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Analysing CO2 emissions from Singapore's electricity generation sector: Strategies for 2020 and beyond


  • Ali, H.
  • Sanjaya, S.
  • Suryadi, B.
  • Weller, S.R.


Since 2009, Singapore has set about implementing mitigation and energy efficiency measures in key sectors to achieve unilaterally pledged reductions in greenhouse gas (GHG) emissions of 7–11% below business-as-usual (BAU) levels in 2020. Carbon dioxide (CO2) emissions from fossil fuel-fired power plants are a major focus for emissions abatement, with an expected reduction of 4 Mt CO2 from the electricity generation sector in 2020. In this paper, we explore Singapore's various strategies in the electricity generation sector to fulfil this target and use an EnergyPLAN optimization model to assess the impact of these strategies on CO2 emissions from Singapore's electricity generation sector through to 2020. A comparison of BAU scenario in 2020 (BAU 2020), 2020 target emissions reduction trajectory, and three emissions reduction alternative policy scenarios (denoted APS-I, APS-II, and APS-III) is carried out. The EnergyPLAN simulation results indicate that all three APS scenarios achieve the 2020 carbon emissions reduction target in Singapore's electricity generation sector. The results furthermore suggest that the 2020 electricity generation associated emissions reduction target can be met through measures that are already available. Vulnerabilities are identified in Singapore's electricity generation fuel mix, and emission reduction strategies beyond 2020 are outlined.

Suggested Citation

  • Ali, H. & Sanjaya, S. & Suryadi, B. & Weller, S.R., 2017. "Analysing CO2 emissions from Singapore's electricity generation sector: Strategies for 2020 and beyond," Energy, Elsevier, vol. 124(C), pages 553-564.
  • Handle: RePEc:eee:energy:v:124:y:2017:i:c:p:553-564
    DOI: 10.1016/

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    Cited by:

    1. Tharsis Teoh & Oliver Kunze & Chee-Chong Teo & Yiik Diew Wong, 2018. "Decarbonisation of Urban Freight Transport Using Electric Vehicles and Opportunity Charging," Sustainability, MDPI, Open Access Journal, vol. 10(9), pages 1-20, September.
    2. Wang, Jie & Xiong, Yiling & Tian, Xin & Liu, Shangwei & Li, Jiashuo & Tanikawa, Hiroki, 2018. "Stagnating CO2 emissions with in-depth socioeconomic transition in Beijing," Applied Energy, Elsevier, vol. 228(C), pages 1714-1725.
    3. Vanegas Cantarero, María Mercedes, 2018. "Reviewing the Nicaraguan transition to a renewable energy system: Why is “business-as-usual” no longer an option?," Energy Policy, Elsevier, vol. 120(C), pages 580-592.
    4. Lin Zhu & Lichun He & Peipei Shang & Yingchun Zhang & Xiaojun Ma, 2018. "Influencing Factors and Scenario Forecasts of Carbon Emissions of the Chinese Power Industry: Based on a Generalized Divisia Index Model and Monte Carlo Simulation," Energies, MDPI, Open Access Journal, vol. 11(9), pages 1-26, September.
    5. Wang, Yongpei & Li, Jun, 2019. "Spatial spillover effect of non-fossil fuel power generation on carbon dioxide emissions across China's provinces," Renewable Energy, Elsevier, vol. 136(C), pages 317-330.
    6. Wei Sun & Hua Cai & Yuwei Wang, 2018. "Refined Laspeyres Decomposition-Based Analysis of Relationship between Economy and Electric Carbon Productivity from the Provincial Perspective—Development Mode and Policy," Energies, MDPI, Open Access Journal, vol. 11(12), pages 1-20, December.
    7. Xue-Ting Jiang & Rongrong Li, 2017. "Decoupling and Decomposition Analysis of Carbon Emissions from Electric Output in the United States," Sustainability, MDPI, Open Access Journal, vol. 9(6), pages 1-13, May.
    8. Narayanan, Arun & Mets, Kevin & Strobbe, Matthias & Develder, Chris, 2019. "Feasibility of 100% renewable energy-based electricity production for cities with storage and flexibility," Renewable Energy, Elsevier, vol. 134(C), pages 698-709.
    9. Prasad, Ravita D. & Raturi, Atul, 2019. "Low carbon alternatives and their implications for Fiji's electricity sector," Utilities Policy, Elsevier, vol. 56(C), pages 1-19.
    10. Liao, Shiwu & Yao, Wei & Han, Xingning & Wen, Jinyu & Cheng, Shijie, 2017. "Chronological operation simulation framework for regional power system under high penetration of renewable energy using meteorological data," Applied Energy, Elsevier, vol. 203(C), pages 816-828.


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