LAPSE:2023.23540
Published Article
LAPSE:2023.23540
Will China Achieve Its Ambitious Goal?—Forecasting the CO2 Emission Intensity of China towards 2030
Yan Li, Yigang Wei, Zhang Dong
March 27, 2023
Abstract
China has set out an ambitious target of emission abatement; that is, a 60−65% reduction in CO2 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 CO2 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 CO2 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.
Keywords
CO2 emission intensity, forecast, forecast evaluation, forecasting techniques
Suggested Citation
Li Y, Wei Y, Dong Z. Will China Achieve Its Ambitious Goal?—Forecasting the CO2 Emission Intensity of China towards 2030. (2023). LAPSE:2023.23540
Author Affiliations
Li Y: Business School, Shandong University at Weihai, Weihai 264209, China [ORCID]
Wei Y: School of Economics and Management, Beihang University, Beijing 100083, China; Beijing Key Laboratory of Emergency Support Simulation Technologies for City Operation, Beijing 100083, China [ORCID]
Dong Z: The School of Humanities and Social Sciences, Beihang University, Beijing 100083, China
Journal Name
Energies
Volume
13
Issue
11
Article Number
E2924
Year
2020
Publication Date
2020-06-07
ISSN
1996-1073
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PII: en13112924, Publication Type: Journal Article
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https://doi.org/10.3390/en13112924
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