Using Simulated Flue Gas to Rapidly Grow Nutritious Microalgae with Enhanced Settleability

Abstract

Favorable microalgal nutrition from waste resources and improved harvesting methods would offset costs for a process that could be scaled up to treat pollution and produce valuable animal feed in lieu of soy protein. Co-benefits include avoidance of carbon dioxide emissions, which may provide an additional revenue stream when carbon markets begin to flourish. To sustainably achieve these goals at scale, barriers to microalgal production such as tolerance for waste streams and dramatic improvement in dewatering and settleability of the microalgae must be overcome. Presently, it is largely assumed that nutritious microalgae, including Scenedesmus obliquus, would be inhibited by SO _x and NO _x in flue gases and settle slowly as discrete particles. Studies conducted with a 2 L photobioreactor, sparged with simulated coal-fired power plant flue gas, demonstrated that both biomass productivity and settling rates were increased. The average maximum biomass productivity was 700 ± 40 mg L^-1 d^-1, which significantly exceeded that of the control culture (510 ± 40 mg L^-1 d^-1). Thirty-minute trials of modeled bulk settling showed rapid coagulation, likely facilitated by extracellular polymeric substances, and compaction when the cultures were grown with simulated emissions. Control cultures, not exposed to the additional toxicants in flue gas, settled as discrete particles and did not show any settling progress within 30 min. Of the SO₂ sparged into the cultivation system, (111 ± 4)% was captured as either SO₄ ^2- in the medium or fixed in the S. obliquus biomass. The stress of simulated-emissions exposure decreased the S. obliquus protein contents and altered the amino acid profiles but did not decrease the fraction of methionine, a valuable amino acid in animal feed.

Figure 1

Modeled biomass productivity of S. obliquus grown with 12% CO₂ and ultra-zero air (control) and simulated coal-fired power plant emissions. Vertical and horizontal error bars represent standard error (n = 3).

Figure 2

Accumulation of sulfate in the bioreactor inoculated with S. obliquus in Bold’s Basal medium as it is sparged with simulated coal-fired power plant emissions containing sulfur dioxide. Vertical and horizontal error bars represent standard error (n = 3). Control did not exceed 34 mg L^–1 SO₄^2–.

Figure 3

Nitrate removal from inoculated, sparged Bold’s Basal medium at pH 6.8. Vertical and horizontal error bars represent standard deviation (n = 3).

Figure 4

Phosphate removal from inoculated, sparged Bold’s Basal medium at pH 6.8. Vertical and horizontal error bars represent standard deviation (n = 3).

Figure 5

Percent crude protein comparison among whole soybean, S. obliquus grown in 3N-BBM and CO₂ blended with ultra-zero air, and S. obliquus grown in sulfur-free 3N-BBM and simulated coal-fired power plant flue gas. Error bars represent standard deviation (n = 3). *Indicates statistical difference from the soy control at p < 0.01, α = 0.05.

Figure 6

Percent amino acid comparison among whole soybean, S. obliquus grown in 3N-BBM and CO₂ blended with ultra-zero air, and S. obliquus grown in sulfur-free 3N-BBM and simulated coal-fired power plant flue gas. Error was 5% of the measured values.

Figure 7

Comparison of (a) S. obliquus grown with simulated flue gas, which coagulated, with (b) S. obliquus grown under control conditions, which did not coagulate.

Figure 8

Comparison of (a) S. obliquus grown with simulated flue gas, which settled rapidly in a backlit graduated cylinder, with (b) S. obliquus grown under control conditions, which settled slowly.

Figure 9

Modeled bulk settling, through coagulation and compaction, of microalgae grown with simulated power plant emissions. The model error is represented with a 95% confidence interval. Settling of control microalgae was not observed within the 30 min period.