2026/7/9
Mahmoud Karimi

Mahmoud Karimi

Academic rank: Assistant Professor
ORCID: https://orcid.org/0000-0003-2097-7858
Education: PhD.
H-Index:
Faculty: Agriculture and Environment
ScholarId:
E-mail: m-karimi [at] araku.ac.ir
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Research

Title
Life cycle assessment and techno-economic optimization of biocrude oil production from microalgae via hydrothermal liquefaction using genetic algorithms
Type
JournalPaper
Keywords
Biofuel optimization Genetic algorithms Carbon emissions Process simulation Sustainable energy
Year
2025
Journal Journal of Cleaner Production
DOI
Researchers Mahmoud Karimi ، Halis Simsek

Abstract

This study presents a comprehensive techno-economic and environmental assessment of biocrude oil production from microalgae via hydrothermal liquefaction (HTL). An integrated framework combining Aspen Plus® V14 process simulation with MATLAB®-based optimization and uncertainty analysis was employed. The baseline HTL process achieved an energy efficiency of 54 %, but the minimum biocrude selling price (MBSP) was high at $11.70 per gasoline gallon equivalent (GGE), primarily due to feedstock costs. Life cycle assessment (LCA) revealed significant environmental impacts, particularly related to feedstock production and ash disposal, with baseline carbon dioxide (CO2) equivalent emissions of 0.025 kg per megajoule (MJ) of biocrude. A genetic algorithm was utilized for multi-objective optimization, targeting both MBSP and CO2 equivalent emissions, which enabled significant process improvements. Multi-objective optimization reduced the MBSP to $11.27/GGE and CO2 emissions to 0.019 kg CO2/MJ under 30 % biomass concentration, 150 bar pump pressure, and 330 ◦C HXTemp, demonstrating synergistic improvements in cost and sustainability. Sensitivity analysis highlighted the strong influence of feedstock cost and biocrude yield on economic performance, while biocrude yield and biomass concentration were key factors affecting environmental impacts. Uncertainty analysis, using Monte Carlo simulation, demonstrated the high sensitivity of MBSP to biocrude yield variability. This integrated approach provides valuable insights for optimizing HTL processes and advancing the feasibility of sustainable microalgal biofuel production.