Probing Energy-Related CO2 Emissions in the Beijing-Tianjin-Hebei Region Based on Ridge Regression Considering Population Factors

The main driving force for huge energy consumption is population growth and economic development, and many studies have analyzed the factors that influence carbon dioxide emissions. But the influencing factors mainly refer to the economic and social fields. Few studies have looked at population factors, and the extended STIRPAT model and ridge regression method are used to pay attention to the impact of population factors on carbon dioxide emissions in the Beijing-Tianjin-Hebei region. The conclusions drawn are as follows: 1) For Beijing, the urbanization level, population density, per capita disposable income, education level, GDP and energy intensity have a positive impact on CO2 emissions. However, age structure, family size and industrial structure play negative roles. The improvement of urbanization level has a distinctive positive influence on CO2 emissions. 2) For Tianjin, most impact factors have a positive effect on CO2 emissions, except family size and energy intensity. The decrease of family size is the first contributor to CO2 emissions growth. 3) For Hebei, the urbanization level, population density, per capita disposable income, age structure, GDP and industrial structure, have a positive influence on CO2 emissions. Education level, family size and energy intensity have a negative impact on CO2 emissions, and population density is the most important factor.