Algal biofuel production for fuels and feed in a 100-ha ...

ALGAL-00275; No of Pages 14 Algal Research xxx (2015) xxx–xxx

Contents lists available at ScienceDirect

Algal Research journal homepage: www.elsevier.com/locate/algal

Algal biofuel production for fuels and feed in a 100-ha facility: A comprehensive techno-economic analysis and life cycle assessment Colin M. Beal a,⁎, Léda N. Gerber b,c, Deborah L. Sills d, Mark E. Huntley e,f, Stephen C. Machesky g, Michael J. Walsh h, Jefferson W. Tester c,i, Ian Archibald j, Joe Granados k, Charles H. Greene b a

B&D Engineering and Consulting LLC, 7419 State Hwy 789, Lander, WY 82520, United States Cornell University, Department of Earth and Atmospheric Sciences, 4120 Snee Hall, Ithaca, NY 14853, United States Cornell University, Department of Chemical and Biomolecular Engineering, 120 Olin Hall, Ithaca, NY 14853, United States d Bucknell University, Department of Civil and Environmental Engineering, 215 Dana Engineering, Lewisburg, PA 17837, United States e Cornell University, Department of Biological and Environmental Engineering, Riley-Robb, 111 Wing Drive, Ithaca, NY 14853, United States f Duke University, Marine Laboratory, Nicholas School of the Environment, 135 Duke Marine Lab Road, Beaufort, NC 28516, United States g KCPM, Inc. dba Kokua Contracting and Project Management, 77-6441 Kuakini Hwy, Kailua-Kona, HI 96740, United States h Center for Integration of Science and Industry, Bentley University, 110 Jennison Hall, Waltham, MA 02425, United States i Cornell University, Cornell Energy Institute, 2160 Snee Hall, Ithaca, NY 14853, United States j Cinglas Ltd, Chester, United Kingdom k Institute for Integrated Renewables, 73-4617 Kaloko Halia Place, Kailua-Kona, HI 96740, United States b c

a r t i c l e

i n f o

Article history: Received 23 September 2014 Received in revised form 19 March 2015 Accepted 19 April 2015 Available online xxxx Keywords: Algae Biofuel Animal feed Life-cycle assessment Techno-economic analysis

a b s t r a c t This techno-economic analysis/life-cycle assessment is based on actual production by the Cornell Marine Algal Biofuels Consortium with biomass productivity N 23 g/m2-day. Ten distinct cases are presented for two locations, Texas and Hawaii, based on a 100-ha production facility with end-to-end processing that yields fungible co-products including biocrude, animal feed, and ethanol. Several processing technologies were evaluated: centrifugation and solvent extraction (POS Biosciences), thermochemical conversion (Valicor), hydrothermal liquefaction (PNNL), catalytic hydrothermal gasification (Genifuel), combined heat and power, wet extraction (OpenAlgae), and fermentation. The facility design was optimized by co-location with waste CO2, a terraced design for gravity flow, using renewable energy, and low cost materials. The case studies are used to determine the impact of design choices on the energy return on investment, minimum fuel and feed sale prices, discounted payback period, as well as water depletion potential, human health, ecosystem quality, non-renewable resources, and climate change environmental indicators. The most promising cases would be economically competitive at market prices around $2/L for crude oil, while also providing major environmental benefits and freshwater savings. As global demands for fuels and protein continue rising, these results are important steps towards economical and environmentally sustainable production at an industrial scale. © 2015 Published by Elsevier B.V.

1. Introduction Algae are among the most promising feedstock candidates to produce second-generation biofuels that satisfy the national mandate in the Renewable Fuels Standards that was enacted into United States' law in the Energy Independence and Security Act of 2007 [1]. Marine algae are especially promising because they do not require arable land or freshwater – thereby avoiding competition with conventional crops for these resources – and they often contain large quantities of oil, protein, carbohydrates, omega-3 fatty acids, and pigments such as astaxanthin. However, the flurry of investment into algal biofuels in the late 2000s in both public and private sectors [2–4] has not yielded economical large-scale algal biofuel production due to the following ⁎ Corresponding author. E-mail address: [email protected] (C.M. Beal).

barriers: unreliable cultivation methods, large nutrient requirements (for carbon, nitrogen, and phosphorus), low energy return on investment (EROI), high capital costs, and competition from existing commodity products with tight margins (primarily crude oil, soy meal, and corn meal) [5–9]. We address all of these barriers in this study in the following ways: Biomass productivity was measured during extended demonstrationscale experiments with consistently high yields from two selected strains (as described in a companion manuscript [10]). The facility modeled in this study is co-located with a carbon dioxide waste stream and utilizes nutrient recycling in most scenarios. Using gravity-fed volume transfers, airlift pond circulation, naturally settling algal species, and efficient conversion/extraction processes, the EROI values obtained in this model are among the highest ever reported. Low capital costs were targeted by designing large cultivation systems to achieve economies of scale, specifying cost-effective pond liners, using multi-purpose

http://dx.doi.org/10.1016/j.algal.2015.04.017 2211-9264/© 2015 Published by Elsevier B.V.

Please cite this article as: C.M. Beal, et al., Algal biofuel production for fuels and feed in a 100-ha facility: A comprehensive techno-economic analysis and life cycle assessment, Algal Res. (2015), http://dx.doi.org/10.1016/j.algal.2015.04.017

2

C.M. Beal et al. / Algal Research xxx (2015) xxx–xxx

pipelines to reduce pipe costs, and eliminating most pumps. Current market prices were used for valuing the biofuel and animal feed, however, the animal feed was shown to have several added benefits over conventional feeds during feed trials with poultry, swine, and fish, such as the high content of protein and omega-3 fatty acids — thereby potentially warranting greater financial value [11,12]. Of the many recent techno-economic analyses (TEA) and life-cycle assessments (LCA) describing the production of biofuel from algae, most evaluate a few selected production pathways based on assumed or modeled biomass and lipid yields for a specific geographical location and the TEA/LCA is conducted after the system (theoretical or experimental) has been designed [4,6,13–23]. By contrast, in this study, we used actual large-scale production results to evaluate a wide range of processing technology combinations for two geographic locations (Texas and Hawaii) and then employed TEA/LCA as a design tool, using the results of one processing scenario to inform design choices for subsequent iterations. This combination is critical to avoid recommending environmentally friendly designs that are not profitable, and vice versa. There have been a wide range of functional units used for algal biofuel TEA/LCA studies [14,24–26] and we chose 1 ha of facility area to enable comparisons with conventional crops and avoid allocation of environmental impacts among co-products [27]. The TEA/LCA analysis yields results for 20 cases in the following metrics: EROI (unitless), minimum feed and fuel sale prices (in $/MT and $/L, respectively), discounted payback period (in years) and the LCA impacts of water depletion potential (m3/ha over a 30 year span), human health, ecosystem quality, non-renewable resources, and climate change (all of which are reported in units of LCA points of environmental damage per hectare). Thus, by combining the large-scale experimental biomass productivity data with novel technology designs and thorough TEA/LCA analysis, this study offers a realistic and comprehensive evaluation of the emerging algal biofuels and animal feed industries. 2. Material and methods 2.1. The model This study evaluates a nominal 100-ha facility model that justifiably expands on the Kona Demonstration Facility (KDF), which is now Cellana LLC – as described by Huntley [10] – and does not exceed reasonable capital finance (on the order of tens-of-millions of dollars). The KDF was used from April 2010 to August 2011 for sustained production in a 0.5-ha hybrid cultivation system of photobioreactors (PBRs) and open ponds that yielded N 23 g/m2-day of biomass productivity [10]. Cultivation of two algal species (a diatom, Staurosira sp., and a chlorophyte, Desmodesmus sp.) is modeled based on actual KDF results and both species are cultivated in seawater. In the model, carbon is obtained from a local waste stream while other nutrients (nitrogen, phosphorus, and silicon, when applicable) are provided from commercial fertilizers. Co-location with a wastewater treatment plant was considered [28,29], however the nutrient demand for high-rate biomass production exceeds the low nutrient content in most wastewater primary effluents; in our analysis, the cost of pipes and pumping outweighed the nutrient savings. The facility is designed in terraces, enabling low-energy water recycling, and the cultivation system is modeled as a hybrid system of PBRs and ponds [10]. Based on the authors' experience with large-scale algae production in this integrated system, the facility is assumed to operate 347 days per year, which corresponds to a 95% capacity factor. Several processing technology configurations were evaluated in this study. The harvesting and dewatering methods considered include 1) natural settling [10] followed by centrifugation [30–32] and a ring dryer [33] (yielding 90% solids), and 2) natural settling and a belt filter press [22,32,35] (yielding 20% solids). The extraction/conversion processes in this study include combinations of hexane extraction [14,36],

Valicor's thermochemical conversion technology [37], hydrothermal liquefaction (HTL) [7,38], OpenAlgae's lipid extraction process [39], ethanol fermentation [40], catalytic hydrothermal gasification (CHG) [38], and combined heat and power (CHP) [40]. The output products include biocrude, protein-rich and omega-3-fatty-acid rich animal feed, and ethanol. Livestock feed and aquafeed trials were conducted in parallel [11,12] and demonstrate the ability to use algae as protein-rich animal feed and justify the co-product value assigned to the residual biomass after biocrude separation. 2.2. Facility design The cultivation process is described by Huntley et al. [10] and the modeled facility (Appendix A of the supplemental information (SI)) in this study contains 480 PBR's with 50 m3 of culture volume each, 16 1-day ponds, and 64 2-day ponds, both of which contain 1500 m3 of growth volume per pond. The total facility culture volume is 114,000 m3. Each PBR has 250 m2 of lit area and each pond has 10,000 m2 (1 ha) of lit area, yielding a total lit growth area for the facility of 92 ha. As shown in Appendix A of the SI, the 111 ha facility is a rectangular land plot with 11 terraces built into a natural 1% slope that enable gravity-fed volume transfers. Contrary to previous land assessments [41], this design is suitable for natural grades steeper than 1%; steeper slopes require more site preparation, but allow faster volume transfers and/or smaller pipe sizes. The upper terrace contains a parking lot, office and lab facilities, a seawater reservoir, nutrient stock tanks, and PBRs. New seawater is acquired from an offshore water intake located 5 km from the Texas site and a saline aquifer well (17 m depth) in the Hawaii location. Each of the main terraces contains one 1-day pond and four 2-day ponds on either side of the access road. Each day, 50% of all PBRs are harvested and combined to inoculate the 1-day ponds. The 1-day ponds are drained entirely each day and used to inoculate the 2-day ponds, half of which are harvested daily. As described in Appendix B of the SI, the daily volume transfers are initiated by harvesting the lowest main terrace — the algal sludge is sent to downstream processing and the supernatant is discharged. Once the lowest ponds are emptied, the second-lowest terrace is harvested — the algal sludge is sent to downstream processing and the supernatant is sent to the lowest terrace for reuse. This process is repeated as the harvesting process moves uphill. New seawater is supplied from the reservoir as needed. All cases require roughly 27,000 m3 of new seawater each day, which represents roughly 75% daily seawater recycling. Salinity increases as the seawater is reused (due to evaporation at 2.8% per day [42]) and the discharged seawater from the lowest terrace contains 39 g of salt/L, which is non-inhibitory for algal growth (authors' experience with these species). 2.3. Case descriptions Ten distinct cases were constructed and evaluated in two geographical locations, yielding a total of twenty case studies. The ten cases are summarized in Table 1, illustrated in Fig. 1, and Appendix C of the SI contains a description of the detailed operations for each process. There are two company-specific processes included in this study: 1) the Valicor thermochemical conversion process that converts wet biomass into biocrude, a carbohydrate-rich aqueous phase, and dry residual biomass [37], and 2) the OpenAlgae extraction process that utilizes a semi-permeable membrane to recover lipids from an algal slurry [29,39]. The biomass productivity and composition for both species is based directly on experimental measurements from large-scale cultivation as described by Huntley et al. [10]. The remainder of the data is modeled. Some processes were used during large scale production or experimentally tested for proof of principle, but lack published experimental data: natural settling, centrifugation, ring drying, belt filter press, POS hexane extraction, and the Valicor thermochemical



3

Table 1 The 10 cases include two algal species and various growth and processing configurations. All 10 are evaluated in Texas and Hawaii. In all cases, carbon is provided from an industrial pointsource as a 94% pure CO2 waste stream located 15 km from the facility. The nutrients in Case 1 are sodium nitrate and sodium phosphate (the same as those used at KDF), while the nutrients for Cases 2–10 are ammonia and diammonium phosphate (DAP). Productivity (in g/m2-day) is normalized to the total facility area. See Table C-1 in Appendix C of the SI for more details. Case number

