Abstract

Transport is an essential infrastructure for development. With its high share of gross domestic product (GDP), it makes a significant contribution to total CO2 emissions in Malaysia. It is therefore important to pay greater attention to reducing CO2 emissions and sustainable development in this sector. Therefore, this study aims at estimating the relationship between transport CO2 emissions and its key drivers using the Autoregressive Distributed Lag (ARDL) technique. The time period covered by the study extends from 1978 to 2018. It further investigates the response of CO2 emissions to shocks in the value of other variables by employing the generalized impulse response approach. The results suggest that urbanization is the major contributor to the increase in CO2 emissions followed by the carbon intensity of energy in the long-run. Carbon intensity of energy, GDP per transport worker and urbanization contribute significantly to increases in transport CO2 emissions in the short- and long-run. Testing the Environmental Kuznets Curve (EKC) hypothesis recommends that Malaysia continue to be on track to reach the highest level of income and welfare to give pay more attention to the environment. Therefore, the country maintains its CO2 emissions level in the future because of economic development. Therefore, these findings show that energy and environmental policymakers need to pay more attention to improving energy efficiency and the use of low-carbon technologies and electrification in the transport sector and the use of high-quality public transport, particularly in urban areas, for sustainable urban development.

Highlights

  • Transportation, as one of the fundamental infrastructures for economic development, requires energy in a significant manner

  • This study examines the impacts of energy intensity, urbanization, CO2 intensity of energy and share of renewable energy in total final energy consumption on transport CO2 emissions in Malaysia from 1978 to 2018 by employing the Autoregressive Distributed Lag (ARDL) technique

  • The exception here is for LURB which is integrated of the order zero, I (0)

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Summary

Introduction

Transportation, as one of the fundamental infrastructures for economic development, requires energy in a significant manner. It is one of most fast-growing sources of climate change and global warming worldwide (Grazi and van den Bergh, 2008; Stanley et al, 2011). In the world’s seven largest CO2 emitting economies, the transport sector uses over 90% of its energy from fossil fuels (Solaymani, 2019). In 2017, the CO2 emissions from fuel combustion in this sector were 8,040 million tonnes, the second-largest rank (24.5% of total CO2 emissions) among other economic sectors and 18% of manmade economy emissions worldwide (Huizenga and Peet, 2017; International Energy Agency-IEA, 2019). Climate change policies in transport, such as electrification and intermodal road-rail operations, without

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