Evaluation of socio-economic factors on CO 2 emissions in Iran: Factorial design and multivariable methods

Abstract

Abstract Nowadays, global CO2 emissions play a focal role in the human sustainable development and environmental concern. This paper investigates the relationships among CO2 emissions and the efficient factors including energy consumption, oil product, gross domestic product (GDP), non-oil GDP, foreign direct investment (FDI), gas consumption, citizen rate, cost of energy, number of vehicles, and mean incoming urban and rural in Iran over the period of 1976–2016. A factorial design was applied to screening the significant factors and their relations on Carbon emissions. The results indicated that energy consumption and its cost, citizen rate, non-oil GDP, and FDI have significant effects on CO2 emissions and there is a linear relationship among these factors and CO2 emissions. The relationships among significant factors were evaluated for the first time by the latent variable modeling method using partial least square (PLS) model. The latent variable model results showed that the lower energy consumption leads to lower CO2 emissions with a coefficient of 0.87. The results also indicated that citizen rate positively and FDI negatively (the share of 13% and 4%) are the other most important factors in raising CO2 emissions by a directional relationship. The share of energy cost and non-oil GDP in explaining CO2 emissions is minimal. It was found that the chance of successful determination of critical factors on CO2 emissions increases with these mathematical models.