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Conversion of Spirulina platensis into methanol via gasification: Process simulation modeling and economic evaluation

Authors :
Muhammad Shahbaz
Muhammad Ammar
Sukarni Sukarni
Source :
Digital Chemical Engineering, Vol 14, Iss , Pp 100204- (2025)
Publication Year :
2025
Publisher :
Elsevier, 2025.

Abstract

The conversion of bioresources like Spirulina platensis (SP) into value-added chemicals, such as methanol, offers a sustainable replacement of fossil fuels and contributes to greenhouse gas mitigation. This study presents an integrated process simulation model, developed using Aspen Plus v10®, for the steam gasification of SP and subsequent methanol production. Process parameters, including temperature range from 650-950 °C, steam/feed ratio from 0.5–2, and recycle ratio from 0–9, were investigated to optimize syngas composition and methanol yield. Results demonstrated that increasing temperature enhances H2 and CO production while reducing CO2 and CH4, significantly increasing methanol production from 6500 to 9500 kg/h. The steam/feed ratio also influences syngas composition and methanol yield, with higher ratios promoting H2 and CO2 production and reducing CO and CH4. The economic evaluation of two scenarios, a base case and an optimum case, shows that the capital expenditure (Capex) and operating expenditure (Opex) are 19.3M$ and 9.07M$ for the base case, and 20.018M$ and 10.21M$ for the optimum case. The analysis also reveals that the optimum case, with higher methanol production (7.2 tonnes/h compared to 6.7 tonnes/h in the base case), generates a higher net income (9.76 M$/y) and reduces CO2 emissions (4.918 tonnes CO2-e/y compared to 5.72 tonnes CO2-e/y). The energy flow indicates the input energy requirement, the energy carried by methanol, and the surplus energy, totalling 26740 kW to meet the major system's energy demands. This study provides valuable insights for researchers, policymakers, and commercial entities seeking to develop sustainable and economically viable biofuel production processes.

Details

Language :
English
ISSN :
27725081
Volume :
14
Issue :
100204-
Database :
Directory of Open Access Journals
Journal :
Digital Chemical Engineering
Publication Type :
Academic Journal
Accession number :
edsdoj.96fba1077851408b995c808c9629eabb
Document Type :
article
Full Text :
https://doi.org/10.1016/j.dche.2024.100204