Due to the adverse effects of fossil fuel use, it is becoming increasingly important to produce next-generation biofuels from renewable, sustainable sources. Filamentous N-2-fixing strains of cyanobacteria have emerged as promising industrial microorganisms capable of producing a range biofuels and chemicals using CO2, water, and sunlight. In this study, a life cycle analysis (LCA) was conducted on a hypothetical production facility that uses a genetically engineered strain of filamentous cyanobacteria to produce the cyclic hydrocarbon limonene. Two scenarios were evaluated in which the only difference between the scenarios was the limonene productivity of the engineered cyanobacteria strain. In Scenario 1, the cyanobacterium was assumed to produce limonene at a rate of 1.8mg/L/h, resulting in an annual production of 32,727 L/yr of limonene. In Scenario 2, limonene productivity was 55.5mg/L/h, resulting in annual production of 1,000,000 L/yr. Both scenarios were assumed to produce the same amount of cellular biomass, that was converted to biogas by anaerobic digestion and the biogas was converted by gas turbines into electricity to power the facility. Excess electricity was assumed to be sold to the grid. The major environmental burdens of the facility, which were measured in eco-points and calculated based on the Eco-indicator 99 method, were the cyanobacteria nutrient supply (especially sodium nitrate) and the photobioreactor (PBR) electrical requirements. The lower output of limonene in Scenario 1 meant that less energy was required for product recovery, leaving more electricity for sale to the grid. Even though a higher limonene productivity will worsen the environmental profile of the process, both scenarios described in this study have less of a negative environmental impact than biodiesel production. This study strongly suggests both scenarios of the theoretical limonene production facility described herein holds great potential as a future solution for producing next-generation biofuels directly from solar energy. (C) 2017 Elsevier B.V. All rights reserved.