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The exploration of the agricultural carbon emission reduction effect of digital rural construction offers a promising path towards achieving dual carbon goals. This study establishes an evaluation system for digital rural construction and analyzes its impact on agricultural carbon emissions using various creative techniques including panel fixed effects, mediation effects, threshold effects, and spatial Durbin models based on provincial panel data from 2011 to 2021.It is found that: (1) The impact of digital rural construction on agricultural carbon emissions exhibits a "inverted U-shaped" pattern, with a nonlinear effect on emissions through promoting agricultural green total factor productivity and adjusting agricultural structure.(2) Digital rural construction has both promoting and inhibiting effects on agricultural carbon emissions, both locally and in adjacent areas. It also demonstrates a threshold effect, with rural human capital as the sole threshold. Once the threshold value 8.830 is surpassed, the agricultural carbon emission reduction effect becomes prominent.(3)Digital rural construction has a dual effect on local agricultural carbon emissions in terms of both promoting and then restraining the emissions, which has a spatial spill-over effect in the neighboring areas. This study contributes to our understanding of carbon reduction pathways by highlighting the comprehensive utilization of digital rural construction and expanding research on the dynamic context of its impact on carbon emissions. [ABSTRACT FROM AUTHOR]

China's industrial sector generally relies on electricity as its main source of energy, and industrial production can be affected if there are problems with the electricity supply. In order to deal with the uncertain electricity supply and achieve the "dual carbon" target, the industrial sector needs to take effective measures to enhance carbon total factor productivity (CTFP). We use the biennial Luenberger productivity index (BLPI) to try to provide strategies for low-carbon industrial development in China. The results indicate that the overall CTFP of China's industrial sector showed an increasing trend from 2006 to 2019. Technology change was the main contributor to the change in CTFP, but fluctuations in efficiency change remained a challenge. Differences were observed between the light industry sector (LIS) and the heavy industry sector (HIS) in terms of changes in CTFP, with LIS showing more stable changes and HIS experiencing larger fluctuations. Most sub-sectors showed increased CTFP during the sample period. R&D investment and R&D personnel have a positive impact on CTFP, while energy structure is found to hinder CTFP. According to the research results of this study, we offer the corresponding policy implications. This study is the first to explore the balance between low-carbon goals and industrial production from the perspective of improving CTFP, providing a new viewpoint on the contributions of technological innovation to solving socio-economic issues. [ABSTRACT FROM AUTHOR]

Climate change has become an unavoidable problem in achieving sustainable development. As one of the major industries worldwide, tourism can make a significant contribution to mitigating climate change. The main objective of the paper is to assess the development level of low-carbon tourism from multi-aspect, using the Yellow River Basin as an example. Firstly, this study quantified tourism carbon dioxide emissions and tourism economy, and analyzed their evolution characteristics. The interaction and coordination degree between tourism carbon dioxide emissions and tourism economy were then analyzed using the improved coupling coordination degree model. Finally, this study analyzed the change in total factor productivity of low-carbon tourism by calculating the Malmquist–Luenberger productivity index. The results showed that: (1) the tourism industry in the Yellow River Basin has the characteristics of the initial environmental Kuznets curve. (2) There was a strong interaction between tourism carbon dioxide emissions and tourism economy, which was manifested as mutual promotion. (3) The total factor productivity of low-carbon tourism was increasing. Based on the above results, it could be concluded that the development level of low-carbon tourism in the Yellow River Basin has been continuously improved from 2000 to 2019, but it is still in the early development stage with the continuous growth of carbon dioxide emissions. [ABSTRACT FROM AUTHOR]

