The combustion of fossil fuels drives the world’s energy production, but it also emits carbon dioxide (CO2) and other greenhouse gases. In recent years, researchers have worked to cultivate alternative, renewable energy sources, including using algae-based systems. Now, a team reports in ACS’ journalIndustrial & Engineering Chemistry Research an optimized way of producing biofuel from algae that also removes CO2 emissions from the environment.
Algae-based biorefineries only need nutrients, water, sunlight and CO2 to run. The aim of these systems is to produce cleaner energy in the form of biodiesel, methane or ethanol. However, current configurations are costly both in terms of money and energy. To address this issue, Eusiel Rubio-Castro and colleagues developed a mathematical model to determine the optimal design of an algae-based biorefinery where flue gases from different industrial facilities are used as raw materials.
The team developed a mixed integer non-linear programming (MINLP) model and applied it to a case study in Mexico. Their model determined that using flue gases as a source of CO2 reduced costs associated with the algae-growing stage of the process — the most expensive part — and reduced all other costs by almost 90 percent. Using water recycled within the biorefining process also reduced fresh water needs by about 83 percent. However, as the technology stands, the researchers say that the costs are still too high to justify an algae-based biorefinery on its own. Instead, they say that producing cleaner, algae-based fuels should be seen as a necessary expense in the global effort to reduce and capture carbon emissions.
Story source: ACS news release, 24 Feb 2016
Journal Reference: Oscar Martín Hernández-Calderón, José María Ponce-Ortega, Jesús Raúl Ortiz-del-Castillo, Maritza E. Cervantes-Gaxiola, Jorge Milán-Carrillo, Medardo Serna-González, Eusiel Rubio-Castro. Optimal Design of Distributed Algae-Based Biorefineries Using CO2Emissions from Multiple Industrial Plants. Industrial & Engineering Chemistry Research, 2016; DOI: 10.1021/acs.iecr.5b01684