April 24, 2024
Journal Article

Carbon neutrality in Malaysia and Kuala Lumpur: Insights from stakeholder-driven integrated assessment modeling

Abstract

Several cities in Malaysia have established plans to reduce their CO2 emissions, in addition to Malaysia submitting a Nationally Determined Contribution to reduce its carbon intensity (against GDP) by 45% in 2030 compared to 2005. Meeting these emissions reduction goals will require a joint effort between governments, industries, and corporations at different scales and across sectors. In collaboration with national and sub-national stakeholders, we developed and used a global integrated assessment model to explore emissions mitigation pathways in Malaysia and Kuala Lumpur. Guided by current climate action plans, we created a suite of scenarios to reflect uncertainties in policy ambition, level of adoption, and implementation for reaching carbon neutrality. Through iterative engagement with all parties, we refined the scenarios and focus of the analysis to best meet the stakeholders’ needs. We found that Malaysia can reduce its carbon intensity and reach carbon neutrality by 2050, and that action in Kuala Lumpur can play a significant role. Decarbonization of the power sector paired with extensive electrification, energy efficiency improvements in buildings, transportation, and industry, and the use of advanced technologies such as hydrogen and carbon capture and storage will be major drivers to mitigate emissions, with carbon dioxide removal strategies being key to eliminate residual emissions. This study highlights the participatory process in which stakeholders contributed to the development of the model and guided the analysis, as well as insights into Malaysia’s decarbonization potential and the role of multilevel governance.

Published: April 24, 2024

Citation

Weber M.A., L.D. Pressburger, L. Chau, Z. Khan, T.R. Waite, M.I. Westphal, and G. Ling, et al. 2024. Carbon neutrality in Malaysia and Kuala Lumpur: Insights from stakeholder-driven integrated assessment modeling. Frontiers in Energy Research 12. PNNL-SA-194494. doi:10.3389/fenrg.2024.1336045