an advantage. The Dagum Gini coefficient was combined to reveal the difference in GTFP growth among cities of different sizes, and urban GTFP growth was decomposed from the perspective of elements and technology. In addition, an econometric model was used to test the effects of city size on the GTFP growth and its decompositions. The results show an increasingly significant GTFP growth advantage in large cities, mainly due to technical progress, scale-mix efficiency growth, technical leadership effect, input utilization efficiency growth, expected output efficiency growth, and unexpected output governance efficiency growth. Notably, the econometric model shows that after controlling some external factors, the growth rate of urban GTFP still increases with the expansion of city size, which proves that large cities have an obvious productivity advantage. However, the sources of GTFP growth advantages of large cities no longer include scale-mix efficiency growth and input utilization efficiency growth. This study's conclusion has significant theoretical and practical implications for promoting the coordinated development of large, medium and small cities. C813, F061.2. [Display omitted] • This study constructs a MNEGLHM productivity indicator to measure the GTFP growth. • This is based on the input and output data of 280 Chinese cities from 2003 to 2019. • Large cities have GTFP growth advantages and move economic development. • Decomposition results show the advantages of GTFP growth and where they stem from. • An econometric model is used to comprehensively test the effects of city size on the GTFP growth. [ABSTRACT FROM AUTHOR]

Green total factor productivity (GTFP) under resource and environmental constraints is becoming increasingly important. This study constructed a new productivity indicator to calculate urban GTFP growth and identify whether large cities have an advantage. The Dagum Gini coefficient was combined to reveal the difference in GTFP growth among cities of different sizes, and urban GTFP growth was decomposed from the perspective of elements and technology. In addition, an econometric model was used to test the effects of city size on the GTFP growth and its decompositions. The results show an increasingly significant GTFP growth advantage in large cities, mainly due to technical progress, scale-mix efficiency growth, technical leadership effect, input utilization efficiency growth, expected output efficiency growth, and unexpected output governance efficiency growth. Notably, the econometric model shows that after controlling some external factors, the growth rate of urban GTFP still increases with the expansion of city size, which proves that large cities have an obvious productivity advantage. However, the sources of GTFP growth advantages of large cities no longer include scale-mix efficiency growth and input utilization efficiency growth. This study's conclusion has significant theoretical and practical implications for promoting the coordinated development of large, medium and small cities. C813, F061.2. [Display omitted] • This study constructs a MNEGLHM productivity indicator to measure the GTFP growth. • This is based on the input and output data of 280 Chinese cities from 2003 to 2019. • Large cities have GTFP growth advantages and move economic development. • Decomposition results show the advantages of GTFP growth and where they stem from. • An econometric model is used to comprehensively test the effects of city size on the GTFP growth. [ABSTRACT FROM AUTHOR]

In recent years, a significant increase in market share has occurred in the global electric vehicle industry. These advancements will eventually lead to a large-scale decommissioning of power batteries. Global governments are actively promoting echelon utilization of retired power lithium batteries, enacting a series of policies and incentives, and the industry has also constructed large-scale projects in line with national strategies to extend the life cycle of retired power batteries. While echelon utilization for retired power lithium batteries is complex, it involves scientific assessment and management of battery health in the full life cycle. This paper summarizes relevant studies and technical progress and reconstructs a health assessment system for the full life cycle of echelon utilization for retired power lithium batteries. By extending the definition of battery health status and improving the assessment index of battery health status, the paper proposes an analysis method of health status in multi-scale, multi-dimensional, and multi-physical fields. We also analyze safety accident reports of energy storage plants, summarize the main factors that affect battery health, and propose a solution for integrated multi-stage and multi-level battery health management throughout the life cycle. Electricity and thermal management are core foundations and humidity, dust, and salt spray management for various geographical and climatic conditions. These technologies can be fully integrated with bionic principles in future studies. With the support of global governments, gradual implementation of supporting policies, and continuous advances in management and core technologies of battery health in the full life cycle of echelon utilization for retired lithium batteries, related industries will develop rapidly in the next five to ten years. • Reconstructing an assessment system for the full life cycle of echelon utilization. • Extending the definition of battery health status. • Improving the assessment index of battery health status. • Proposing a method in multi-scale, multi-dimensional, and multi-physical fields. • Proposing a solution for integrated multi-stage and multi-level health management. [ABSTRACT FROM AUTHOR]

Scientific measurement of energy efficiency is the cornerstone of improving energy efficiency and realizing energy transition. Considering that the production technology of each region is restrained by factors including economic development and natural resource endowment, this paper first uses the emergy theory to measure the ecological carrying capacity of each region, and then selects other representative data to construct the "Ecology-Economy-Geography" heterogeneous framework. From the perspective of energy input minimization, the spatial and temporal features of China's ecological total factor energy efficiency (ETFEE) from 2006 to 2019 have been discussed by employing the sequential directional SBM model and Luenberger productivity index. After robustness tests, we conclude that: (a) The grouping results under multidimensional variables are different from the traditional grouping of "East-Central-West"; (b) The meta-frontier Ecological Total Factor Energy Efficiency (METFEE) and group frontier Ecological Total Factor Energy Efficiency (GETFEE) vary in spatial distribution and temporal change; (c) Technological progress is the key to improving METFEE, but part of the improvement will be offset by diminishing returns of "catch-up effect". Finally, policy recommendations to promote the ecological total factor energy efficiency in China are put forward. [Display omitted] • Construct a new heterogeneity framework of"ecological effect-economic benefit-geographical space". • Introduce a new ecological total factor energy efficiency index based on sequential directional SBM energy distance function. • acquire new findings on static and dynamic differences in energy efficiency. [ABSTRACT FROM AUTHOR]