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Coal-based cities, compared with others, are generally deemed to face double pressure from both emission reduction and economic development, indicating the great practical significance to explore high-quality development methods for China's goal of carbon neutrality. As previous studies have verified, technological innovation exerts the driving effect on total factor productivity, yet the impact mechanism between green innovational technology and carbon emission performance (TFCEP) of coal-based cities remains rather a blank area. Given this, the super-SBM model was applied to measure the TFCEP of 47 typical coal-based cities in China from 2013 to 2016. Furthermore, the econometric model was employed to analyze the impact mechanism of TFCEP. Finally, the heterogeneity effects of green technology within different regulation levels on TFCEP through mechanism analysis were revealed. The results indicate that: (1) The TFCEP of coal-based cities in the northeast, west and east regions is on the rise, while the central region shows a gradual decline trend. The relationship between TFCEP and urban development stage shows a U-shaped curve. (2) The heterogeneous effects of green innovational technology on TFCEP were revealed. The innovation compensation effect mainly occurs in coal-based cities with relatively loose environmental regulation level. the driving effect of green technologies featured by breakthrough innovations on TFCEP is greater than that of green technologies featured by conceptual design. (3) The openness has proved to be an important channel for green innovational technologies affecting TFCEP. Therefore, to advocate high-quality green development in coal-based cities, the government can choose to increase financial support for local green technology breakthroughs and reduce dependence on foreign technologies. [ABSTRACT FROM AUTHOR]

The energy saving and emissions reduction of the construction industry are crucial for China to achieve the "carbon peaking and carbon neutrality" goals. In order to promote the green development of the life cycle of the construction industry and improve the efficiency of emissions reduction. This paper examines the spatial-temporal distribution of life cycle carbon emissions in China's construction industry (LCCECI) from 2004 to 2018. It uses the SBM-Malmquist total factor productivity (TFP) index to measure technological progress and establishes the spatial econometric model based on the STIRPAT model. The study investigates the driving factors of the LCCECI at the provincial and regional levels, aiming to provide suggestions for low-carbon development in the construction industry. The research results are as follows. © The growth in the SBM-Malmquist TFP index of the construction industry distinctly curbs the LCCECI. © Total population and urbanization level are not the primary driving factors for the LCCECI. The growth of per capita GDP significantly induces the LCCECI, while concurrently exhibiting a notable inhibitory effect on the LCCECI of neighboring regions. © The improvement of the SBM-Malmquist TFP index is conducive to the reduction of the LCCECI in the three major regions. The per capita GDP has the largest positive driving effect of the LCCECI in the eastern region, and the urbanization level the urbanization rate only significantly inhibits the growth of the LCCECI in the central region. [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]

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]