In recent years, there has been increasing interest in greenhouse gas mitigation technologies. As a consequence, there has been renewed interest in microalgae mass culture and fuels production from the perspective of CO2 utilization. This is not a new concept, as Oswald and Golueke (1960) had previously emphasized the potential for microalgae systems to reduce and avoid CO2 emissions and thus reduce the potential for global warming. Indeed, microalgae have a rather unique attribute: they can utilize concentrated CO2 for growth, rather than the air-levels of CO2 used by higher plants. This could allow the culture of microalgae on power plant flue gases, probably the only method for directly using such CO2 sources. Of course, once the microalgae biomass is converted to, and used as fuel, this CO2 is again released. However, an equivalent amount of fossil fuel is not burned and fossil CO2 released into the atmosphere, reducing overall CO2 emissions.

In the early 1990s, some ASP work at NREL was supported by the Pittsburgh Energy Technology Center, PETC (now FETC, Federal Energy Technology Center, see Section III. D.9.). PETC also contracted with the University of California-Berkeley to analyze microalgae systems for power plant flue gas utilization and CO2 mitigation (Benemann and Oswald 1996). This report updated and extended the earlier cost analysis reviewed above. In particular it reanalyzed the assumptions on which these studies were based, and the costs for the various system components. For example, the costs of laser grading and earthworks were independently cost estimated through contacts with agricultural engineers with expertise in constructing rice paddies in northern California. Paddle wheel costs were based on the experience of the principal investigator (WJO) with large unit designs for waste treatment ponds. Pond walls and dividers were simple earthworks, much cheaper than the Weissman and Goebel (1987) design. Among the process innovations introduced was the use of a three-phase centrifuge to separate the algal lipids from the water and other biomass fractions. This provides a relatively straightforward method for lipid recovery (a major issue in prior studies) at only marginally higher costs than the centrifuge earlier specified for final concentration. However, overall this analysis was derivative of the prior studies.

Table III. D.6. summarizes the costs projected by this analysis. Both 20 and 60 g/m2/d productivities were assumed, with a high (40%) lipid biomass, equivalent to a 10% total solar conversion efficiency. Such very high productivities would clearly require a major R&D breakthrough. The theoretical approaches to such advances were reviewed. A reduction in light harvesting (“antenna”) pigments would increase the photosynthetic efficiencies at high light intensities. Microalgae with reduced antenna pigments would, however, not be very competitive in large-scale algal pond systems, and thus would be subject to contamination. However, nutrient limitation, required in any event to maximize lipid content in the algal cells, could be used as a strategy to limit such contaminants.

Both direct flue-gas utilization near the power plant and remote use of CO2 captured from flue gas and piped to the algal ponds were considered. With projected oil prices of $25/bbl and productivities of 5% solar conversion and 30 g/m2/d assumed to be achievable in the near-term, projected cost were $77/mt to $100/mt CO2 avoided, similar to other direct flue gas mitigation options. With higher productivities (60 g/m2/d) and oil prices ($35/bbl), CO2 avoidance with microalgae costs could drop below $ 10/mt CO2, a very competitive cost compared to other direct CO2 mitigation options. The estimates for CO2 mitigation are summarized in Table III. D.7.

This report also estimated the costs of providing a significant inoculum for the culture systems, taking as the example the cultivation of B. braunii. This would involve producing small amounts of inoculum under highly controlled laboratory conditions, then amplifying the cultures using increasingly larger, but less controlled and less expensive photobioreactors. Such a process would add some 10% to 30% to overall costs, depending on the amount and control over inoculum production desired. The microalgae industry and harvesting technologies were also reviewed in some detail.

A major emphasis in this report was the potential of microalgae CO2 utilization during wastewater treatment, recapitulating the work since the 1950s by this group (Section III. B.). Indeed, with CO2 mitigation being now the primary goal, rather than fuel production, what was before a cost could now add to the waste disposal credits of such systems. Microalgae wastewater treatment uses less energy, and thus fossil fuels, than conventional treatment processes, resulting in a reduction of greenhouse gas emissions. Wastewater treatment processes could provide a near-term pathway to developing large-scale microalgae production processes and could find applications around the world. With climate change a global problem, this now allows consideration of such international perspectives, even within a DOE-funded R&D program.

