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Coproduction of butene oligomers and adipic acid from lignocellulosic biomass: Process design and evaluation

  • Bomin Choe
  • , Shinje Lee
  • , Wangyun Won

Research output: Contribution to journalArticlepeer-review

23 Citations (Scopus)

Abstract

A new process for the coproduction of butene oligomers (BO) as biofuel and adipic acid (ADA) as a high-value chemical from lignocellulosic biomass is developed. In the proposed process, the split mass ratio of gamma-valerolactone (GVL) are controlled for efficient production of BO and ADA according to the market requirements of each product. Three distinct strategies are investigated, wherein the GVL split mass ratio is varied to produce BO and ADA in ratios of 2:1, 1:1, or 1:2, demonstrating how process economics are affected by modification of fuel and chemical production. The minimum selling prices of BO are calculated as 4.74, 3.14, and 2.90 dollars per gallon of gasoline equivalent in each case, indicating that the process in which BO and ADA are produced in a ratio of 1:2 is the most economical. Key cost drivers for the process are identified from sensitivity and uncertainty analyses. Additionally, life cycle assessment (LCA) is performed to investigate the environmental impacts of the proposed process. When the production ratio of BO and ADA is 2:1, the environmental impact is minimal, showing 0.151 kg CO2 eq and −0.075 kg oil eq, respectively, for climate change and fossil depletion.

Original languageEnglish
Article number121278
JournalEnergy
Volume235
DOIs
Publication statusPublished - 15 Nov 2021

Bibliographical note

Publisher Copyright:
© 2021 Elsevier Ltd

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy
  2. SDG 12 - Responsible Consumption and Production
    SDG 12 Responsible Consumption and Production
  3. SDG 13 - Climate Action
    SDG 13 Climate Action

Keywords

  • Carbon efficiency
  • Economics
  • Global warming
  • Monte-carlo simulation
  • Optimization
  • Sensitivity

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