Spatial effects of environmental regulation on high-quality economic development: From the perspective of industrial upgrading.

Studying the spatiotemporal heterogeneity of environmental regulations on high-quality regional economic development is of enormous practical value in the context of sustainable economic, social, and environmental development. Only a few studies, however, examined the regional heterogeneity of environmental regulation affecting economic development from the standpoint of upgrading the industrial structure. This research investigated the spatial distribution traits of high-quality regional development based on the construction of a comprehensive assessment index system for high-quality economic development. The economic geography-nested spatial Durbin model is then used to perform an empirical test. The findings demonstrate that (1) high-quality economic development has visible spatial heterogeneity, with strong local spatial agglomeration between regions; (2) environmental regulation and the modernization of the industrial structure are significant variables influencing high-quality economic development, but their development is not balanced; and (3) environmental policies promote high-quality regional development through a distinct channel. Formal environmental regulation promotes economic development through rationalizing industrial structure, while informal environmental regulation does so through upgrading the industrial structure. Further, both kinds of environmental regulation have positive spatial spillover effects on adjacent areas. Therefore, the regional heterogeneity of environmental regulation and industrial structure is of great significance in promoting the high-quality and sustainable development of regional economies.

Exploring the Impact and Path of Environmental Protection Tax on Different Air Pollutant Emissions.

Existing studies have examined the double dividend effect of environmental protection tax. However, less attention has been paid to the influencing factors and transmission paths of the pollution abatement effect of the environmental protection tax. Based on the panel data for 30 of China's provinces from 2007 to 2019, this study discusses the environmental protection tax's influencing factors and transmission paths on the emission scale and intensity of different air pollutants through the panel threshold regression model and mediating effect model. The results show that: (1) the environmental protection tax has a positive emission reduction effect on the emission scale or emission intensity of sulfur dioxide (SO2) and nitrogen oxides (NO2); (2) the abatement effect is stronger when per capita gross regional product is above the threshold value; (3) technological progress, economic growth, and industrial structure all have positive mediating effects. Therefore, the local environmental protection tax rate should be set with comprehensive consideration of regional economic development, industrial structure, and technological progress.

Does a Recycling Carbon Tax with Technological Progress in Clean Electricity Drive the Green Economy?

The environmental issue is a significant challenge that China faces in leading the development of the green economy. In this context, reducing CO2 emissions is the key to combatting this problem. Taking the 2017 social accounting matrix (SAM) as the database and combing macroeconomic parameters from previous studies, this article constructed the environmentally computable general equilibrium (CGE) model as an analytical model to analyze the economic-environmental-energy impacts of recycling carbon tax with technological progress in clean electricity. We found that when the rate of clean electricity technological progress reaches 10%, the carbon recycling tax that reduces corporate income taxes will achieve a triple dividend of the carbon tax, namely, promoting economic development, reducing carbon emissions, and improving social welfare. In the meantime, on the basis of carbon tax policies that raise the price of fossil energy, clean electricity technological progress will help accelerate the transformation of electricity structure, reduce the proportion of thermal power generation, and better promote emission reduction. In addition, due to the high carbon emission coefficient, coal contributes significantly to carbon emission reduction. Therefore, China should implement a carbon tax recycling policy supplemented by the progress of clean power technology as soon as possible to better promote green economy development.

How to Promote Low-Carbon Economic Development? A Comprehensive Assessment of Carbon Tax Policy in China.

Facing the increasingly severe environmental problems, the development of a green and sustainable low-carbon economy has become an international trend. In China, the core issue of low-carbon economic development is effectively resolving the contradiction between the exploitation and utilization of fossil energy and greenhouse gas emissions (mainly carbon emissions). Based on the SAM matrix, we established a static Computable General Equilibrium (CGE) model to simulate the impact of carbon tax policies on energy consumption, carbon emissions, and macroeconomics variables under 10, 20, and 30% emission reductions. Meanwhile, we analyze the impact of different carbon tax recycling mechanisms under the principle of tax neutrality. We find that the carbon tax effectively reduces carbon emissions, but it will negatively impact economic development and social welfare. A reasonable carbon tax recycling system based on the principle of tax neutrality can reduce the negative impact of carbon tax implementation. Among the four simulated scenarios of carbon tax cycle, the scenario of reducing residents' personal income tax is most conducive to realizing the "double dividend" of carbon tax.

Groundwater pollution early warning based on QTR model for regional risk management: A case study in Luoyang city, China.

Groundwater pollution early warning has been regarded as an effective tool for regional groundwater pollution prevention, especially in China. In this study, the systemic model was established to assess the groundwater pollution early warning by integrating the present situation of groundwater quality (Q), groundwater quality trend (T) and groundwater pollution risk (R). The model integrated spatial and temporal variation of groundwater quality, and combined the state and process of the groundwater pollution. Q, T and R were assessed by the methods of fuzzy comprehensive assessment, Spearman or nonparametric Mann-Kendall trend test, and overlay index, respectively. Taking the Luoyang City as an example, the groundwater pollution early warning mapping was generated, and verified by corresponding the groundwater quality classes and the early warning degrees. The results showed that the groundwater was dominated by the levels of no warning and light warning, which accounted for 77% of the study area. The serious and tremendous warning areas were affected by the worse trend and relatively bad/bad present situations of groundwater quality with the typical contaminants of total hardness, nitrate, Hg and COD. In summary, the present situation of groundwater quality was the most important factor of groundwater pollution early warning mapping in the study area. The worse trend of groundwater quality played equally a key role in the local regions, as well as the high pollution risk, which was mainly affected by the pollution source loading. Targeted measures for groundwater pollution prevention were proposed in the corresponding degrees of groundwater pollution early warning. The QTR model was proved to be effective for assessing the regional groundwater pollution early warning. The accuracy of the model could be improved if there is further data acquisition of groundwater quality in longer time series and in larger number, and further investigation of pollution sources. The QTR model is proposed and proved to be effective for assessing regional groundwater pollution early warning.