Forecasting China’s CO2 Emissions for Energy Consumption Based on Cointegration Approach
Forecasting CO2 emissions is important for climate policy decision making. The paper attempts to implement empirically the long-term forecast of CO2 emissions based on cointegration theory under the business-as-usual scenario, by using statistical data from China over the period 1953 to 2016. We foc...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2018-01-01
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| Series: | Discrete Dynamics in Nature and Society |
| Online Access: | http://dx.doi.org/10.1155/2018/4235076 |
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| author | Xiangmei Li Yan Song Zhishuang Yao Renbin Xiao |
| author_facet | Xiangmei Li Yan Song Zhishuang Yao Renbin Xiao |
| author_sort | Xiangmei Li |
| collection | DOAJ |
| description | Forecasting CO2 emissions is important for climate policy decision making. The paper attempts to implement empirically the long-term forecast of CO2 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 CO2 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: (1) continuous increase of carbon pollution resulting from energy consumption (1953-2016) indicates that China has beard great pressure of carbon reduction. (2) 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 tCO2 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 CO2 emissions and realize the win-win of economic and ecological benefits. |
| format | Article |
| id | doaj-art-aef44a1fcb3b44b7b8fc4be120b3b245 |
| institution | OA Journals |
| issn | 1026-0226 1607-887X |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Discrete Dynamics in Nature and Society |
| spelling | doaj-art-aef44a1fcb3b44b7b8fc4be120b3b2452025-08-20T02:23:15ZengWileyDiscrete Dynamics in Nature and Society1026-02261607-887X2018-01-01201810.1155/2018/42350764235076Forecasting China’s CO2 Emissions for Energy Consumption Based on Cointegration ApproachXiangmei Li0Yan Song1Zhishuang Yao2Renbin Xiao3School of Low Carbon Economics, Hubei University of Economics, Wuhan 430205, ChinaProgram on Chinese Cities, University of North Carolina at Chapel Hill, New East Building, CB No. 3140, Chapel Hill, NC 27599-3140, USASchool of Environmental Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, ChinaSchool of Automation, Huazhong University of Science and Technology, Wuhan 430074, ChinaForecasting CO2 emissions is important for climate policy decision making. The paper attempts to implement empirically the long-term forecast of CO2 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 CO2 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: (1) continuous increase of carbon pollution resulting from energy consumption (1953-2016) indicates that China has beard great pressure of carbon reduction. (2) 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 tCO2 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 CO2 emissions and realize the win-win of economic and ecological benefits.http://dx.doi.org/10.1155/2018/4235076 |
| spellingShingle | Xiangmei Li Yan Song Zhishuang Yao Renbin Xiao Forecasting China’s CO2 Emissions for Energy Consumption Based on Cointegration Approach Discrete Dynamics in Nature and Society |
| title | Forecasting China’s CO2 Emissions for Energy Consumption Based on Cointegration Approach |
| title_full | Forecasting China’s CO2 Emissions for Energy Consumption Based on Cointegration Approach |
| title_fullStr | Forecasting China’s CO2 Emissions for Energy Consumption Based on Cointegration Approach |
| title_full_unstemmed | Forecasting China’s CO2 Emissions for Energy Consumption Based on Cointegration Approach |
| title_short | Forecasting China’s CO2 Emissions for Energy Consumption Based on Cointegration Approach |
| title_sort | forecasting china s co2 emissions for energy consumption based on cointegration approach |
| url | http://dx.doi.org/10.1155/2018/4235076 |
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