The applications of microalgae to CO2 mitigation from power plants became a major focus of the ASP during the 1990s, as briefly reviewed in the following section.

I Publications:

Benemann, J. R. (1993) “Alternative recommendation regarding biological CO2 utilization R&D.” In The Capture, Utilization and Disposal of Carbon Dioxide from Fossil Fuel Power Plants (Herzog, H., et al., eds.), U. S. Dept. of Energy, DOE/ER-30194/1, 56 pp.

Benemann, J. R.; Oswald, W. J. (1966) “Systems and economic analysis of microalgae ponds for conversion of CO2 to biomass.” Final Report, Pittsburgh Energy Technology Center, Grant No. DE-FG22-93PC93204.

Herzog, H., et al. (1993) “The capture, utilization and disposal of carbon dioxide from fossil fuel power plants.” Report, U. S. Dept. of Energy, DOE/ER-30194, vol. 1 and 2.

Table III. D.6. Summary of cost analysis of microalgae CO2 mitigation.

400-ha system, @ $0.065/kWh for power sales.

(Source: Benemann and Oswald 1996.)

Productivity Assumptions 30 gftn^/day 60 g/m^/day Capital Costs, $/ha COg Flue Gas CO2 FlueG L Site prep, leeves, geotextile 6,000 6,000 2. Mixing (paddle wheels) 5,000 5,000 3. CO2 sumps, supply, distrib. 4,300 10,000 4300 13,000 4. 1° Harvesting, Flocculation 9,000 10,000 5. Centrifugation, Extraction 12500 25,000 6. Anaerobic digestion lagoon 3350 6300 7. Gen-set (power generation) 8,700 — 17,400 — 8. Water, nutrient, waste 6,200 6300 9. Buildings, roads, electrical 4500 5500 10. Eng. & Conting. (15% above) 8,900 8500 12,800 11500 11. Land Costs 2,000 2,000 12. Working Capital (25% op. cost) 3,800 2,700 4300 3,800 Total Capital Investment Operating Costs, $/ha-yr 74,150 69,650 104,400 94,000 13. Power, all except CO2 1,870 2370 14. Power, flue gas supply — 1,000 — 2,000 15. Nutrients, NJP, Fe 90S 1,800 16. CO2 (@ $4Q/mt) 7,400 — 7,400 —- 17. Flocculant 1,000 2,000 18. Labor + Overheads 3,000 4,000 19. Waste Disposal 1,000 1,000 20. Maint, Tax, Ins. (@ 5% Cap.) 3,400 3350 4,900 4,400 21. Credit for Power or fuel (3,400) (1,150) (6,800) (2300) 22. Total Net Operating Costs 15,170 10,870 16,670 15,270 23. Capital Charge (15%) 11,100 10500 15,650 14,100 24. Total Annual Costs. 26,270 21370 32320 29370 25. S/ml biomass 241 196 148 135 26. {/barrel algal oil 69 56 42 39

Table III. D.7. Greenhouse gas balances and mitigation costs.

400-ha system, @$0.065/kWh.

(Source: Benemann and Oswald 1996.)

Productivity Assumptions 30 g/m^/day £0 ghn^/day

CO2 Flue Gas CO2 Flue Gas

1. Gross Power Produced kWhr/ha-yr 52,000

2. Net Power Exported kWhr/ha-yr 26,500 10Д00

3. CO2 mitigated from #2, mt/ha-yr 23 9

4. CO; due to fertilizers, etc, mt/ha/yr

5. CO2 mitigated before oil mt/ha/yr

5. Algal oil outputs barrel/ha-yr

6. CO2 mitigated from oQ, mt/ha-yr

7. Net CXZ>2 avoided, mt/ha-yr

8. Net CX>2 avoided, mt/barrel oil

9. $/barrel algal oil (from Table 83)

10. Net cost of CO2 avoided S/mt

for $25/barrel ofl for $35/barrel ой

5 10

18 4 63 35

380	760
150	300

168	154	363	335
0.44	0.40	0.48	0.44
69	56	42	39
100	075	35	32
n	52.5	145	9