A linear programming input–output model for mapping low-carbon scenarios for Vietnam in 2030

• Main Authors: Nguyen, Hoa Thi, Aviso, Kathleen B., Le, Dien Quang, Kojima, Naoya, Tokai, Akihiro
• Format: text
• Published: Animo Repository 2018
• Subjects: Greenhouse gas mitigation > Vietnam; Climatic changes—Government policy > Vietnam; Input-output analysis; Linear programming; Chemical Engineering
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/2730
• Institution: De La Salle University

The intended nationally determined contribution (INDC) of Vietnam to the 2015 United Nations Climate Change Conference (COP21) is a 25% reduction in greenhouse gas (GHG) emissions relative to the business-as-usual (BAU) scenario by 2030. There are various measures proposed in the INDC, but studies to assess their potential effectiveness are still needed. An input–output based linear programming model is developed in this work to evaluate the maximum GHG emission reductions which can be achieved, given various climate change mitigation strategies. Six scenarios are considered to identify the highest GHG emission reduction that can be achieved by the year 2030. These scenarios include BAU, the consideration of two different levels of differentiated sector growth, the adoption of a low-carbon electricity mix, energy efficiency enhancement for final consumption, and energy efficiency enhancement in the agriculture, transport and waste sectors. Each scenario quantifies the sector final demand, sector gross output, sector GHG emission load and the impact on human health. Results show that the best strategy is to simultaneously implement all of the identified low-carbon measures, which achieves a 24.6% reduction in overall GHG emissions in comparison to BAU levels. © 2018 Institution of Chemical Engineers