Key features

Case 1 (demonstration)

Low-N, Staurosira sp., paddle-wheel pond circulation 24 h/day, hypalon pond liner ($30/m2), 19 g DW/m2-day, 0.246 g AFDW/L at harvest, 31% lipid, 18 MT biomass/day, natural settling + centrifuge + ring dryer, hexane extraction Low-N, Staurosira sp., airlift pond circulation 16 h/day, RPP pond liner ($13/m2), 19 g DW/m2-day, 0.246 g AFDW/L at harvest, 31% lipid, 18 MT biomass/day, natural settling + filter press, Valicor extraction with CHG/CHP High-N, Staurosira sp., airlift pond circulation 16 h/day, RPP pond liner ($13/m2), 33 g DW/m2-day, 0.424 g AFDW/L at harvest, 36% lipid, 30 MT biomass/day, natural settling + filter press, Valicor extraction with CHG/CHP High-N, Desmodesmus sp., airlift pond circulation 16 h/day, RPP pond liner ($13/m2), 23 g DW/m2-day, 0.433 g AFDW/L at harvest, 38% lipid, 22 MT biomass/day, natural settling + filter press, Valicor extraction with CHG/CHP Same as Case 4 except fermentation of aqueous phase rather than CHG/CHP Same as Case 4 except wind power is used Same as Case 4 except HTL used for extraction/conversion Same as Case 4 except OpenAlgae process is used for extraction/conversion High-N, Desmodesmus sp., airlift pond circulation 12 h/day, low cost ponds ($3/m2), 23 g DW/m2-day, 0.433 g AFDW/L at harvest, 38% lipid, 22 MT biomass/day, natural settling + filter press, HTL, wind power High-N, Desmodesmus sp., airlift pond circulation 12 h/day, low cost ponds ($3/m2), 23 g DW/m2-day, 0.433 g AFDW/L at harvest, 38% lipid, 22 MT biomass/day, natural settling + filter press, OpenAlgae, wind power

Case 2 (low-N) Case 3 (high-N) Case 4 (high-N green) Case Case Case Case Case

5 (fermentation) 6 (wind) 7 (HTL) 8 (OpenAlgae) 9 (target HTL)

Case 10 (target OpenAlgae)

conversion process. Although these processes were used, experimental data for all energy and mass throughputs were not directly measured for the processing of Staurosira and Desmodesmus from Cellana. Instead, these processes are modeled based on information from the companies that provided the equipment or conducted the processing. Processes that were not tested during this project, and therefore rely on literature data for modeling, include: HTL, OpenAlgae's extraction method, fermentation, CHG, and CHP. Generally speaking, Case 1 is based on experimental procedures employed during this project, Cases 2–8 are base cases representing the current state of technologies, and Cases 9 and 10 are target cases with optimistic parameters. Case 1 includes conditions and processes that were experimentally validated during low-nitrogen production of Staurosira sp. at the KDF, although some of the processes are known to be inefficient (e.g., paddlewheel circulation, centrifugation, and ring drying). Cases 2 and 3, which are identical in design except for the nitrogen fertilizer dose, model more efficient methods for cultivation and processing (i.e., airlift pond circulation, filter press dewatering, and Valicor's thermochemical conversion process) for low-nitrogen and high-nitrogen Staurosira sp. production scenarios, respectively. Case 4 is identical to Case 3 except that Desmodesmus sp. is grown, thereby eliminating the need for silicate. Desmodesmus sp. is modeled in all subsequent cases (Cases 5–10). In Cases 2–4, the carbohydrate-rich aqueous phase produced from Valicor's thermochemical conversion process is gasified via CHG and the resulting biogas is used for CHP with the produced heat and electricity being used onsite. Case 5 is identical to Case 4 except that the aqueous phase is fermented to produce ethanol rather than used for CHG/CHP. Case 6 is identical to Case 4 except that electricity is provided from wind power ($0.07/kWh in Texas and Hawaii [43,44] with significant LCA impact reductions) rather than grid electricity in those locations ($0.06/kWh in Texas and $0.31/kWh in Hawaii [45]). Cases 7 and 8 replace the Valicor conversion process with HTL [38] and the OpenAlgae wet extraction process [29,39], respectively. Cases 9 and 10, which can be considered target cases, also use the HTL and OpenAlgae conversion processes, respectively, and assume low-cost pond liners, utilize wind power, and reduce pond circulation duty cycles. The geographic locations impact the results in three ways: 1) the energy and cost of acquiring new seawater varies for Texas (an offshore intake with 5 km of pipeline) and Hawaii (a saline aquifer); 2) where location-specific costs are not known, geographic cost modifiers are used to scale the associated operating, capital, or labor cost in relation to the average cost in the United States for Texas (0.88) and

Hawaii (1.37) [46]; and 3) when available, data from the ecoinvent© version 3 LCA database were selected for the respective locations (e.g., emissions from the Texas electricity grid versus those in Hawaii) [47]. The system boundary for this analysis extends to the “facility gate,” with some combination of biocrude, animal feed, and/or ethanol co-products exiting the facility in each case. For this assessment, it is assumed that the product yields from different technologies (e.g., biocrude produced by hexane extraction, Valicor, HTL, and OpenAlgae are equivalent and the animal feed co-product is also equivalent among cases). However, composition differences might exist between these products in practice, thereby requiring different upgrading methods, and determining proper upgrading methods remains as future work. 2.4. Assessment methods 2.4.1. Energetic methods The EROI provides a direct comparison not only between the energy inputs and outputs of each case, but also among other energy production technologies. We calculate the EROI as the ratio of (total) energy outputs (Eout) to (total) energy inputs (Ein), EROI ¼

Eout E þ EEtOH þ EA F X ¼ BC Ein EE þ EH þ EMATL

MJ=d MJ=d

ð1Þ

where EBC is the energy output from biocrude (53.0 MJ/kg), EEtOH is the energy output from ethanol (41.9 MJ/kg), E AF is the energy credit from animal feed (25.1 MJ/kg), EE is the energy input from electricity (3.8 MJ/MJ for the Texas grid, 3.9 MJ/MJ for the Hawaii grid, and 1.13 MJ/MJ for wind power), E H is the energy input from heat (1.2 MJ/MJ), and ∑ EMATL is the sum of all embedded energy inputs from operating materials (see Appendix D in the SI) [47]. When onsite heat or electricity (produced from CHG + CHP) is used the associated amount is subtracted from the inputs in the denominator. If the non-renewable energy impacts are used rather than the total energy impacts, the EROI results change significantly, especially for the cases with wind power and large oil yields (see Section 3.2 Sensitivity Analysis). 2.4.2. Economic methods Two economic evaluations were conducted: 1) a discounted cash flow analysis assuming current market prices for all output products and assuming a 30-year facility lifetime, and 2) the minimum biocrude


4


sale price and the minimum animal feed sale price were determined for a 30-year payback period and the current market price for either the animal feed (when determining the minimum biocrude sale price) or the biocrude (when determining the minimum animal feed price). For Case 5, which includes ethanol as a co-product, the minimum animal feed and biocrude price calculations also assume the current market price for ethanol. A 30-year facility lifetime was selected because the pond liners are guaranteed for 20 years and the HDPE pipes have N30 year lifespans (the two greatest contributors to capital cost), and there is a large maintenance budget.

requirements and site work and is roughly 90% of the total capital cost for all cases. 2.4.2.2. Operating costs. Operating costs include the following contributions: energy, materials, land, maintenance, insurance, loan payments, taxes, and labor. The amounts of each energy and material input were determined from the integrated model of each case (including energy, mass, volume, and nutrient balances), as detailed in Appendix C of the SI. The operating energy and material costs (CE&M) determined for each case are listed in Appendix D of the SI along with their assumed market prices for Texas and Hawaii. The annual land lease (Cland) is $6.50/ac-year in Texas and $15/ac-year in Hawaii [48]. The annual maintenance cost (Cmtn) and the annual insurance costs (Cins) are both set equal to 1% of the facility depreciable capital cost. The model assumes that capital costs are split between equity (40%) and a 10-year project financing loan (60%) with an annual loan payment (Cloan) determined by an 8% interest rate. The annual tax payment (Ctax) applies depreciation of assets using a 7-year Modified Accelerated Cost Recovery System (MACRS) schedule [49] and losses

2.4.2.1. Capital costs. Capital costs were estimated using a methodology and data from RS Means with an estimated 20% uncertainty [46]. The costs are detailed in Appendix F of the SI and include the following categories: general requirements, site work (including cut-and-fill terracing), concrete, masonry, metals, wood and plastic, thermal and moisture protection, doors and windows, finishes, specialties, equipment, furnishings, special construction, conveying systems, mechanical systems, and electrical systems. The depreciable capital cost omits general

Technology Process Lineup: Case 1 Dry route to fuel and feed Seawater intake AIR

% TSS

X%

Seawater discharge Na2SiO3

NaNO3

NaH2PO4

CO2

Hexane recycle 20%

2%

1-Day Pond

PBR

2-Day Pond

Gravity settling

Centrifuge

90%

Ring Dryer

Oil Extraction

Phase separation

Solvent distillation

Biocrude

Water recycle

Animal Feed

Solids

Technology Process Lineup: Case 2-4,6 Seawater intake

Wet route to fuel and feed

Seawater discharge

X% AIR

Na2SiO3 (Case 2 &3) DAP

NH3 CO2

Biocrude

20%

2% PBR

1-Day Pond

Electricity, Heat, Nutrients

2-Day Pond

% TSS

Gravity settling

Filter Press

Valicor

Solids

Animal Feed

Water recycle CHP

CHG

Aqueous

Fig. 1. Process flow diagrams for all cases. Several cases share identical processing pathways: Cases 2, 3, 4, and 6 are based on the Valicor process; Cases 7 and 9 are based on HTL; and Cases 8 and 10 are based on the OpenAlgae process. All cases are described in Table 1 and Table C-1 of Appendix C in the SI.



5

Technology Process Lineup: Case 5 Seawater intake


Seawater discharge

% TSS

X% AIR Biocrude

NH3

DAP

CO2

20%

2% 1-Day Pond

PBR

2-Day Pond

Gravity settling

Filter Press

Valicor

Solids

Aqueous

Fermentation

Animal Feed

Water recycle Ethanol

Technology Process Lineup: Case 7,9 Seawater intake

Wet route to fuel

Seawater discharge

% TSS

X% AIR NH3

DAP

CO2

20%

2% PBR

1-Day Pond

2-Day Pond

Gravity settling

Filter Press

HTL

Biocrude

Water recycle

Electricity, Heat, Nutrients

Solids & Aqueous

CHG

CHP

Technology Process Lineup: Case 8, 10 Seawater intake


Seawater discharge

X%

% TSS

AIR Biocrude

NH3

DAP

CO2

20%

2% PBR

1-Day Pond

2-Day Pond

Gravity settling

Filter Press

OpenAlgae

Solids

Animal Feed

Water recycle Fig. 1 (continued).

were continuously carried forward. Tax liability on net income was calculated using a 20% rate. Labor costs (Clabor), detailed in Appendix E of the SI, were taken from Huntley [10] (specified for the same facility as modeled in this study) and determined by estimating the number of laborers, scientists, engineers, contractors, maintenance workers, and administrators needed to operate the production facility. There are 41 full-time equivalent employees and salaries include 30% fringe benefits.

