161 / 2017-07-10 23:18:21

The Researches on Relationship between Carbon Dioxide Emission and the Influence Factors in China

15036,15038,6290,15040

This paper investigates the relationship between carbon dioxide emissions and the influence factors in China. Eight affecting factors, namely, population (P), urban population (UP), primary industry output value (PIOV), secondary industry output value (SIOV) and tertiary industry output value (TIOV), primary industry output value proportion (PPIOV), secondary industry output value proportion (PSIOV), tertiary industry output value proportion (PTIOV), are chosen. Principal component analysis is used to extract four main components from the eight factors which can explain 99.83% of the variance of the eight affecting factors. Then Ordinary least square regression is used to analyze the relationship between the four components and carbon dioxide emissions. Finally, we get conclusion: When PIOV, SIOV, TIOV increase one hundred million yuan, the carbon dioxide emissions will increase 41.0456 kt, 9.5082 kt and 9.9444 kt respectively. And carbon dioxide emissions generated by the primary industry is more than that generated by the secondary and tertiary industries; When PPIOV, PSIOV, PTIOV increase by one percentage, carbon dioxide emissions will increase -4723.1681 kt, 474.1405 kt, 11.4513 kt respectively. Period with primary industry in a dominant position is characterized by backward technology and economic development, and the secondary industry and tertiary industry is developed with the development of economic and technological innovation. Thus the increase of PPIOV has a negative impact on carbon dioxide emissions, while PSIOV and PTIOV have the opposite impact. When the number of P and UP increase one thousand people, the carbon dioxide emissions will increase 11.4513 kt, and 19.6893 kt respectively. Thus it can be inferred that the carbon intensity of the rural population is less than 11.4513 kt per thousand people, which may resulted from the widely usage of bio-energy in poor rural.