The economic uncertainty caused by COVID-19 has led governments around the world to attach more importance to green innovation to accomplish their carbon reduction schemes. To improve the green innovation encouraging effect of an environmental policy system, this study introduces a unit progressive carbon tax on the basis of a green innovation subsidy to discuss the synergy green innovation effect between them. We set up a dynamic evolutionary game model to analyze the respective influences of green innovation subsidies and an environmental policy system containing a unit progressive carbon tax on Low Carbon Technology (LCT) heterogeneous enterprises’ endogenous green innovation strategies. The Evolutionary Stable Strategy analysis of dynamic game models demonstrate that there does exist a synergy green innovation effect between green innovation subsidies and unit carbon taxes. The numerical simulation shows that the synergy green innovation effect of green innovation subsidies and carbon taxes contains both an overlapping policy effect and a more significant green innovation stimulating effect on enterprises with high LCT. Additionally, the introduction of a carbon tax will increase enterprises’ affordability on the green innovation cost coefficient. Furthermore, introducing a unit progressive carbon tax would also create additional stimulation for enterprises to pursue a larger carbon reduction amount for the carbon emission cost-saving advantage. Based on the synergy green innovation effect mentioned above, we also investigate the policy implications of varying the tax rate and subsidy proportion in different situations.
The major global economies are facing increasing pressure to reduce their carbon emissions. Introducing environmental policy instruments to stimulate green innovation is key to mitigating global warming. We propose a carbon tax design with a typical green innovation orientation that links carbon taxes with the low-carbon technology (LCT) of enterprises and imposes a progressive tax on heterogeneous enterprises with LCT stock to encourage green innovation. This study used a dynamic evolution game model based on the Stackelberg model of heterogeneous enterprises with LCT stock to analyze the green-innovation-inducing effect of unit progressive carbon taxes. A unit progressive carbon tax could encourage enterprises to participate in green innovation, regardless of their initial green innovation willingness. The progressive tax rate was more effective than a fixed rate for stimulating green innovation by all enterprises. There was a marginal diminishing effect of increases in the tax rate. An increase in the innovation cost coefficient of enterprises reduced the green-innovation-inducing effect of the unit progressive carbon tax. Increasing the tax rate was effective only under normal circumstances. A decline in the carbon reduction in enterprises also reduced the green-innovation-inducing effect of the unit progressive carbon tax. Furthermore, increasing the tax rate when the carbon reduction amount was extremely low caused enterprises to abandon green innovation.
In this paper, the CEL (Coupled Eulerian-Lagrangian) fluid-solid coupling simulation method is adopted to simulate the mechanical behavior and bubble pulsation evolution process of the transformer oil filled in the converter transformer when a high-energy discharge failure occurs in the on-load tap-changer of the converter transformer. The mechanical response of the tap changer and its solid structure is analyzed. Based on this, the compensation performance and strength of the pressure compensated expansion joint installed on the tap changer are evaluated.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.