Environmental influence on the economy can be enhanced by consumption upgrading, transforming the key driver of economic development from supply to demand. This study constructs a model for consumption upgrading and applies threshold regression based on the susceptible–infectious–recovered (SIR) model, to explore the role of carbon emissions on high-quality economic development. The results reveal that the environmental input characterized by carbon emissions has an inverted U-shaped effect on high-quality economic development. A diminishing marginal rate of substitution of economic output demand to environment demand is observed during consumption upgrading. This study proves that environmental resources can assume both supply and demand roles for economic output and customers, which gradually emerge during consumption upgrading. [ABSTRACT FROM AUTHOR]

Improving energy efficiency is vital for addressing climate change and reducing carbon emissions in emerging economies. Financial development (FD) is crucial for economic growth, and its environmental impact and the adjustment of the industrial structure (IND) is a crucial lever in China's economic transition period. This study explored the relationship between FD, IND, and China's green total factor productivity (GTFEE) from 2000 to 2020 using the super-efficiency SBM-undesirable model, which estimates China's GTFEE. The ARDL results suggest that FD and IND enhance GTFEE in the long term, with FD promoting GTFEE by facilitating industrial structure adjustments. The Dumitrescu–Hurlin panel causality tests supported this finding. The QRPD panel quantile regression and heterogeneity analysis revealed significant heterogeneity in the effects. With increasing GTFEE, FD exerts a restraining effect, gradually weakening and transitioning into a promoting effect, while the IND consistently plays a promoting role. [ABSTRACT FROM AUTHOR]

This study investigates the relationship between environmental regulation and total factor carbon productivity in China's industrial sectors. Using panel data analysis from 2000 to 2016, we find that environmental regulations significantly enhance carbon productivity. We also examine the mediating effect of environmental regulation and analyze the dynamic effects using a threshold effect model. The results reveal a non-linear relationship, where stricter regulations may increase carbon emissions beyond a certain threshold. The study emphasizes the importance of energy allocation and technology development in shaping carbon productivity outcomes. Promoting innovation, developing a clean energy system, and implementing effective environmental regulations are crucial for improving total factor carbon productivity and achieving sustainable economic growth. [ABSTRACT FROM AUTHOR]

On the one hand, economies, particularly developing ones, need to grow. On the other hand, climate change is the most pressing issue globally, and nations should take the necessary measures. Such a complex task requires new theoretical and empirical models to capture this complexity and provide new insights. Our study uses a newly developed theoretical framework that involves renewable energy consumption (REC) and total factor productivity (TFP) alongside traditional factors of CO2 emissions. It provides policymakers with border information compared to traditional models, such as the Environmental Kuznets Curve (EKC), being limited to income and population. Advanced panel time series methods are also employed, addressing panel data issues while producing not only pooled but also country-specific results. 20 Renewable Energy Country Attractiveness Index (RECAI) nations are considered in this study. The results show that REC, TFP, and exports reduce CO2 emissions with elasticities of 0.3, 0.4, and 0.3, respectively. Oppositely, income and imports increase emissions with elasticities of 0.8 and 0.3. Additionally, we show that RECAI countries are commonly affected by global and regional factors. Moreover, we find that shocks can create permanent changes in the levels of the factors but only temporary changes in their growth rates. The main policy implication of the findings is that authorities should implement measures boosting TFP and REC. These factors are driven mainly by technological progress, innovation, and efficiency gains. Thus, they can simultaneously reduce emissions while promoting long-run green economic growth, which addresses the complexity mentioned above to some extent. • The CO2 effects of renewable energy consumption (REC) and total factor productivity (TFP) are assessed. • 20 out of the top 40 Renewable Energy Country Attractiveness Index (RECAI) countries are considered. • A newly developed theoretical framework of CO2 and advanced panel methods are used. • It is found that TFP, REC, and exports reduce CO2, whereas income and imports increase. • Main policy insight is that TFP and REC should be boosted as they reduce CO2 while promoting growth. [ABSTRACT FROM AUTHOR]