Therefore, the annual operating cost (Caop) is expressed as C aop ¼ C E&M þ C land þ C mtn þ C ins þ C loan þ C tax þ C labor :

ð2Þ

2.4.2.3. Discounted payback period. A discounted cash flow model using an internal rate of return (i.e., discount rate) of 10% was used to assess financial feasibility. The discounted payback period represents the


6


length of time it takes for the facility to achieve a financial break-even point (i.e., a net present value (NPV) equal to zero), assuming that the fuel and feed are sold at certain market prices. The discounted payback period (DPB) is calculated by solving XDPB k¼0

DC F k ¼ 0 ½year

ð3Þ

where DCFk is the discounted cash flow associated with the facility for year k. Facility construction occurs during year 0 and full operation begins in year 1. Therefore DCFk is calculated by: for k ¼ 0 DC F 0 ¼ C eq

½$=year

ð4Þ

where Ceq is the equity portion of the total capital cost (40%) and for k≥1 DC F k ¼

Rtot −C aop

ð5Þ

ð1 þ iÞk

where Rtot is the annual revenue from product sales, Caop is the annual operating expense of the facility, and i is the discount rate (i = 10%). 2.4.2.4. Minimum selling price of fuel or feed. The minimum selling price of biocrude (Pmin,BC) or feed (Pmin,feed) represents the price at which one product has to be sold for the facility to break-even after a certain period, assuming the other products are sold at certain prices. Excel Solver was used to nonlinearly optimize Pmin for biocrude or animal feed with the price of the other co-products being fixed, assuming a 30-year facility life. To determine Pmin,BC, the price of feed was fixed at $600/MT in Texas and $930 Hawaii [50]. Conversely, to determine Pmin,feed the price of biocrude was set to $0.58/L in Texas and $0.91/L in Hawaii [51]. For Case 5, ethanol was fixed at $0.59/L in Texas and $0.93/L of ethanol in Hawaii [52]. 2.4.3. Environmental impact metrics The LCA was conducted according to ISO standards [53,54] with the objective of assessing environmental impacts associated with the ten

cases studies defined in Table 1 for Texas and Hawaii. The functional unit is 1 ha of facility area, including cultivation, processing, and general facilities. The LCA was conducted by implementing the integrated case models and their corresponding life cycle inventories in the OSMOSE software system [55], which interfaces directly with the ecoinvent© version 3 database [47]. Details of the life cycle inventories can be found in Appendix G of the SI. The Impact2002 + impact assessment method [56] was applied to yield four endpoint categories: human health, ecosystem quality, non-renewable resources, and climate change (all of which are described in Appendix G of the SI [57]). The weighting factors for the final results are specific to the USA, using the results from Lautier et al. [57]. All categories are reported in units of LCA points per hectare, which enables results from across the four categories to be compared for relative impact. One point corresponds to the yearly impacts generated per capita in the USA in each endpoint category. Water depletion potential, not available with Impact2002+, was included as a fifth indicator of environmental performance, using the Recipe impact assessment method [58], and is expressed in m3 of depleted water over a 30 year period. Details of the LCA method can be found in Appendix G of the SI. 3. Results and discussion 3.1. Results 3.1.1. Energy The energy inputs and outputs for all 20 cases are shown in Fig. 2. The energy impacts assigned to each contribution are listed in Table D-3 of the SI. Case 1 incorporates inefficient methods that yield high energy requirements and a low-nitrogen growth setting with lower productivity than the high-nitrogen cases. Case 2 improves upon Case 1 by using more efficient technologies and Case 3 applies a high-nitrogen growth setting with higher yields, further improving the EROI with respect to Case 1. Case 4 (Desmodesmus sp.) has a greater oil content than Case 3 (Staurosira sp.) and no silicon requirement, but the EROI is less than Case 3 because there is less animal feed produced, which receives a large displacement

Energy Impacts (GJ/day) (inputs are negative, outputs are positive) 900

Texas

750

Hawaii

600 450 300 150 0 -150

8.35

4.90

-300

2.13

-450

1.38 1.39

-600

1.00 1.36

-750

1.16 1.14

1.73

1.25

-1050

EROI=output/input

-1200 -1350

1.55 1.47

Water Supply Pond Circulation Nitrogen Silicon Extraction Electricity Other Animal Feed

-900

-1500

4.16

3.29

3.24

2.65

1.66

PBR Circulation Carbon Transport Phosphorus Centrifuge or Filter Press Extraction Heat Biocrude Ethanol

0.38 0.34

1T 2T 3T 4T 5T 6T 7T 8T 9T 10T

1H 2H 3H 4H 5H 6H 7H 8H 9H 10H

Fig. 2. Energy impacts for the ten cases in Texas (T) and Hawaii (H). All inputs (e.g., electricity, measured in MJ/day, and nitrogen fertilizer, measured in kg/day) are shown in Tables D-1 and D-2 and they are scaled by their associated energy impact factor (e.g., MJ/MJ or MJ/kg), which are listed in Table D-3 such that all inputs and outputs are reported in MJ/day and include upstream life-cycle impacts. The EROI for each case is shown in bold below the corresponding bar. On-site electricity and heat generation are not shown. For areal energy value calculations, the total facility is 111 ha, the cultivation area (including berms and space between PBRs) is 103 ha, and the sunlit growth area is 92 ha.



credit. Fermentation of the aqueous phase produced during the Valicor process (Case 5) results in a slight reduction in the EROI as compared to Case 4 due to energy required to distill the ethanol produced by fermentation. Implementing wind power (Cases 6, 9, and 10) provides major energy savings, reducing the energy impact for electricity from roughly 3.85 to 1.13 MJ/MJ. HTL provides the most energetically advantageous separations/conversion method (Cases 7 and 9), yielding an EROI above 8 in Case 9H, which is among the highest EROI reported to-date for an endto-end algae fuel scenario. The benefits of HTL include large biocrude yields, on-site electricity and heat production, and low embedded energy inputs due to high levels of nutrient recycling. The OpenAlgae process (Cases 8 and 10) is quite similar energetically to the Valicor process, but provides slight improvements in this assessment by reducing the heat required for extraction. All of the Hawaii cases result in greater EROI values than their Texas counterparts because the water supply energy is significantly less for drilled wells in Hawaii versus a 5 km pipeline in Texas. For Cases 2–10 in Texas, the water supply energy accounts for over 25% of the total energy input, whereas all of the cases in Hawaii require less than 25% of the total energy input for water supply.

3.1.2. Economics The capital costs for all 20 cases are shown in Fig. 3 with corresponding data listed in Appendix F of the SI. The largest contributions to the capital costs are the pond construction (specifically the Hypalon liner ($30/m2) in Case 1, RPP liner ($13/m2) in Cases 2–8, and an unspecified advanced material ($3/m2, equivalent to clay ponds in [28]) in target Cases 9 and 10, pipes (included in the Mechanical category), and processing equipment. Pipe costs are greater in Texas due to the water supply pipeline. By contrast, all other capital costs are greater in Hawaii than Texas after scaling by the geographic cost modifier in Texas (0.88) and Hawaii (1.37) [46]. The total capital costs in Texas range from $70 M (Case 1) to $46 M (Case 10), while those in Hawaii range from $95 M (Case 1) to $46 M (Case 10). The initial debt is 60% of the total capital cost.

7

The operating costs and revenues for the entire facility are shown in Fig. 4 along with the minimum selling price of animal feed (above each bar) and biocrude (below each bar). The minimum animal feed selling price ranges from $1384/MT to $5066/MT, while the minimum biocrude sale prices range from $1.93/L to $20.39/L. Although the product quality from different methods are considered equivalent (e.g., biocrude from hexane extraction, HTL, Valicor, and OpenAlgae), the products might have different compositions that would require different upgrading methods to convert the residual biomass and biocrude to refined products (e.g., diesel fuel, salmon feed and poultry feed); upgrading was not considered in this study. Generally speaking, during the loan term (10 years) for most cases, the greatest contributors to the operating cost are the loan payments (~ 50–60%), energy and materials (~ 15–20%), and labor costs (~ 15– 20%) (see Appendix F of the SI). Maintenance and insurance combine for roughly 10% of the operating cost during the loan term, while land cost and taxes are negligible. Electricity contributes over 50% of the energy and materials cost for all cases in Hawaii without wind power, and due to the difference in electricity price in Texas ($0.06/kWh [45]) and Hawaii ($0.31/kWh [45]), the total electricity cost in Texas is roughly one-third of that in Hawaii for the corresponding cases. As a result, the total energy and materials cost in Texas is only 37% to 46% of that in Hawaii for cases without wind power. At current market sale prices, the only case that generates net annual revenue within the 30-year facility lifespan is Case 10H, and thus it is the only case that incurs income tax. The cumulative discounted cash flow, which is calculated assuming current market prices for feed and fuel, is presented in Appendix F of the SI. Due to the high capital costs and low revenues associated with current feed and fuel market prices, none of the cases achieve a positive net-present-value within the assumed 30-year lifetime. In fact, none of the cases yield a break-even scenario within 40 years. This result indicates that at current market prices, none of the scenarios would be profitable, thereby preventing actual investment. Thus, in the absence of drastic cost reductions, increased sale prices (such as the minimum

Capital Costs ($M) 100 90 80

General Req. Concrete Metals Thermal and Moisture Finishes Equipment Special Construction Mechanical

Site Work Masonry Wood and Plastic Doors and Windows Specialties Furnishings Conveying Systems Electrical

70 60 50 40 30 20 10 0 1T 2T 3T 4T 5T 6T 7T 8T 9T 10T 1H 2H 3H 4H 5H 6H 7H 8H 9H 10H Fig. 3. Capital costs for all ten cases in Texas (T) and Hawaii (H) shown in millions of dollars and grouped into the 16 RS Mean categories. Capital costs for individual components (e.g., pond liner, water supply pump and HTL equipment) are listed in Table F-3. In general, pond construction (Special Construction), piping (Mechanical), and processing equipment (Equipment) are the three greatest contributors. For areal cost value calculations, the total facility is 111 ha, the cultivation area (including berms and space between PBRs) is 103 ha, and the sunlit growth area is 92 ha.


8


Operating Costs and Revenues ($/day) (costs are negative, revenues are positive) 3.0E+04

Min. Feed Price in $/MT

1949

2.5E+04 2.0E+04

2992 1487

1.5E+04 2842

1.0E+04

5066 2259

2444

2666

1620

1393

3204

3419

2116

1384

2738

2466

NA

NA

NA

NA

5.0E+03 0E+00 -5.0E+03 -1.0E+04

2.45 4.46

-1.5E+04 -2.0E+04

-3.5E+04 -4.0E+04 -4.5E+04

3.02 2.77 3.05

2.90

2.16

2.38

2.30

1.93 3.29

11.16

Water Supply Pond Circulation Nitrogen Silicon Extraction Electricity Other Maintenance Biocrude Ethanol

3.20 3.60

5.57

Texas

-2.5E+04 -3.0E+04

2.87

3.90 3.62 3.53

Min. Biocrude Price in $/L

PBR Circulation Carbon Transport Phosphorus Centrifuge or Filter Press Extraction Heat Labor Insurance Animal Feed

Hawaii 20.39

-5.0E+04 1T 2T 3T 4T 5T 6T 7T 8T 9T 10T

1H 2H 3H 4H 5H 6H 7H 8H 9H 10H

Fig. 4. Operating costs and revenues for all ten cases in Texas (T) and Hawaii (H). All inputs (e.g., electricity, measured in MJ/day, and nitrogen fertilizer, measured in kg/day) are shown in Tables D-1 and D-2 and they are scaled by their associated cost/price (e.g., $/MJ or $/kg), which are listed in Table D-3 such that all inputs and outputs are reported in $/day. The minimum sale price for biocrude is shown under each bar in $/L and the minimum sale price for animal feed is shown above each bar in $/MT. On-site electricity and heat generation are not shown. Annual loan payments and taxes vary from year-to-year and are not shown. For areal cost value calculations, the total facility is 111 ha, the cultivation area (including berms and space between PBRs) is 103 ha, and the sunlit growth area is 92 ha.

biocrude and animal feed prices identified in Fig. 4) are needed to generate sufficient revenue to justify investment. 3.1.3. Life-cycle assessment Life-cycle environmental impacts for five indicators – human health, ecosystem quality, climate change, non-renewable resources, and water depletion – are displayed in Fig. 5 for Cases 2 through 10 (impacts for Case 1 are not shown because they are an order of magnitude larger

(worse) than the other cases). The impact categories (except water depletion) are normalized to common units of pts/ha [56,57] and this study shows that co-production of biocrude and animal feed has the most significant effects on non-renewable resources, followed by climate change and ecosystem quality (which are similar in magnitude), and finally, the least effect on human health. Generally speaking, almost all of the cases demonstrate neutral or beneficial ecosystem quality, climate change, and water depletion impacts, while some

Life Cycle Environmental Impacts (positive is for an overall harmful balance, negative for a beneficial one) 150 100

1.2E+05 Human Health Ecosystem Quality Climate Change

Non-Renewable Resources

m3/ha

points/ha

50

8E+04

0 -50

Water Depletion Potential

4E+04 0 -4E+04

-100

-8E+04

-150

-1.2E+05

-200

-1.6E+05

-250

-2.0+05

2T

3T

4T

5T

6T

7T

8T

9T

10T

corresponding Hawaii (H) configuration

Fig. 5. Life cycle environmental impacts calculated with Impact2002 + (categories of human health, ecosystem quality, climate change and non-renewable resources, reported in points/ha) and Recipe (category of water depletion potential, reported in m3/ha). Only Cases 2 to 10 are presented because Case 1 yields environmental impacts well above the other cases. Data for all cases are included in Appendix H of the SI.



