Liguo Xin

Reducing carbon emissions in cities is crucial for addressing climate change, while the city-level emissions of different compositions and their relationships with socio-economic features remain largely unknown in China. Here, we explored the city-level emission pattern from the industrial, transportation, and household sectors and the emission intensity, as well as their associations with socio-economic features in China, using the up-to-date (2020) CO₂ emissions based on 0.1° grid (10 × 10 km) emission data. The results show that: (1) CO₂ emissions from the industrial sector were considerably dominant (78%), followed by indirect (10%), transportation (8%), and household (2%) emissions on the national scale; (2) combining total emissions with emission intensity, high emission–high intensity cities, which are the most noteworthy regions, were concentrated in the North, while low emission–low intensity types mainly occurred in the South-West; (3) cities with a higher GDP tend to emit more CO₂, while higher-income cities tend to emit less CO₂, especially from the household sector. Cities with a developed economy, as indicated by GDP and income, would have low emissions per GDP, representing a high emission efficiency. Reducing the proportion of the secondary sector of the economy could significantly decrease CO₂ emissions, especially for industrial cities. Therefore, the carbon reduction policy in China should focus on the industrial cities in the North with high emission–high intensity performance. Increasing the income and proportion of the tertiary industry and encouraging compact cities can effectively reduce the total emissions during the economic development and urbanization process.

Photovoltaic is emerging as a cost-competitive source of energy generation and has experienced a decade of substantial cost decline. Recognizing that innovation in sustainable technologies can substantially contribute to the sustainable generation of energy, the federal government, universities, and industries in the USA have invested considerably in innovative solar technologies involving photovoltaic energy generation. However, the association between innovations in photovoltaic energy generation, distribution, or transmission-related technologies (IPVEGRT) and carbon dioxide emissions is unclear. The present study significantly contributes to energy economics by inspecting the nexus between IPVEGRT and carbon dioxide emissions, renewable energy consumption, the expansionary monetary policy, international collaboration in green technology development, gross domestic product per capita, and trade openness in the USA from 1990Q1 to 2018Q4. The results indicate that IPVEGRT helps reduce carbon dioxide emissions. International collaboration in green technology development and renewable energy consumption was negatively associated with carbon dioxide emissions, while expansionary monetary policy, gross domestic product per capita, and trade openness were positively associated with carbon dioxide emissions. The two-way causality between IPVEGRT and carbon dioxide emissions and between international collaboration in green technology development and carbon dioxide emissions was validated. Finally, a one-way causality between expansionary monetary policy, carbon dioxide emissions, gross domestic product per capita, and carbon dioxide emissions was validated.

We conduct theoretical and empirical study on the impact of economic policy uncertainty on PM2.5 pollution. Economic policy uncertainty has important impact on PM2.5 pollution through investment channel and innovation channel. Specifically, according to real option theory, increase in economic policy uncertainty can reduce investment, thereby reducing PM2.5 pollution. However, increase in economic policy uncertainty can hinder corporate’s innovation activities, which in turn make PM2.5 pollution increase. Therefore, the impact of economic policy uncertainty on PM2.5 pollution depends on the combination effect of these two different effects. Furthermore, using 25 countries’ unbalanced panel data and fixed effects estimation methods, we empirically test the impact of economic policy uncertainty on PM2.5 pollution. The results show that, with the increase of economic policy uncertainty, countries’ PM2.5 pollution has significantly decreased. In addition, economic policy uncertainty has heterogeneous effect on countries’ PM2.5 pollution. Compared with countries who have higher R&D input, increase in economic policy uncertainty makes the reduction of PM2.5 pollution in countries with relatively lower R&D input higher. By changing the measurement methods of economic policy uncertainty and PM2.5 pollution indicators, and using 2SLS methods to estimate the models, the conclusions of the paper are robust. Finally, we put forward corresponding policy implications.