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Will China Achieve Its Ambitious Goal?—Forecasting the CO2 Emission Intensity of China towards 2030.
- Source :
- Energies (19961073); Jun2020, Vol. 13 Issue 11, p2924, 1p
- Publication Year :
- 2020
-
Abstract
- China has set out an ambitious target of emission abatement; that is, a 60–65% reduction in CO<subscript>2</subscript> emission intensity by 2030 compared with the 2005 baseline level and emission peak realisation. This paper aimed to forecast whether China can fulfil the reduction target of CO<subscript>2</subscript> emission intensity and peak by 2030 based on the historical time series data from 1990 to 2018. Four different forecasting techniques were used to improve the accuracy of the forecasting results: the autoregressive integrated moving average (ARIMA) model and three grey system-based models, including the traditional grey model (1,1), the discrete grey model (DGM) and the rolling DGM. The behaviours of these techniques were compared and validated in the forecasting comparisons. The forecasting performance of the four forecasting models was good considering the minimum mean absolute percentage error (MAPE), demonstrating MAPE values lower than 2%. ARIMA showed the best forecasting performance over the historical period with a MAPE value of 0.60%. The forecasting results of ARIMA indicate that China would not achieve sufficient reductions despite its projected emission peak of 96.3 hundred million tons by 2021. That is, the CO<subscript>2</subscript> emission intensity of China will be reduced by 57.65% in 2030 compared with the 2005 levels. This reduction is lower than the government goal of 60–65%. This paper presents pragmatic recommendations for effective emission intensity reduction to ensure the achievements of the claimed policy goals. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 19961073
- Volume :
- 13
- Issue :
- 11
- Database :
- Complementary Index
- Journal :
- Energies (19961073)
- Publication Type :
- Academic Journal
- Accession number :
- 144301607
- Full Text :
- https://doi.org/10.3390/en13112924