cases are harmful for human health and non-renewable resources and others are beneficial for these categories. The harmful impacts on human health are caused by the electricity consumption from the grid, which has a high share in fossil resources such as coal, natural gas (Texas case) or oil (Hawaii case). Their combustion is responsible for significant emissions of PAH (poly-aromatic hydrocarbons), SOx and NOx (sulfur and nitrogen oxides), causing carcinogenic and respiratory effects. Cases 6, 9, and 10 (the three cases with wind-powered electricity) result in beneficial life cycle impacts for all five environmental categories, demonstrating that replacing grid electricity with nonfossil electricity is critical for environmental sustainability. There are also general differences associated with the processing technologies. The scenarios producing only fuel via HTL (Cases 7 and 9) are most favorable for climate change and resource impacts, whereas the combined fuel-and-feed scenarios (using the Valicor or OpenAlgae process — i.e., Cases 2, 3, 4, 5, 6, 8, and 10) are more favorable for ecosystem quality and water depletion potential due to the animal feed substitution. Direct comparisons between the fuel-only route and the fueland-feed route can be made by comparing Case 7 (HTL) with Case 8 (OpenAlgae) and by comparing Case 9 (HTL, target case) with Case 10 (OpenAlgae, target case). The tradeoffs among environmental impacts emphasize the importance of considering multiple LCA indicators, and not just one type of impact, such as climate change. To illustrate the relative impact of individual model components (e.g., electricity, nitrogen fertilizer and animal feed substitution) on the overall LCA impacts, Fig. 6 shows the LCA results for four base case scenarios (Cases 4T, 6T, 7T, and 8T) with discretized impact contributions — thereby illustrating the most harmful impacts and beneficial product substitutions in the model. These four cases were selected as a subset to simplify presentation and because they encompass most of the processing pathways evaluated in this study. Detailed LCA contributions for all cases are presented in Appendix H in the SI. As shown in Fig. 6, fossil-derived electricity consumption, animal feed substitution, and biocrude substitution are the most impactful parameters to the LCA. Favorable ecosystem quality and water depletion impacts for the combined fuel-and-feed scenarios result from the beneficial substitution of algae meal for conventional animal feed (it is assumed that 75% of the algae meal replaces soybean meal and 25% of

9

the algae meal replaces corn feed). Meanwhile, the biocrude substitution has favorable impacts for the climate change and resource categories by reducing petroleum consumption and the associated emissions. Grid electricity consumption (mostly associated with cultivation), which is primarily produced from fossil fuel resources in Texas and Hawaii, contributes the vast majority of the negative effects for all five impact categories. Using renewable electricity sources, as in Cases 6, 9 and 10 that use wind power, results in configurations that are beneficial for all impact categories because wind power incurs negligible impacts (see Fig. 5). Because electricity generation is the main contributor to all negative LCA impacts (see Fig. 6), the increased electricity demand for water supply in Texas results in more harmful environmental impacts in Texas than in Hawaii for ecosystem quality, climate change, and nonrenewable resources for cases with grid electricity (see Fig. 5). However, the human health and water depletion impacts are relatively insensitive to the electricity demand and as a result, the water depletion potential is very similar in both locations because this indicator is dominated by the water-intensive animal feed credit (Fig. 6). 3.1.4. Combined results Fig. 7 presents the combined results from the TEA/LCA analysis by plotting the EROI, minimum biocrude sale price, and illustrating the aggregate LCA impact magnitudes (the sum of human health, ecosystem quality, climate change, and resource depletion impacts). As expected, the target cases (9H, 10H, 9T, and 10T) yield the most favorable results in all three metrics, with EROI values between 3.24 and 8.35, minimum biocrude prices between $1.93 and $2.39/L, and aggregate LCA impacts as low as — 500 pts/ha. The Hawaii cases without wind power are roughly $0.75/L more expensive than their Texas counterparts, however the EROI in Texas is slightly lower than that in Hawaii. The environmental benefits of the cases with wind power (Cases 6, 9, and 10) are significantly greater than the other cases. 3.2. Sensitivity analysis Before discussing the sensitivity analysis, it is useful to identify the most impactful financial contributions in this model. These parameters

Details of LCA impact contributions for Cases 4T, 6T, 7T and 8T (positive is for harmful impacts, negative for beneficial substitutions of products) 300 200

Ecosystem Quality

Climate Change

m3/ha

2.0E+04 Resources

Water Depletion Potential

0

7T

-2.0E+04

100

points/ha

Human Health

-4.0E+04 0

4T 6T 7T 8T

-6.0E+04

7T

-100

-8.0E+04

4T 6T

4T 6T

-200

7T

8T 8T

4T 6T

8T -300

4T 6T

-1.2E+05

7T

8T

-400 Biocrude

-1.0E+05

-1.4E+05 Animal feed

Land occupation

Transports

Solvent loss

Solvent

Disposal Heat

Process equipment Electricity

Plastics for ponds/PBRs

Phosphorus

Emissions CHP

Nitrogen

Fig. 6. Details of contributions to environmental impacts calculated with Impact2002+ (categories of human health, ecosystem quality, climate change and non-renewable resources, reported in points/ha) and Recipe (category of water depletion potential, reported in m3/ha over a 30-year period). Only Cases 4, 6, 7 and 8 for Texas are represented here. Results for all cases are included in Appendix H of the SI.


10


10 LEGEND

9

3T 3H

4T 4H

5T 5H

6T 6H

7T 7H

EROI

6

9T 9H

10T 10H

Total Impact (Impact2002+)

8 7

8T 8H

200 pts/ha (worst)

Target Cases 9-10

0 pts/ha -250 pts/ha

5

-500 pts/ha (best)

4 3

Hawaii Case 3-8 Texas Case 3-8

2 1 0 1.5

2

2.5

3

3.5

4

Minimum Biocrude Sale Price ($/L) Fig. 7. EROI versus minimum biocrude sale price. The size of each marker indicates the overall LCA impact in pts/ha. The target cases are the most favorable, yielding high EROI and low biocrude prices. The cases in Texas generally yield lower biocrude sale prices than those in Hawaii.

also serve as targets for future research aimed at lowering the cost of algal biofuel and feed production. The parameters listed in Table 2 are critical for cost and energy balances and are incorporated into the sensitivity analysis below along with factors that have strong impacts on the LCA results. As described by Sills et al., the most effective way to evaluate uncertainty in the TEA/LCA results is to incorporate specific uncertainty ranges for every single parameter in the study [22]. However, that approach was unmanageable for this study because there are more than 80 independent variables, 20 end-to-end cases, and three assessment efforts (energetic, economic, and environmental), all of which would need unique uncertainty functions for each variable. Furthermore, many of the parameters do not have a well-known uncertainty range. Thus, in lieu of a complete Monte Carlo uncertainty analysis, we conducted a sensitivity analysis on Cases 4–8T to evaluate the variability in the TEA/LCA results using the less favorable, baseline, and more favorable values shown in Table 3. Using the non-renewable energy impact rather than the total energy impact [47] has favorable impacts on the EROI for some cases and unfavorable impacts on other cases. For all inputs and outputs, the non-renewable energy impact is less than the total energy impact (see Table D-3 in the SI). For instance, the non-renewable energy impact for wind power is 0.05 MJ/MJ, while the total energy impact is 1.13 MJ/MJ — accounting for the kinetic wind energy. Similarly, the non-renewable energy impact for animal feed is 3.58 MJ/MJ, while the total energy impact is 25.08 MJ/MJ — accounting for the

biomass energy content. Thus, using the non-renewable impact can increase or decrease the EROI depending on whether the numerator or denominator is more strongly affected, as shown in Fig. 8. The LCA impacts use the Impact2002 + method, which can only accommodate non-renewable resource impacts (e.g., fossil-fuels and uranium), and therefore aggregate LCA impacts cannot be determined for total (renewable and non-renewable) resource impacts. These five cases (Cases 4–8T) represent base case scenarios for four separate production pathways — they are based on models for the current state of technologies and include pathways for the Valicor, HTL, and OpenAlgae processes. The results are presented in the following three metrics: EROI (unitless, Fig. 8), minimum biocrude sale price ($/L, Fig. 9), and aggregate LCA impact (pt/ha, Fig. 10), which is the sum of the four LCA impact categories with like units. All of the sensitivity analysis results are presented in Appendix I of the SI. For EROI and LCA impacts, changing the concentration of CO2 resulted in the largest changes in model results, due to increased volumetric flow rates and the associated electricity consumption. However, the percent change in CO2 concentration (~ 90% change) was bigger than the percent changes in the other parameters studied in the sensitivity analysis. We chose to see how changing CO2 concentration from 94% (typical for hydrogen or cement plants) to 10% (more typical for a coal- or gas-fired power plant), since the lower-concentration CO2 source is more available. The energetics, economics, and environmental impacts were all sensitive to changes in biomass productivity. For EROI,

Table 2 Ten most-impactful contributions to Cases 4–8T. Values given in millions of dollars of cost or revenue over a 30-year period. Negative values indicate revenue.

1 2 3 4 5 6 7 8 9 10

Case 4T

Case 5T

Case 6T

Case 7T

Case 8T

Animal feed (−63.5) Biocrude (−46.7) Labor (41.1) Insurance (19.5) Maintenance (19.5) Interest (17.5) Piping (16.1) Pond liner (12.8) Nitrogen (11.4) Water supply (9.4)

Animal feed (−63.5) Biocrude (−46.7) Labor (41.1) Insurance (16.8) Maintenance (16.8) Interest (16.4) Piping (16.1) Pond liner (12.8) Nitrogen (12.6) Water supply (9.4)

Animal feed (−63.5) Biocrude (−46.7) Labor (41.1) Interest (17.5) Insurance (17.4) Maintenance (17.4) Piping (16.1) Pond liner (12.8) Nitrogen (11.4) Water supply (10.4)

Biocrude (−70.4) Labor (41.1) Interest (18.8) Insurance (16.3) Maintenance (16.3) Piping (16.1) Pond liner (12.8) Water supply (9.3) Pond circulation (6.8) CHG equipment (4.1)

Animal feed (−91.3) Biocrude (−39.0) Labor (41.1) Interest (16.3) Piping (16.1) Insurance (15.1) Maintenance (15.1) Pond liner (12.8) Nitrogen (12.6) Water supply (9.4)



Sensitivity parameters

Less favorable

Baseline

More favorable

Biomass productivity (g/m2-day) Lipid content (−) Airlift efficiency (−) Biocrude recovery efficiency (−) Valicor:HTL:OpenAlgae CO2 concentration (−) Cost of CO2 ($/MT) Stoichiometric N:P (% AFDW) Labor cost ($M/year) Non-renewable vs. total energy Discount rate (%), tax rate (%) Interest rate (%), loan term (year) Animal feed price ($/MT) Capital cost Operating days (days/year)

18

24

30

0.28 0.15 0.7:0.35:0.5

0.38 0.47 0.25 0.35 0.9:0.5:0.75 0.95:0.65:0.9

0.1 $40/MT 8.1:0.7 1.7 Non-renewable⁎

0.94 0 6.5:0.6 1.4 Total

NA NA 4.9:0.4 1.0 Non-renewable⁎

15%, 35% 12%, 5

10%, 15% 8%, 10

5%, 0% 4%, 15

300 125% of baseline 329

600 Baseline 347

1500 75% of baseline 360

5 Minumum Biocrude Price ($/L)

Table 3 Sensitivity analysis parameters: values for less favorable, baseline, and more favorable scenarios. ⁎Using the non-renewable energy impact rather than the total impact has favorable impacts on some cases and unfavorable impacts on others.

11

4.5 4 3.5 3 2.5 2 1.5 1 0.5

Biomass Oil Rec N&P Feed Price Operating Days

Lipid CO2 Conc Labor Interest & Loan

Airlift CO2 Cost Disc & Tax Capital Cost

0 4T - 4T + 5T - 5T + 6T - 6T + 7T - 7T + 8T - 8T + Fig. 9. Sensitivity analysis for minimum biocrude sale price for Cases 4–8T. Parameters are listed in Table 3 and changes that incurred less favorable results (compared to the base cases) are indicated with a (−) sign for each case and parameters that incurred more favorable results (compared to the base cases) are indicated with (+) signs for each case. Parameters that do not impact the minimum biocrude sale price are not shown.

the type of energy analysis (Non-Renewable vs. Total, see Eq. (1)) was also a sensitive parameter, demonstrating the importance of specifying which analysis is being conducted when comparing EROI values across studies. For the minimum biocrude sale price, changes in the interest rate and loan term, discount and tax rates, biomass and lipid productivities, and the price of animal feed impacted model results the most. Some of the most important parameters in this model could not be evaluated in a sensitivity analysis because changes in those parameters would require an entire system re-design. These include: slope of the land, supernatant and sludge pumping rather than gravity flow, algal species, pond and PBR dimensions (length, depth, etc.), settling characteristics, and variations in the ratio of PBRs:1-day ponds:2-day ponds. Changes to these parameters can have significant impacts on the productivity, costs, and energy balance.

beneficial aggregate environmental LCA impact (6T, 9T, 10T, 6H, 7H, 9H, and 10H). Although these cases rely on renewable electricity sources, even the cases with grid electricity show promise, such as Cases 7 and 8 in Texas and Hawaii, which yield EROI values between 1.25 and 2.13 and minimum biocrude sale prices between $2.45/L and $3.60/L. The environmental impacts of these cases are roughly neutral. Although the baseline cases in this study yield minimum biocrude sale prices around $2.64/L ($10/gal), if the co-product revenue is increased (as shown in the sensitivity analysis), the minimum sale prices can be as low as $0.86/L ($3.26/gal, Case 8T+ in Fig. 9), which is economically competitive in current markets. There are several potential co-products that could yield $1500/MT, such as omega-3 fatty acid human nutrition supplements [59–61] and aquafeeds [62,63]. Results from this study for minimum biocrude sale price are compared with others from the literature in Fig. 11.