Although our knowledge of national carbon emission trading system and green certificate trading system are powerful incentive instruments that can deliver on increasingly ambitious climate targets in China, there remains an uncertainty of systems' structural reforms. This study builds on and extends a well-established dynamic computable general equilibrium (CGE) model to incorporate carbon trading system and green certificate trading system into the modeling framework, simulating a diverse of system development pathways further allows an exploration of the many possible policy effect. Then, using total factor productivity as a comprehensive indicator to asses policy effectiveness, the evolutionary trend of comprehensive effects under different paths are separately evaluated to discover the reforms' optimal range. Our work offers main results: First, these instruments provide a price signal. The introduction of a carbon allowance auction drive up carbon prices, while the implementation of a green certificate punishment and the expansion of the trading scope promote an increase in green certificate prices. Second, all policy scenarios that help reduce carbon emission intensity and optimize the power supply structure. However, in achieving the net-zero goal, the green certificate policy incurs more economic costs than the carbon trading policy. Indeed, the combination of multiple policy tools alleviates the decline of social welfare levels. Third, synergism design among policy tools: the focus should be on carbon trading policy from 2021 to 2030, green certificate trading policy from 2030 to 2050, and strengthened policy from 2050 to 2060. Reform measures within policies may need to be introduced in a timely manner. This study offers specific insights and tailored policy proposals to support policymakers in balancing environmental goals with economic and social needs in light of the aforementioned findings. Fig. 1. Introduction of the research questions Fig. 2. Framework of this paper. [Display omitted] • Carbon emission trading and green certificate trading policies were introduced into a dynamic CGE model. • The comprehensive performance of different scenarios were measured using total factor productivity index. • The policy effects of different scenarios were explored from 2020 to 2060. • The even more effective reform measures were adopt, within a single policy. • A sensible mix were proposed, within different policies. [ABSTRACT FROM AUTHOR]

Extant studies focus on the impact of environmental regulation on regional economic growth or environmental pollution, and a lot of research outcomes have been made. However, from the perspective of corporate green sustainable development, the question of whether carbon emission trading represents a "green blessing" remains unclear. To address this issue, we employ a staggered difference-in-differences model to investigate the effects and mechanisms of the carbon emissions trading pilot policy (CETPP) on the green total factor productivity (GTFP) of listed manufacturing companies in China. Our results demonstrate that: a) CETPP can effectively promote corporate GTFP, and the robustness of this result is verified through a series of checks; b) the mediating role of environmental, social, and governance (ESG) performance is critical in the relationship between CETPP and corporate GTFP, with environmental and governance performance serving as two key transmission channels; and c) CEO green experience and public environmental concern both play the moderating roles on the relationship between CETPP and GTFP; d) CETPP has a stronger positive impact on GTFP of private enterprises and enterprises in the maturity life cycle; and e) CETPP has a spatial spillover effect on GTFP, and the effect will decay as spatial distance increases. Our study offers both theoretical and practical implications for enterprises to achieve their green economic development objectives, so as to promote China's high-quality development. • We find that carbon emission trading pilot policy (CETPP) has a positive impact on the corporate green total factor productivity (GTFP). • We estimate the mediating effect of environmental, social, and governance (ESG) performance on the relationship between CETPP and corporate GTFP. • We explore the positive moderating effect of CEO green experience and public environmental concern on the relationship between CETPP and corporate GTFP. • We show that the impact of CETPP on GFTP of private enterprises and enterprises in the maturity life cycle. • We further find that there is spatial spillover effect of CETPP on GTFP, and the effect will decay with the increasing spatial distance. [ABSTRACT FROM AUTHOR]

