Abstract
The leading cause of global climate change and warming is greenhouse gas emissions. In developing economic activities, energy plays an important role, and human activities are responsible for climate change, carbon dioxide (CO2) emissions adverse impacts on the environment. This study investigates carbon dioxide emissions from liquid fuel consumption on CO2 emissions rather than total energy consumption. Carbon dioxide (CO2) emissions have a causal relationship of CO2 emissions from liquid fuel consumption (CO2L), industry (IND), economic growth (GDP), and trade openness (TR). The ARDL bound method incorporates the structure break and Granger causality method to measure the long-run and short-run cointegration relationship between the variables based on annual data from 1971 to 2016 Malaysia. Both the augmented Dickey-Fuller and Phillips-Perron analysis also supported exploring the study variables' stationarity. The long-run forecasts indicate that CO2L, IND, TR, and GDP are significantly related to CO2 emissions. The error correction term (ECT) value was -0.952, revealing that CO2 emissions diverged from a short-run to long-run equilibrium by 95.2% each year. Furthermore, the Granger causality test shows bidirectional causality between trade openness and CO2L. A unidirectional causality runs from the trade openness to industry at a 1% level form. The current study aims to find out the relationship between carbon dioxide emissions, economic growth, energy consumption, and trade in Malaysia to fill this scientific gap. Based on this study's results, the government needs effective policies and initiatives to identify Malaysia's ecological issues. It is also essential to determine the basic target of Malaysia's consumption of liquid fuel and its environmental mitigation policies.
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This research was funded by the National Natural Science Foundation of China with Grant Nos. 71771129.
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Aslam, B., Hu, J., Ali, S. et al. Malaysia's economic growth, consumption of oil, industry and CO2 emissions: evidence from the ARDL model. Int. J. Environ. Sci. Technol. 19, 3189–3200 (2022). https://doi.org/10.1007/s13762-021-03279-1
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DOI: https://doi.org/10.1007/s13762-021-03279-1