3.3. Discussion

3.3.2. Resource constraints While this study provides many promising and progressive results for algal biofuel production, it also reveals significant limitations. Algal

3.3.1. Overview This study yields several encouraging results. There are six cases with an EROI N 1.5, a minimum biocrude sale price b $3.50/L, and a Lipid CO2 Conc

Airlift N&P

2.7 2.4

EROI

2.1 1.8 1.5 1.2 0.9 0.6 0.3 0 4T - 4T + 5T - 5T + 6T - 6T + 7T - 7T + 8T - 8T + Fig. 8. Sensitivity analysis for EROI for Cases 4–8T. Parameters are listed in Table 3 and changes that incurred less favorable results (compared to the base cases) are indicated with a (−) sign for each case and parameters that incurred more favorable results (compared to the base cases) are indicated with (+) signs for each case. Parameters that do not impact the EROI are not shown.

Lipid Operating Days

Airlift

Oil Rec

CO2 Conc

600 Aggregate LCA Imapct (pts/ha)

3

Biomass Oil Rec Non-Ren vs Tot

Biomass N&P

480 360 240 120 0 -120 -240 -360 -480 -600 4T - 4T + 5T - 5T + 6T - 6T + 7T - 7T + 8T - 8T +

Fig. 10. Sensitivity analysis for aggregate LCA impact for Cases 4–8T. Parameters are listed in Table 3 and changes that incurred less favorable results (compared to the base cases) are indicated with a (−) sign for each case and parameters that incurred more favorable results (compared to the base cases) are indicated with (+) signs for each case. Parameters that do not impact the LCA impacts are not shown. The Impact2002+ method only accommodates non-renewable resource impacts, and thus the aggregate LCA impact for total resources cannot be determined.


12


Comparison of biocrude and biofuel production costs with previous studies Benemann et al. (1982) Weissmann & Goebel (1987) Benemann & Oswald (1996) Lundquist et al. (2010) Williams & Laurens (2010) Amer et al. (2011) Sun et al. (2011) Davis et al. (2011) Delrue et al. (2012) Richardson et al. (2012) Davis et al. (2014) This Study (Texas) This Study (Hawaii)

production costs 0 ($ 2013/L)

2

4

6

8

10

drop-in fuel

12

14

16

18

20

intermediate product

Fig. 11. Minimum biocrude sale price: comparison of results from this study (in purple) and those in the literature (in blue for intermediate products and in green for drop-in fuels). The red line shows the average price of diesel for comparison [7,18,23,28,64–70].

biofuel and animal feed production are limited by the accessibility of waste carbon as well as nitrogen and phosphorus fertilizer. The proximity and quality of the carbon source is one of the most important parameters for algal biofuel production and there have been numerous studies devoted to evaluating carbon availability and the feasibility of different sources [71–75]. This model assumes that a waste source of nearly pure CO2 (94%) is available at no cost. While such concentrated CO2 sources exist (e.g., hydrogen plants and cement plants), they are comparatively rare. Widespread algae production would require additional sources – such as flue gas – and the collection, purification, and distribution of that carbon would incur additional energetic and financial costs, as shown in the sensitivity analysis. The silicon requirement for diatom production creates several disadvantages: additional energetic and financial costs, difficult nutrient preparation methods, and high ash content in the residual animal feed. As shown in Table 4, in order to satisfy the Renewable Fuel Standards mandate with 18.9 billion L of annual biocrude production from algae (roughly 3% of the U.S. petroleum demand), the U.S. would require from as little as a 1% increase in both national nitrogen and phosphorus consumption, to as much as a 33% and 21% increase in national nitrogen and phosphorus consumption, respectively. These results demonstrate the importance of nutrient recycling, which is greatly facilitated using HTL (Cases 7 and 9, achieving roughly 92% nutrient recycling) and to a much lesser degree by using

CHG/CHP with the aqueous phase remaining after the Valicor process (Cases 2–6, achieving 9% nutrient recycling). It is important to note that although there are large nutrient requirements for the Valicor and OpenAlgae cases, both routes produce significant amounts of animal feed (in contrast to HTL), thereby eliminating large flows of nutrient requirements for conventional feed production, which on a global scale is less than 50% efficient in the use of nitrogen fertilizer [76], causing widespread eutrophication [77]. 3.3.3. Large-scale impacts Case 4 was designed to represent a facility and operations as if it were to be “built today.” It represents the Base Case in [10] and lies between the more-proven, but inefficient Cases 1–3 and the optimistic, but less-proven Cases 5–10. Large-scale production is more likely to occur in the southern continental U.S. [75], thus we can use Case 4T to evaluate the large-scale impacts of these results. We recognize that resource consumption, including land and water use, can vary substantially on a site-specific basis, which leads to inherent constraints on the coverage of this analysis, but these values are provided to give readers a sense of scale for algal fuel and feed production from this integrated system. The EROI for Case 4T is 1.16, which indicates a positive energy balance and a return on investment similar to U.S. oil shale deposits [80]

Table 4 Carbon, silicon, nitrogen, and phosphorus requirements for 18.9 billion L of annual biocrude production (5 billion gal) for the 10 cases. The data in parentheses indicate the percentage of the total U.S. nitrogen and phosphorus consumption (2011) required for these nutrient demands [78] or the percentage of the U.S. soybean meal animal feed market (roughly 27 million MT per year [76,79]) that would be displaced. Unless noted, data are in thousand MT per year. Case

1

2

3

4

5

6

7

8

9

10

Carbon demand Silicon demand Nitrogen demand Phosphorus demand Animal feed yield Land required (thousand ha) Fresh water savings (billion m3/year)

55,403 1028 3800 (33%) 346 (20%) 89,244 (328%) 2063

31,093 577 1778 (15%) 176 (10%) 35,536 (131%) 1158

39,102 977 3021 (26%) 300 (17%) 48,892 (180%) 844

33,090 0 2825 (24%) 280 (16%) 24,980 (92%) 789

33,090 0 3109 (27%) 309 (18%) 24,980 (92%) 789

33,090 0 2825 (24%) 280 (16%) 24,980 (92%) 789

21,964 0 162 (1%) 16 (1%) 0 (0%) 523

39,708 0 3730 (32%) 371 (21%) 43,069 (158%) 946

21,964 0 162 (1%) 16 (1%) 0 (0%) 523

39,708 0 3730 (32%) 371 (21%) 43,069 (158%) 946

7.5

3.2

4.5

2.2

3.7

2.3

~0.0

3.9

~0.0

4.0



13

and corn ethanol produced in the U.S. [81]. However, low EROI values – particularly an EROI b 3 – have been linked to economic recession [82]. There are similar financial challenges. Although Case 4T would achieve a break-even point after 30 years with minimum biocrude or animal feed sale prices of $3.02/L and $2444/MT (Fig. 4), if these products can only fetch market prices for less valuable products, the venture does not reach a break-even cumulative discounted cash flow within 40 years of operation, thereby preventing actual investment. Clearly, a breakeven cumulative discounted cash flow that exceeds the expected facility lifetime (30 years) would prevent actual investment. For a viable algal biofuels industry, high-value products are required, fetching the minimum sale prices shown in Fig. 4. The ability to achieve the high values listed in Fig. 4 for algal biocrude and algae meal for animal feed is therefore a critical area for future study. Due to the water intensive nature of corn and soybean production (246 m3 and 42 m3 depletion per MT of U.S. corn and soybean meal produced, respectively [47]), replacing corn and soybean meal with algae meal (assuming 25% of the algae meal replaces corn and 75% of the algae meal replaces soybean meal — representative of typical poultry and swine diets) for animal feed would provide huge fresh water savings. For instance, producing 18.9 billion L of biocrude would require 789,000 ha of land (non-arable, but located near CO2 and seawater, notably less than the estimate by Pate et al. [75]) and 2.2 billion m3 of fresh water would be saved each year (by avoiding the fresh water consumed for conventional animal feed production) — enough to fulfill the water demands of roughly 7.9 million Californians (assuming 757 L/Californian-day [83]). In addition to the water savings, this production would displace 92% of the soybean meal animal feed market, thereby freeing current soybean fields for alternative use or preventing further deforestation for global protein production. Of the five environmental impacts evaluated in the LCA, the human health and resource indicators show slight harmful balances, largely as a result of the electricity consumption. However, the remaining indicators demonstrate major environmental benefits for large-scale deployment of Case 4T.

With these limitations in mind, it is important to recognize that global fuel and protein demand is projected to rise sharply along with the growing global population. Marine algae represent a potential candidate for large-scale production of both fuel and protein, with the possibility of yielding several other global benefits such as reducing fresh water consumed for agriculture, reducing the amount of arable land required to produce the world's protein (thereby preventing further deforestation, reducing greenhouse gas emissions and other environmental damage), yielding omega-3-fatty-acid rich animal feeds that improve herd health, and providing locally-produced high-quality petroleum fuel substitutes for applications requiring high energy density transportation fuels (e.g., semi-trucks and airplanes) that other biofuels cannot supply. Thus, despite many remaining barriers (including carbon and nutrient acquisition, high capital costs, and geographic sensitivity), the novel facility design and integrated processing pathways presented in this study represent several options to produce feed and fuel from algae to meet the demands of a rapidly growing world population.

3.3.4. Conclusions While this study demonstrates that progress is being made in the field of algal biofuels and bioproducts (as new technologies continue to improve the economic and environmental potential of algae products), it also illustrates that widespread near-term investment is not feasible. Even the most promising cases yield minimum sale prices that exceed expected near-term market commodity prices for petroleum and/or animal feeds. Although the EROI for many cases in this study are greater than unity, which represents energy-positive operation, most cases yield an EROI that is too low to be economically viable (it is estimated that an EROI N 3 is needed [82]). In addition, the requirements for high purity CO2 and large amounts of fertilizer are barriers to large-scale commercial deployment. Finally, the large capital cost (tensof-millions of dollars with associated financing) and high risk associated with a large-scale algae production facility also deter realized algae production at commodity scale. Based on the results of this study, potential means of improvement include:

Supplementary information for this article can be found online at http://dx.doi.org/10.1016/j.algal.2015.04.017.

