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Carbon emission reduction potential analysis of biodiesel production from microalgae and waste cooking oil under different SSPs scenarios in China-based on GRA-CNN-BiLSTM modeling

Author

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  • Tang, Yan
  • Jiang, Yizhuo
  • Hu, Yang
  • Cheng, Yunpei

Abstract

Biodiesel production from microalgae and waste cooking oil is considered a form of energy production that can lead to resource recycling. It is important to explore whether microalgae and waste cooking oil biodiesel can play an important part in energy transformation and to effectively estimate the further potential of biodiesel production from microalgae and waste cooking oil. This study uses a deep learning model combining gray correlation analysis with a convolutional neural network-bidirectional long short-term memory network. By integrating five sustainable social pathways, the research forecasts biodiesel production from 2024 to 2035 and further analyzes the economic feasibility and carbon reduction potential of biodiesel production from microalgae and waste cooking oil. The results showed that the SSP1 scenario had the highest biodiesel yield, microalgae, and waste cooking oil performed well in economic feasibility and carbon reduction potential, and microalgae biodiesel was more advantageous. By 2035, SSP1 scenario biodiesel production will reach 4395 kilotons, and microalgae biodiesel will reduce costs by $1612 million and CO2 emissions by 13165 kilotons. From the perspective of energy production and environmental protection, biodiesel produced from microalgae and waste cooking oil will contribute to China's sustainable development in the future.

Suggested Citation

  • Tang, Yan & Jiang, Yizhuo & Hu, Yang & Cheng, Yunpei, 2026. "Carbon emission reduction potential analysis of biodiesel production from microalgae and waste cooking oil under different SSPs scenarios in China-based on GRA-CNN-BiLSTM modeling," Renewable Energy, Elsevier, vol. 258(C).
    • Handle: RePEc:eee:renene:v:258:y:2026:i:c:s0960148125026709
    DOI: 10.1016/j.renene.2025.125006
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