• ·The three-stage super efficiency SBM-DEA model and Malmquist index was used to measure carbon emission efficiency, index and decomposition terms of land use. • ·LUCE and its spatial and temporal pattern of urban agglomerations in the YREB were discussed from static and dynamic perspectives respectively. • ·Environmental variables such as level of economic development, urbanization rate, and industrial structure all have significant effects on input slack value. • ·The PTE of the MRYR was relatively low due to insufficient resources in low-carbon technology, while the low TE of the CC is due to its insufficient SE. • ·TC was the main factor promoting the improvement of LUCE in the whole basin, and the trend changes of LUCE in the three urban agglomerations was closely related to their management level, technological level, and adjustment of element structure. Exploring regional differences in land use carbon emission efficiency (LUCE) and the path of collaborative emission reduction in the Yangtze River Economic Belt (YREB) are of immense importance to achieve the sustainable regional development. Firstly, based on the estimation method of land use carbon emissions, this paper scientifically calculates the carbon emission of land use of the Yangtze River Delta urban agglomeration (YRD), the middle reaches of the Yangtze River urban agglomeration (MRYR), and the Chengdu-Chongqing urban agglomeration (CC) from 2010 to 2021 in the YREB. And the carbon emission of land use of each city in urban agglomerations was obtained, which was regarded as the unexpected output in the efficiency evaluation index system. Secondly, the three-stage SBM-DEA model was used to reveal the LUCE and its spatiotemporal characteristics in different regions from a static perspective. The empirical results of the second stage SFA showed that the level of economic development, urbanization rate, industrial structure, non-agricultural conversion rate of agricultural land, the level of scientific and technological innovation and government intervention had significant effects on LUCE. By comparing the efficiency values and their decompositions in the first and third stage of various urban agglomerations, it was found that after eliminating environmental and random factors, the average ranking of comprehensive technical efficiency (TE) of land use carbon emission changed from YRD > MRYR > CC to YRD > CC > MRYR due to the cross influence of pure technical efficiency (PTE) and scale efficiency (SE). Thirdly, Malmquist index model was used to analyze the change of total factor productivity index (TFPch) and its spatiotemporal pattern from a dynamic perspective. It was found that the TFPch, technological progress index (TC), pure technical efficiency index (PEC) and scale efficiency index (SEC) of land use carbon emission of the three major urban agglomerations all showed varying degrees of increase after adjustment. Finally, to further analyze the impact of technological progress, PTE and SE on LUCE, a regression model was constructed with LUCE of each city in urban agglomeration as the dependent variable, and TC, PEC and SEC as independent variables. It was concluded that technological progress was the main factor to promote the improvement of LUCE in the whole YREB. The trend of changes of LUCE in various urban agglomerations was closely related to its management level, technology level and factor structure adjustment. The above conclusions provide support for the coordinated emission reduction path of urban agglomerations in the YREB from the perspective of land use, which is conducive to actively and steadily promoting the realization of carbon peak and carbon neutrality goals. [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]

Ensuring the coordinated development of carbon emissions and green economy has important implications for China's sustainable development. For examining the coordinated development between carbon emissions and green economy in China and its influencing factors, this study assessed the coupling coordination degree (CCD) between carbon emission intensity (CEI) and green total factor productivity (GTFP) using the coupling coordination degree model (CCDM), revealed the spatiotemporal evolution law of CCD using a spatial correlation model and empirically examined their influencing factors using the spatial Durbin model (SDM) to test influencing factors. The following findings were made: (1) The green economy in China synchronously developed with carbon emission reductions from 2000 to 2020. (2) CCD has global spatial concentration effects, and the objects are divided into three categories: cold spots, hot spots, and random distributions. (3) Government scale expansion, transportation volume increase, industrial agglomeration, and urbanization are all not conducive to CCD, but population density and industrial structure upgrading have opposite effects. To promote the coordinated development of carbon emissions and green economy, we can improve the efficiency of energy utilization and reduce carbon emissions, by using clean energy, adopting clean production technology, increasing non-productive public investment in environmental protection, industrial agglomeration in reasonable space, and improving the moderate population agglomeration. Our findings offer valuable insight for understanding the relationship between carbon emission reduction and green economic development. They will allow authorities to take specific actions to ensure the coordinated development of CEI and GTFP. [ABSTRACT FROM AUTHOR]