1) Producing additional high-value co-products, such as omega-3 supplements, pharmaceuticals, or cosmetics 2) Improve biomass productivity over 25 g/m2-day 3) Developing automated technologies to reduce labor costs 4) Creating advanced pond liner materials and pond designs to reduce capital costs below $2/m2 5) Integrating algae production with low-cost renewable electricity 6) Using atmospheric carbon and/or waste forms of carbon, nitrogen, and phosphorus 7) Reducing pipe costs using canals or low-cost materials. 8) Downstream processing improvements

Conflict of interest Co-author, M. Huntley, has a financial interest in Cellana LLC. Acknowledgments Funding for the techno-economic and life cycle assessment was provided by awards from US Department of Energy (DE-EE0003371) and US Department of Agriculture (2011-10006-30361) to the Cornell Marine Algae Biofuels Consortium, and is based on the results of large scale production trials funded by Royal Dutch Shell at Cellana's Kona Demonstration Facility (KDF) for the period from 2007 to 2011. Michael Walsh was supported by the National Biomedical Research Foundation. We thank all members of the Cornell Marine Algae Biofuels Consortium. Appendix A. Supplementary Information (SI)

References [1] Congress, U.S., Energy Independence and Security Act of 2007, One Hundred Tenth Congress of the United States of America, H.R.6, 2007 (H.R.6). [2] United States DOE, National Algal Biofuels Technology Roadmap, 2010. [3] K. Howell, Exxon sinks $600 M into algae-based biofuels in major strategy shift, The New York Times, 2009. [4] J. Benemann, I. Woertz, T. Lundquist, Life cycle assessment for microalgae oil production, Disruptive Sci. Technol. 1 (2) (2012) 68–78. [5] J.W. Richardson, et al., A financial assessment of two alternative cultivation systems and their contributions to algae biofuel economic viability, Algal Res. 4 (2014) 96–104. [6] C.M. Beal, et al., Comprehensive evaluation of algal biofuel production: experimental and target results, Energies 5 (6) (2012) 1943–1981. [7] R.E. Davis, et al., Integrated evaluation of cost, emissions, and resource potential for algal biofuels at the national scale, Environ. Sci. Technol. 48 (10) (2014) 6035–6042. [8] J.C. Quinn, et al., Microalgae to biofuels lifecycle assessment — multiple pathway evaluation, Algal Res. 4 (2014) 116–122. [9] J.W. Richardson, et al., Harvesting and extraction technology contributions to algae biofuels economic viability, Algal Res. 5 (2014) 70–78. [10] M. Huntley, et al., Actual large-scale production of marine microalgae for fuels and feed, Algal Res. (2015) (in press). [11] R.E. Austic, et al., Potential and limitation of a new defatted diatom microalgal biomass in replacing soybean meal and corn in diets for broiler chickens, J. Agric. Food Chem. 61 (30) (2013) 7341–7348. [12] V. Kiron, et al., Marine microalgae from biorefinery as a potential feed protein source for Atlantic salmon, common carp and whiteleg shrimp, Aquac. Nutr. 18 (5) (2012) 521–531. [13] L. Batan, et al., Net energy and greenhouse gas emission evaluation of biodiesel derived from microalgae, Environ. Sci. Technol. 44 (20) (2010) 7975–7980. [14] L. Lardon, et al., Life-cycle assessment of biodiesel production from microalgae, Environ. Sci. Technol. 43 (17) (2009) 6475–6481. [15] A.F. Clarens, et al., Environmental life cycle comparison of algae to other bioenergy feedstocks, Environ. Sci. Technol. 44 (5) (2010) 1813–1819.


14


[16] P. Collet, et al., Life-cycle assessment of microalgae culture coupled to biogas production, Bioresour. Technol. 102 (2011) 207–214. [17] O. Jorquera, et al., Comparative energy life-cycle analyses of microalgal biomass production in open ponds and photobioreactors, Bioresour. Technol. 101 (4) (2010) 1406–1413. [18] A. Sun, et al., Comparative cost analysis of algal oil production for biofuels, Energy 36 (8) (2011) 5169–5179. [19] R.M. Handler, et al., Evaluation of environmental impacts from microalgae cultivation in open-air raceway ponds: analysis of the prior literature and investigation of wide variance in predicted impacts, Algal Res. 1 (1) (2012) 83–92. [20] L. Brennan, P. Owende, Biofuels from microalgae — a review of technologies for production, processing, and extractions of biofuels and co-products, Renew. Sust. Energ. Rev. 14 (2) (2010) 557–577. [21] R. Slade, A. Bauen, Micro-algae cultivation for biofuels: cost, energy balance, environmental impacts and future prospects, Biomass Bioenergy 53 (2013) 29–38. [22] D.L. Sills, et al., Quantitative uncertainty analysis of life cycle assessment for algal biofuel production, Environ. Sci. Technol. 47 (2) (2013) 687–694. [23] R. Davis, A. Aden, P.T. Pienkos, Techno-economic analysis of autotrophic microalgae for fuel production, Appl. Energy 88 (10) (2011) 3524–3531. [24] A.F. Clarens, et al., Environmental impacts of algae-derived biodiesel and bioelectricity for transportation, Environ. Sci. Technol. 45 (17) (2011) 7554–7560. [25] S. Grierson, V. Strezov, J. Bengtsson, Life cycle assessment of a microalgae biomass cultivation, bio-oil extraction and pyrolysis processing regime, Algal Res. 2 (3) (2013) 299–311. [26] J. Hou, et al., Life cycle assessment of biodiesel from soybean, jatropha and microalgae in China conditions, Renew. Sust. Energ. Rev. 15 (9) (2011) 5081–5091. [27] G. Finnveden, et al., Recent developments in life cycle assessment, J. Environ. Manag. 91 (1) (2009) 1–21. [28] T. Lundquist, et al., A Realistic Technology and Engineering Assessment of Algal Biofuel Production, Energy Biosciences Institute, University of California, Berkeley, California, 2010. 178. [29] C.M. Beal, et al., Energy return on investment for algal biofuel production coupled with wastewater treatment, Water Environ. Res. 84 (9) (2012) 692–710. [30] Westfalia Separator, Instruction Manual and Parts List No. 1354-9015-001, 2009. Model MSD 300-96-777. [31] C.M. Beal, et al., The energy return on investment for algal biocrude: results for a research production facility, Bioenergy Res. 5 (2) (2011) 341–362. [32] P.E. Wiley, J.E. Campbell, B. McKuin, Production of biodiesel and biogas from algae: a review of process train options, Water Environ. Res. 83 (4) (2011) 326–338. [33] P. Mason, Dedert Corporation Algae Ring Dryer, in: C.M. Beal (Ed.), 2014 (personal communication). [35] K. Sander, G. Murthy, Life cycle analysis of algae biodiesel, Int. J. Life Cycle Assess. 15 (7) (2010) 704–714. [36] POS Biosciences, Hexane Solvent Extraction, in: C.M. Beal (Ed.), 2010 (http://www. pos.ca/) (personal communication). [37] B. Goodall, K. Kadam, Valicor Conversion Processes, in: C.M. Beal (Ed.), 2014 (http:// www.valicor.com/renewables.aspx) (personal communication). [38] Y. Zhu, et al., Development of hydrothermal liquefaction and upgrading technologies for lipid-extracted algae conversion to liquid fuels, Algal Res. 2 (2013) 455–464. [39] H. Thomas, OpenAlgae Wet Extraction, in: C.M. Beal (Ed.), 2014 (www.openalgae.com) (personal communication). [40] R. Turton, et al., Analysis Synthesis and Design of Chemical Processes, 1998. [41] M.S. Wigmosta, et al., National microalgae biofuel production potential and resource demand, Water Resour. Res. 47 (3) (2011) W00H04. [42] Z.I. Johnson, Pond evaporation, Marine Algae Consortium Technical Report2010. 1–18. [43] M.A. Delucchi, M.Z. Jacobson, Providing all global energy with wind, water, and solar power, part II: reliability, system and transmission costs, and policies, Energy Policy 39 (2011) 1170–1190. [44] Austin Energy, Austin City Council Approves New Wind Contract to Reach Renewable Energy Goal. Available from: http://austinenergy.com/wps/portal/ae/about/news/ press-releases/austin-city-council-approves-new-wind-contract-to-reachrenewable-energy-goal/2014. [45] US Energy Information Administration, Table ET1. Primary Energy, Electricity, and Total Energy Price and Expenditure Estimates, 1970–2012, Texas/Hawaii. Available from: http://www.eia.gov/state/seds/data.cfm?incfile=/state/seds/2014. [46] R.S. Means, Heavy construction cost data, BNI News General Construction 2012 Costbook2012. [47] R. Frischknecht, et al., The ecoinvent database: overview and methodological framework, Int. J. Life Cycle Assess. 10 (2005) 3–9. [48] USDA, Land Rents, Quick Stats12-25-14; Available from: http://quickstats.nass.usda. gov/results/58B27A06-F574-315B-A854-9BF568F17652#7878272B-A9F3-3BC2960D-5F03B7DF48262014. [49] United States Internal Revenue Service, Publication 946 (2013), How to Depreciate Property, http://www.irs.gov/publications/p946/index.html, Editor. 2013. [50] World Bank, Global Economic Monitor (GEM) Commodities. Available from: http:// databank.worldbank.org/data/databases/commodity-price-data2014. [51] US Energy Information Administration, Cushing, OK WTI Spot Price FOB, Crude Oil. Available from: http://www.eia.gov/dnav/pet/hist/LeafHandler.ashx?n= PET&s=RWTC&f=D2014.

[52] Nebraska Ethanol Board Nebraska Energy Office, Ethanol and Unleaded Gasoline Average Rack Prices[cited 2014]; Available from: http://www.neo.ne.gov/statshtml/ 66.html 2014. [53] ISO, Environmental Management, Life Cycle Assessment, Principles and Framework, International Standard ISO 14 040, 2006. [54] ISO, Environmental Management, Life Cycle Assessment, Requirements and Guidelines, International Standard ISO 14 044, 2006. [55] L. Gerber, M. Gassner, F. Marechal, Systematic integration of LCA in process systems design: application to combined fuel and electricity production from lignocellulosic biomass, Comput. Chem. Eng. 35 (2011) 1265–1280. [56] O. Jolliet, et al., IMPACT 2002+: a new life cycle impact assessment methodology, Int. J. Life Cycle Assess. 8 (6) (2003) 324–330. [57] A. Lautier, et al., Development of normalization factors for Canada and the United States and comparison with European factors, Sci. Total Environ. 409 (1) (2010) 33–42. [58] M. Goedkoop, et al., in: Ruimte en Milieu (Ed.)ReCiPe 2008, 2013. [59] Qualitas Health, Qualitas Health and Valicor Renewables Announce Strategic Partnership to Commercialize Algae-based Omega-3 Supplements. Available from: http://www.qualitas-health.com/qualitas-health-and-valicor-renewables-announcestrategic-partnership-to-commercialize-algae-based-omega-3-supplements/2014. [60] Nordic Naturals, Algae Omega Liquid. Available from: http://www.nordicnaturals. com/en/Products/Product_Details/514/?ProdID=1649 2014. [61] Aurora Algae, Make Way for a Better Omega-3 Source. Available from: http://www. aurorainc.com/solutions/omega-3/2014. [62] C. Leschin-Hoar, Why farmed salmon is losing its omega-3 edge, Time, 2014 (http:// time.com/3620869/salmon-omega-3/). [63] L. Welch, Fish factor: salmon feed prices on the rise; strong chum landings on Yukon, Alaska J. Commer. (1) (2013). [64] P.J. Williams, M.L. Laurens, Microaglae as biodiesel & biomass feedstocks: review & analysis of the biochemistry, energetics, & economics, Energy Environ. Sci. 3 (2010) 554–590. [65] F. Delrue, et al., An economic, sustainability, and energetic model of biodiesel production from microalgae, Bioresour. Technol. 111 (2012) 191–200. [66] J.W. Richardson, M.D. Johnson, J.L. Outlaw, Economic comparison of open pond raceways to photo bio-reactors for profitable production of algae for transportation fuels in the southwest, Algal Res. 1 (1) (2012) 93–100. [67] L. Amer, B. Adhikari, J. Pellegrino, Technoeconomic analysis of five microalgae-tobiofuels processes of varying complexity, Bioresour. Technol. 102 (20) (2011) 9350–9359. [68] J. Benemann, W. Oswald, Systems and Economic Analysis of Microalgae Ponds for Conversion of CO2 to Biomass, Department of Energy, 1996. [69] J.C. Weissmann, R.P. Goebel, Design and Analysis of Microalgal Open Pond Systems for the Purpose of Producing Fuels: A Subcontract Report, Solar Energy Research Institute, 1987. [70] J.R. Benemann, et al., Microalgae as a Source of Liquid Fuels, Solar Energy Research Institute, 1982. [71] D.M. Wogan, An integrated resource and biological growth model for estimating algal biomass production with geographic resolution, Mechanical Engineering, University of Texas at Austin, Austin, TX, 2010. [72] K.L. Kadam, Environmental implications of power generation via coal-microalgae cofiring, Energy 27 (10) (2002) 905–922. [73] M. Huntley, D. Redalje, CO2 mitigation and renewable oil from photosynthetic microbes: a new appraisal, Mitig. Adapt. Strateg. Glob. Chang. 12 (4) (2007) 573–608. [74] M. Packer, Algal capture of carbon dioxide; biomass generation as a tool for greenhouse gas mitigation with reference to New Zealand energy strategy and policy, Energy Policy 37 (9) (2009) 3428–3437. [75] R. Pate, G. Klise, B. Wu, Resource demand implications for US algae biofuels production scale-up, Appl. Energy 88 (10) (2011) 3377–3388. [76] D.E. Canfield, A.N. Glazer, P.G. Falkowski, The evolution and future of Earth's nitrogen cycle, Science 330 (6001) (2010) 192–196. [77] J.N. Galloway, et al., Transformation of the nitrogen cycle: recent trends, questions, and potential solutions, Science 320 (5878) (2008) 889–892. [78] R. Nehring, Fertilizer Use and Price, USDA[cited 2014 2014]; Available from: http://www.ers.usda.gov/data-products/fertilizer-use-and-price.aspx#.U_ t5GvldVWE2013. [79] EPA, U.S. Major Crops Grown in the United States. Available from: http://www.epa. gov/agriculture/ag101/cropmajor.html2013. [80] A.R. Brandt, Converting oil shale to liquid fuels: energy inputs and greenhouse gas emissions of the shell in situ conversion process, Environ. Sci. Technol. 42 (19) (2008) 7489–7495. [81] A.E. Farrell, et al., Ethanol can contribute to energy and environmental goals, Science 311 (5760) (2006) 506–508. [82] C.W. King, Energy intensity ratios as net energy measures of United States energy production and expenditures, Environ. Res. Lett. 5 (4) (2010). [83] P. Rogers, N. St. Fleur, California drought: database shows big difference between water guzzlers and sippers, San Jose Mercury News, 2014.


