 Forecasting China’s CO 2 Emissions for Energy Consumption Based on Cointegration ApproachXiangmei Li, Yan Song, Zhishuang Yao and Renbin Xiao Discrete Dynamics in Nature and Society, 2018, vol. 2018, 1-9 Abstract: Forecasting CO 2 emissions is important for climate policy decision making. The paper attempts to implement empirically the long-term forecast of CO 2 emissions based on cointegration theory under the business-as-usual scenario, by using statistical data from China over the period 1953 to 2016. We focus on the relationships between CO 2 emissions for energy consumption and influential factors: per capita GDP, urbanization level, energy intensity, and total energy consumption. The empirical results are presented as follows: continuous increase of carbon pollution resulting from energy consumption (1953-2016) indicates that China has beard great pressure of carbon reduction. Though reduction of carbon intensity in 2020 would account for 50.14% that of 2005, which meets the requirements announced by Chinese government in 2009, China would bear carbon emissions for energy consumption of 14.4853 billion tCO 2 by 2030, which is nearly 1.59 times that of 2016 and nearly 105 times that of 1953. The results suggest that the policymakers in China may take more effective measures such as reducing energy intensities and formulating stricter environmental regulations in order to mitigate the CO 2 emissions and realize the win-win of economic and ecological benefits. Date: 2018 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:hin:jnddns:4235076 DOI: 10.1155/2018/4235076 Access Statistics for this article More articles in Discrete Dynamics in Nature and Society from Hindawi |
Is your work missing from RePEc? Here is how to contribute.
Questions or problems? Check the EconPapers FAQ or send mail to .
EconPapers is hosted by the
School of Business at Örebro University.