Based on the scientific identification of urban built-up areas, the spatial and temporal characteristics of PM_2.5 concentrations in Chinese cities during 2000-2015, and the factors influencing them, were analyzed by exploratory spatial analysis and spatial econometric models. The results showed that the concentration of PM_2.5 in Chinese cities increased in an inverted “L” pattern during 2000-2015. However, the cities with high PM_2.5 concentrations are characterized by large-scale agglomeration, and urban agglomeration is an urban agglomeration area with a high PM_2.5 concentration. Specifically, the areas with high PM_2.5 concentrations are affected by natural factors, social and economic factors and urban form factors which all work together. From 2000 to 2005, the annual average concentration of PM_2.5 across all Chinese cities increased from 31.19 μg m^-³ to 46.00 μg m^-³, and small-scale high concentrations were densely concentrated at the intersection of Hebei, Shandong and Henan. From 2005 to 2010 and from 2010 to 2015, the annual average growth rate of the PM_2.5 concentration in urban areas slowed down, with average levels of 47.67 μg m^-³ in 2010 and 48.72 μg m^-³ in 2015, representing increases of only 3.63% and 2.20%, respectively. In 2010, the high-concentration agglomeration areas expanded to include the Beijing-Tianjin-Hebei region, the Central Yangtze River, the Yangtze River Delta, and the Chengdu Plain; while in 2015 they further expanded to the entire North China Plain, the Central Yangtze River, and the Harbin-Changchun region.

Based on the panel data of 30 provinces in China from 2000 to 2018, the mutual relationships and mechanisms of influence between industrial upgrading, total factor energy efficiency and regional carbon emission were investigated. The results show that the sophistication of industrial structure has a significant inhibitory effect on carbon emissions in all regions. The intensity of inhibition in different regions shows a sequence of “western > central > eastern”. The inhibitory effect of the rationalization of industrial structure on carbon emissions varies greatly among the different regions, with a significant restraining influence in the central and western regions, but much less influence in the eastern region. The inhibition of carbon emissions through the improvement of total factor energy efficiency is significant in all regions, and the inhibition intensity shows the sequence of “western > eastern > central”. Furthermore, the mediating effect test shows that the total factor energy efficiency in different regions has either a partial or complete mediating effect on the influence of industrial upgrading on carbon emission, so it can promote and strengthen the inhibitory effect of industrial upgrading on carbon emissions. Therefore, upgrading the industrial structure and improving the total factor energy efficiency are effective means to promote carbon emission reduction. Reducing carbon emissions by relying solely on industrial upgrading is not ideal, and it needs to be combined with improvements in the total factor energy efficiency to effectively promote carbon emission reduction.

At present, carbon intensity in the economy has become a realistic problem faced by many countries. Decarbonization and green development have gradually become one of the main trends in the world, and major countries around the world have put forward carbon neutrality targets. Russia is one of the largest greenhouse gas emitters in the world. Therefore, under the current international situation of The Russia-Ukraine war and the exogenous impact on Russia’s economy and finance, it is of great significance to study Russia’s carbon emissions for Russia’s economic development, environmental protection and global green development. In recent years, Russia’s carbon intensity has remained high, which may be caused by several factors, such as the decline in actual investment level, single industrial structure, excessive dependence on oil and gas industry, external shocks to the Russian economy in 2014 and other macroeconomic factors. The purpose of this study is to identify trends in carbon intensity during the period of exogenous shocks to the Russian economy and financial sector from 2014 to 2018, and to explain the causes. First, the synthetic control method is used to examine the changes in Russia’s carbon intensity since 2014, and the results show that since 2014, Russia’s carbon intensity has increased significantly; Secondly, using the mediation effect analysis model to test the impact mechanism, it is found that since 2014, the Russian industrial structure has not been actively improved, but instead increased its dependence on the resource industry, thereby increasing carbon emissions. Combined with the tail effect analysis, Russia has faced significant economic pressure, and its carbon intensity is unlikely to return to the state before 2014 in the short term.