Supplemental Information Algal biofuel production for fuels and feed in a 100-ha facility: a comprehensive technoeconomic analysis and life cycle assessment Colin M. Beal, Léda N. Gerber, Deborah L. Sills, Mark E. Huntley, Stephen C. Machesky, Michael J. Walsh, Jefferson W. Tester, Ian Archibald, Joe Granados, Charles H. Greene Contents A. Appendix A: Facility Design .................................................................................................. 5 Site Work .................................................................................................................................... 5 Terraces ................................................................................................................................... 5 Berms ...................................................................................................................................... 5 Trenching ................................................................................................................................ 5 Water Supply and Discharge Systems ...................................................................................... 10 Texas ..................................................................................................................................... 10 Hawaii ................................................................................................................................... 11 Seawater Reservoir ................................................................................................................... 11 Nutrient and Carbon Delivery................................................................................................... 11 Carbon Delivery .................................................................................................................... 12 Silicon Delivery .................................................................................................................... 12 Nitrogen and Phosphorus Delivery ....................................................................................... 13 PBRs ......................................................................................................................................... 14 Ponds ......................................................................................................................................... 16 B.

Appendix B: Daily Facility Operations ................................................................................ 19 Volume Transfers...................................................................................................................... 19 Salinity ...................................................................................................................................... 22

C.

Appendix C: Process Flow Diagrams and Processing Step Descriptions............................. 23 Harvesting and Dewatering: ..................................................................................................... 26 In-pond settling and secondary settling ................................................................................ 26 Centrifugation ....................................................................................................................... 26 Ring Dryer ............................................................................................................................ 27 Filter Press ............................................................................................................................ 27 Extraction/Conversion: ............................................................................................................. 27 Hexane Extraction (POS)...................................................................................................... 27 Valicor Thermochemical Conversion ................................................................................... 27 Hydrothermal Liquefaction ................................................................................................... 28

1

OpenAlgae Lipid Extraction ................................................................................................. 28 Catalytic Hydrothermal Gasification .................................................................................... 28 Combined Heat and Power ................................................................................................... 28 Fermentation ......................................................................................................................... 29 Mass and Nutrient Balances...................................................................................................... 29 D.

Appendix D: Production Costs: Energy and Materials ......................................................... 38

E.

Appendix E: Labor Estimates ............................................................................................... 43

F.

Appendix F: Capital Cost Estimates and Discounted Cash Flow ......................................... 46 Cumulative Discounted Cash Flow .......................................................................................... 60

G.

Appendix G: Life Cycle Inventory and Impact Definitions ................................................. 64 LCA Inventory .......................................................................................................................... 64 Impact Definitions .................................................................................................................... 66 Human Health ....................................................................................................................... 66 Ecosystem Quality ................................................................................................................ 67 Climate Change ..................................................................................................................... 67 Non-renewable Resources .................................................................................................... 67 Water Depletion Potential ..................................................................................................... 67

H.

Appendix H: Detailed Life Cycle Impact Assessment Results ............................................ 68

I.

Appendix I: Sensitivity Analysis Data .................................................................................. 73

List of Figures FIGURE A-1. THE 111-HA FACILITY IS ARRANGED ON 8 MAIN TERRACES, WITH AN ADDITIONAL PBR-TERRACE AND A SINGLE 1-DAY POND TERRACE LOCATED AT THE TOP OF THE FACILITY AND A DOWNSTREAM PROCESSING TERRACE LOCATED AT THE BOTTOM OF THE FACILITY. ALL UNITS ARE IN METERS. ... 6 FIGURE A-2. PBR END ASSEMBLIES. ALL UNITS ARE IN METERS. .............................. 7 FIGURE A-3. POND DESIGN. ALL UNITS ARE IN METERS. .............................................. 8 FIGURE A-4. TERRACED LAYOUT. ........................................................................................ 8 FIGURE A-5. PIPE LAYOUT. PIPE COLORING: 1-DAY POND DRAINS IN PINK, 2-DAY POND DRAINS IN WHITE, FRESH SEAWATER IN BLUE, PBR INOCULUM IN GREEN, SLUDGE PIPELINE TO PROCESSING IN YELLOW, AND NUTRIENT DELIVERY LINES IN ORANGE. ........................................................................................ 9 FIGURE A-6. PBR DRAIN LINES AND UPPER 1-DAY POND TERRACE. WASTE TRENCHES ARE SHOWN BESIDE THE ROAD. .............................................................. 9 FIGURE A-7. NUTRIENT STOCK TANK AND SEAWATER RESERVOIR. ....................... 10 FIGURE H-1. IMPACTS ON HUMAN HEALTH CALCULATED WITH IMPACT2002+ FOR ALL CASES IN TEXAS (T) AND HAWAII (H). POSITIVE CONTRIBUTIONS

2

REPRESENT HARMFUL IMPACTS, NEGATIVE ONES BENEFICIAL SUBSTITUTIONS OF PRODUCTS.................................................................................... 68 FIGURE H-2. IMPACTS ON ECOSYSTEM QUALITY CALCULATED WITH IMPACT2002+ FOR ALL CASES IN TEXAS (T) AND HAWAII (H). POSITIVE CONTRIBUTIONS REPRESENT HARMFUL IMPACTS, NEGATIVE ONES BENEFICIAL SUBSTITUTIONS OF PRODUCTS. .......................................................... 69 FIGURE H-3. IMPACTS ON CLIMATE CHANGE CALCULATED WITH IMPACT2002+ FOR ALL CASES IN TEXAS (T) AND HAWAII (H). POSITIVE CONTRIBUTIONS REPRESENT HARMFUL IMPACTS, NEGATIVE ONES BENEFICIAL SUBSTITUTIONS OF PRODUCTS.................................................................................... 70 FIGURE H-4. IMPACTS ON RESOURCES CALCULATED WITH IMPACT2002+ FOR ALL CASES IN TEXAS (T) AND HAWAII (H). POSITIVE CONTRIBUTIONS REPRESENT HARMFUL IMPACTS, NEGATIVE ONES BENEFICIAL SUBSTITUTIONS OF PRODUCTS.......................................................................................................................... 71 FIGURE H-5. IMPACTS ON WATER DEPLETION POTENTIAL CALCULATED WITH RECIPE FOR ALL CASES IN TEXAS (T) AND HAWAII (H). POSITIVE CONTRIBUTIONS REPRESENT HARMFUL IMPACTS, NEGATIVE ONES BENEFICIAL SUBSTITUTIONS OF PRODUCTS. .......................................................... 72 List of Tables TABLE A-1. CARBON, SILICON, NITROGEN, AND PHOSPHORUS REQUIREMENTS FOR THE FACILITY FOR THE 10 CASES. DATA ARE IN METRIC TONNES PER DAY. ..................................................................................................................................... 11 TABLE B-1. VOLUME TRANSFERS FOR EACH TERRACE. ALL CASES ARE IDENTICAL. TERRACES #8 - #3 ARE IDENTICAL TO TERRACE #9....................... 19 TABLE B-2. DAILY OPERATIONS SCHEDULE FOR THE FACILITY. TERRACE NUMBERS ARE LISTED IN APPENDIX A...................................................................... 21 TABLE B-3. SALINITY PROGRESSION IN FACILITY TERRACES. .................................. 22 TABLE C-1. CASE DESCRIPTIONS. ....................................................................................... 23 TABLE C-2. MASS AND NUTRIENT BALANCES FOR CASES 1-5. .................................. 29 TABLE C-3. MASS AND NUTRIENT BALANCES FOR CASES 6-10. ................................ 33 TABLE D-1. OPERATING ENERGY AND MATERIAL INPUTS AND OUTPUTS FOR CASE 1 - 5. ........................................................................................................................... 38 TABLE D-2. OPERATING ENERGY AND MATERIAL INPUTS AND OUTPUTS FOR CASE 5 - 10. ......................................................................................................................... 40 TABLE D-3. PRICES FOR ENERGY AND MATERIAL INPUTS AND OUTPUTS, AS WELL AS THE ENERGY IMPACT FACTORS FOR EACH INPUT AND OUTPUT. ... 42 TABLE E-1. LABOR ESTIMATES FOR THE TEXAS FACILITY. ........................................ 43 TABLE E-2. LABOR ESTIMATES FOR THE HAWAII FACILITY. ..................................... 45 TABLE F-1. CAPITAL COST UNIT VALUES FOR ALL 10 CASES. .................................... 46 TABLE F-2. PIPE COST ESTIMATES. ..................................................................................... 52 TABLE F-3. CAPITAL COSTS FOR ALL 10 CASES. ALL DATA ARE IN THOUSANDS OF DOLLARS. ..................................................................................................................... 54 TABLE F-4. CAPITAL COST SUMMARY. ............................................................................. 59 TABLE F-5. MACRS DEPRECIATION SCHEDULE. ............................................................. 60

3

TABLE F-6. DEPRECIATION FOR TEXAS AND HAWAII. ALL VALUES ARE IN MILLIONS OF DOLLARS. ................................................................................................. 60 TABLE F-7. ANNUAL REVENUE AND OPERATING COSTS IN MILLIONS OF DOLLARS. *THE TOTAL OPERATING COSTS SHOWN HERE EXCLUDE LOAN PAYMENTS AND TAXES, WHICH VARY FROM YEAR TO YEAR. **THE LOAN TERM IS 10-YEARS. TAXES ARE NEGLIGIBLE. ......................................................... 61 TABLE F-8. CUMULATIVE DISCOUNTED CASH FLOW EACH YEAR IN MILLIONS OF DOLLARS. ........................................................................................................................... 61 TABLE G-1. CHOSEN ECOINVENT© EQUIVALENCES (VERSION 3.1) FOR THE DIFFERENT ELEMENTS OF THE LIFE CYCLE INVENTORIES. ................................ 64 TABLE G-2. DETAILED LIFE CYCLE INVENTORIES FOR CASES 1 TO 5. ...................... 65 TABLE G-3. DETAILED LIFE CYCLE INVENTORIES FOR CASES 6 TO 10. .................... 66 TABLE I-1. RESULTS FOR THE SENSITIVITY ANALYSIS WITH FAVORABLE PARAMETERS ARE SHOWN IN RED AND UNFAVORABLE PARAMETERS ARE SHOWN IN BLUE. IN A FEW CASES, PARAMETERS ARE FAVORABLE FOR SOME METRICS AND UNFAVORABLE FOR OTHERS. .............................................. 73

4

A. Appendix A: Facility Design Site Work Terraces The facility was designed to be constructed on a 1% slope in sandy loamy soil. The site is prepared with cut-and-fill earthworks to create the following terraces: #1) Upper terrace containing the PBRs, water reservoir, and nutrient reservoirs. Dimensions: 705 m x 324 m at 2 m of elevation above terrace #2. #2) Upper-most 1-day pond terrace containing one 1-day pond on either side of the road. Dimensions: 705 m x 45 m at 1.55 m of elevation above terrace #3 #3 - #9) Main terraces containing one 1-day pond and four 2-day ponds on either side of the road. Dimensions: 705 m x 155 m at 1.55 m of elevation above terrace #10 #10) Lowest 2-day pond terrace containing four 2-day ponds on either side of the road. Dimensions: 705 m x 123 m at 1.55 m of elevation above terrace #10 #11) Processing terrace containing two secondary settling reservoirs and the processing facilities. Dimensions: 705 m x 10 m. The total earthworks required to construct these terraces is 360,000 m3. Berms The berm volume for each pond was determined from Solidworks to be 107 m3 and the seawater and nutrient reservoirs require 1,000 m3 of berm construction, yielding a total berm volume of 9,500 m3. Trenching Pond drain plumbing is constructed underground and each terrace requires 620 m of trenching length at a cross section of 1.5 m2, yielding 7,440 m3 of trenching and backfill. A waste trench is constructed on either side of the road – 2,480 m in length and 1.5 m2 in cross section.

