The effects of population aging, life expectancy, unemployment rate, population density, per capita GDP, urbanization on per capita carbon emissions

Human-induced carbon dioxide emissions (CO2) is the main source of global warming. This work is aimed to systematically explore the effects of human factors on CO2. To this end, this paper investigates the effects of population aging, life expectancy, population density, unemployment rate, per capita GDP, urbanization on per capita CO2 using linear panel data analysis and panel threshold regression approach for 154 countries. The results show that there is no threshold value between unemployment rate and per capita CO2, and between urbanization and per capita CO2, indicating that the effects of unemployment rate and urbanization on per capita CO(2)is linear. Urbanization contributes to the increase in per capita CO2, which is offset by the unemployment rate. In addition, there are threshold values between aging and per capita CO2, between life expectancy and per capita CO2, between population density and per capita CO2, and between per capita GDP and per capita CO2. This means the effects of aging, life expectancy, population density, per capita GDP on per capita CO2 are nonlinear. The contribution effect of per capita GDP on per capita CO2 decreases with the increase in per capita GDP. The inhibitory effects of population aging, life expectancy on per capita CO(2)increase with the increase in the degree of aging and life expectancy, respectively. Whereas the inhibitory effect of population density on per capita CO2 decreases with increase in the population density. The empirical analysis of 154 countries further confirms the complexity and heterogeneity of the impact of human factors on carbon emissions. (C) 2021 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.

Automated summary

This study systematically explored the effects of human factors on CO2 emissions in 154 countries. The results showed that some factors like urbanization have a linear impact on per capita CO2 emissions, while others like population aging have a non-linear effect. Overall, the analysis confirmed the complexity and heterogeneity of the impact of human factors on carbon emissions.