5

Figure A-1. The 111-ha facility is arranged on 8 main terraces, with an additional PBR-terrace and a single 1-day pond terrace located at the top of the facility and a downstream processing terrace located at the bottom of the facility. All units are in meters.

6

Figure A-2. PBR end assemblies. All units are in meters.

7

Figure A-3. Pond design. All units are in meters.

Figure A-4. Terraced layout.

8

Figure A-5. Pipe layout. Pipe coloring: 1-day pond drains in pink, 2-day pond drains in white, fresh seawater in blue, PBR inoculum in green, sludge pipeline to processing in yellow, and nutrient delivery lines in orange.

Figure A-6. PBR drain lines and upper 1-day pond terrace. Waste trenches are shown beside the road.

9

Figure A-7. Nutrient stock tank and seawater reservoir.

Water Supply and Discharge Systems Head loss is calculated according to the following equation: 1

∆𝑃𝑃 = 𝜌𝜌𝜌𝜌(∆𝑧𝑧 + 𝑓𝑓

𝐿𝐿 𝑉𝑉 2 𝐷𝐷 2𝑔𝑔

+ 𝐾𝐾𝐿𝐿

𝑉𝑉 2 ) 2𝑔𝑔

where: density (𝜌𝜌) is 1 kg/L, ∆𝑧𝑧 is the elevation change, friction factor (𝑓𝑓) is approximated as

0.015 for all flows, pumping distance is 𝐿𝐿, pipe diameter is 𝐷𝐷, mean flow velocity is 𝑉𝑉, minor

loss coefficient (𝐾𝐾𝐿𝐿 ) is the sum of corner (0.3), entry (0.5), and exit coefficients (1), and 𝑔𝑔 is the gravity constant (9.8 m/s2). Texas New seawater is supplied to the facility by a pipeline (5,817 m in length with 17.1 m of elevation change) with an offshore intake providing 27,000 m3 of new medium each day (at a mean fluid velocity of 2.6 m/s). The seawater is filtered using a primary sand filter and a secondary cartridge filter (0.5 μm). It is assumed that the pipeline is 0.5 m in diameter with 10 corners.

10

The pump and filter contribute 40 m of additional head loss. The total head loss for the pipeline is 130 m. The discharge supernatant (19,000 m3/day) is returned to the ocean by a 1-m diameter pipeline (5,000 m in length originating at an elevation of 1.9 m above sea level). Solving equation 1 yields a mean flow velocity of 0.7 m/s, thus draining requires 9.4 hrs. Hawaii New seawater is supplied to the facility from a well (with a static head of 19.1 m) providing 27,000 m3 of new medium each day (at a mean fluid velocity of 6.1 m/s). The seawater is drawn from a dark lens and therefore does not require filtering. It is assumed that there are 5 corners in the water supply line and the total head loss for the well pump is 29 m. The discharge supernatant (19,000 m3/day) is returned to the underground lens with an injection well (76 m in depth with 0.5 m diameter and 57 m of backpressure head). Solving equation 1 yields a mean flow velocity of 9.7 m/s, thus draining requires 3.3 hrs. Seawater Reservoir The new seawater reservoir, built with earthen berms and located at the top of the facility, is 583 m x 75 m x 0.75 m – sufficient for the 27,000 m3 of daily intake. Nutrient and Carbon Delivery Table A-1 lists the carbon and nutrient requirements for each case, along with the recycling amounts. Table A-1. Carbon, silicon, nitrogen, and phosphorus requirements for the facility for the 10 cases. Data are in metric tonnes per day.

Case Carbon Demand Silicon Demand Silicon Recycling Nitrogen Demand Nitrogen Recycling

1 8.63 0.16 0.00 0.59 0.00

2 8.63 0.16 0.00 0.59 0.05

3 14.89 0.37 0.00 1.38 0.13

4 13.48 0.00 0.00 1.38 0.13

5 13.48 0.00 0.00 1.38 0.00

6 13.48 0.00 0.00 1.38 0.13

7 13.48 0.00 0.00 1.38 1.27

8 13.48 0.00 0.00 1.38 0.00

9 13.48 0.00 0.00 1.38 1.27

10 13.48 0.00 0.00 1.38 0.00

11

Phosphorus Demand 0.05 0.05 0.13 Phosphorus Recycling 0.00 0.00 0.01

0.13 0.01

0.13 0.00

0.13 0.01

0.13 0.12

0.13 0.00

0.13 0.12

0.13 0.00

Carbon Delivery Carbon is provided to the facility as a 94% CO2 waste stream form a hydrogen production facility located 15 km from the algae production facility. Due to complex fluid mechanics associated with compressible flow, intermittent demand, line packing, and temperature fluctuations, the energy required for transporting the CO2 stream was approximated by assuming compression to 10 atm using the following equation, 2

𝐸𝐸𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 =

𝑐𝑐𝑝𝑝 ∗𝑇𝑇 𝜂𝜂

𝑃𝑃

𝛾𝛾−1 𝛾𝛾

∙ �� 𝑃𝑃𝑓𝑓 � 𝑜𝑜

− 1�

𝑘𝑘𝑘𝑘

�𝑘𝑘𝑘𝑘�

where 𝑐𝑐𝑝𝑝 is the specific heat capacity (0.85 kJ/kg-K), 𝑇𝑇 is the temperature (298 K), 𝜂𝜂 is the

compression efficiency (0.85), 𝑃𝑃𝑓𝑓 is the final pressure (10 atm), 𝑃𝑃𝑜𝑜 is the initial pressure (1.2

atm), and 𝛾𝛾 is the ratio of specific heats (1.4). The total energy required for carbon delivery is calculated by multiplying the result of Equation 2 by the mass of gas transported per day as shown in Table A-1. Silicon Delivery Silicon is provided as a concentrated stock solution of sodium silicate pentahydrate (Na2SiO3 5H20). The stock is prepared daily in a mixing reservoir located on the upper-most terrace and delivered to culture volumes by gravity flow. The relevant parameters for stock preparation are: silicon fertilizer demand, 𝑀𝑀𝑆𝑆𝑆𝑆 (Table A-1), silicon uptake efficiency, 𝜂𝜂𝑆𝑆𝑆𝑆 (1), density of silicon

fertilizer, 𝜌𝜌𝑠𝑠𝑠𝑠 𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠 (1750 g/L), solubility of fertilizer, 𝑆𝑆𝑠𝑠𝑠𝑠 (440 g/L), salinity, 𝜇𝜇 (33 g/L), saturation of stock solution, 𝜆𝜆𝑆𝑆𝑆𝑆 (0.18), days for dissolving (1). The volume of the stock solution, ∀𝑠𝑠𝑠𝑠 𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠 ,

is calculated as,

12

3

∀𝑠𝑠𝑠𝑠 𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠 =

𝑀𝑀𝑆𝑆𝑆𝑆 /𝜂𝜂𝑆𝑆𝑆𝑆 (𝑆𝑆𝑠𝑠𝑠𝑠

1

∙ 103 ∗ �𝜆𝜆 � −𝜇𝜇) 𝑆𝑆𝑆𝑆

𝑚𝑚3

� 𝑑𝑑 �

The silicon fertilizer reservoir is mixed 24 hours per day at a rate of 0.249 kW/m3. The stock solution is delivered to PBRs in 1.5 hours via the following pipelines: 0.1 m diameter inlets to each PBR (1 m in length with 2 corners, 0.015 m/s flow) from a 0.5 m diameter delivery manifold (828 m in length with 2 corners, 0.11 m/s flow). The total head loss for the PBR silicon solution delivery system (from Equation 1) is 0.016 m and driven with 1.5 m of static head between the silicon reservoir and the PBR inlets. The stock solution is delivered to ponds over 54 minutes via the following pipelines: 0.2 m diameter inlets to each pond (5 m in length with 2 corners, 0.25 m/s flow) from a 0.5 m diameter delivery manifold (155 m in length with 2 corners on each tier, 0.11 m/s flow). The total head loss for the pond silicon solution delivery system (from Equation 1) is 0.004 m per tier due to low speed flow and driven with 1.55 m of static head between each tier. Nitrogen and Phosphorus Delivery Nitrogen and phosphorus are provided as a concentrated stock solution of the following fertilizers: sodium nitrate (NaNO3) and sodium phosphate (NaH2PO4) for Case 1 and ammonia (NH3) and diammonium phosphate (DAP, (NH4)2HPO4) for all other cases. Dissolution requires 11 days and therefore there are two stock solution mixing reservoirs with 11-day solution capacity on the upper-most terrace and delivered to growth volumes by gravity flow. The relevant parameters for stock preparation are: nitrogen fertilizer demand, 𝑀𝑀𝑁𝑁 (Table A-1),

nitrogen uptake efficiency, 𝜂𝜂𝑁𝑁 (1), density of nitrogen fertilizer, 𝜌𝜌𝑁𝑁 𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠 (2260 g/L for sodium

nitrate and 0.73 g/L for ammonia), solubility of fertilizer, 𝑆𝑆𝑁𝑁 (870 g/L for sodium nitrate and 500 g/L for ammonia), salinity, 𝜇𝜇 (33 g/L), saturation of nitrogen in stock solution, 𝜆𝜆𝑁𝑁 (0.5),

phosphorus fertilizer demand, 𝑀𝑀𝑃𝑃 (Table A-1), phosphorus uptake efficiency, 𝜂𝜂𝑃𝑃 (1), density of

13

phosphorus fertilizer, 𝜌𝜌𝑃𝑃 𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠 (2040 g/L for sodium phosphate and 1203 g/L for DAP), solubility of fertilizer, 𝑆𝑆𝑃𝑃 (480 g/L for sodium phosphate and 580 g/L for DAP), saturation of phosphorus in stock solution, 𝜆𝜆𝑃𝑃 (0.05), and days for dissolving (11).

The volume of the stock solution, ∀𝑁𝑁&𝑃𝑃 𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠 , is calculated as, 4

𝑀𝑀 /𝜂𝜂

1

𝑀𝑀 /𝜂𝜂

1

𝑁𝑁 𝑃𝑃 ∀𝑁𝑁&𝑃𝑃 𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠 = (𝑆𝑆𝑁𝑁 −𝜇𝜇) ∙ 103 ∗ �𝜆𝜆 � + (𝑆𝑆𝑃𝑃 −𝜇𝜇) ∙ 103 ∗ �𝜆𝜆 � 𝑁𝑁

𝑁𝑁

𝑃𝑃

𝑃𝑃

𝑚𝑚3

� 𝑑𝑑 �

The nitrogen and phosphorus fertilizer reservoirs are mixed 24 hours per day at a rate of 0.249 kW/m3. The stock solution is delivered to PBRs in 1.5 hours via the following pipelines: 0.1 m diameter inlets to each PBR (1 m in length with 2 corners, 0.016 m/s flow) from a 0.4 m diameter delivery manifold (828 m in length with 2 corners, 0.55 m/s flow). The total head loss for the PBR nitrogen and phosphorus solution delivery system (from Equation 1) varies between 0.3 and 0.7 m and is driven with 1.5 m of static head between the reservoir and the PBR inlets. The stock solution is delivered to ponds over 1.3 hours via the following pipelines: 0.1 m diameter inlets to each pond (5 m in length with 2 corners, 0.50 m/s flow) from a 0.3 m diameter delivery manifold (155 m in length with 2 corners on each tier, 0.30 m/s flow). The total head loss for the pond nitrogen and phosphorus solution delivery system (from Equation 1) varies between 0.03 m and 0.08 m per tier due to low speed flow and driven with 1.55 m of static head between each tier.

PBRs The PBR design is described in detail by Huntley et al. [1] and illustrated in Figure A-2. In brief, there are 480 PBRs, each containing 50 m3 of fluid volume in two 244 m long circulation legs with 0.38 diameter polyethylene plastic tubing. One blower provides airflow for 12 PBR airlifts. Each PBR tube is spaced evenly such that 1 PBR occupies 371 m2. The PBRs are driven with

14

airlift pumps that have a 2 m riser. Carbon and nutrients are injected into the airlift tubing. The power required to circulate fluid in the PBRs [2-4], 𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 , is calculated by 𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 =

5

𝜌𝜌∙𝑔𝑔∙∆𝑃𝑃∙𝑄𝑄 𝜂𝜂𝑃𝑃𝑃𝑃𝑃𝑃

[𝑊𝑊]

where 𝜌𝜌 is the fluid density (1,024 g/L), g is the gravity constant (9.8 m/s2), ∆𝑃𝑃 is the head loss

as determined by Equation 6, 𝑄𝑄 is the flow rate (0.04 m3/s), and 𝜂𝜂𝑃𝑃𝑃𝑃𝑃𝑃 is the PBR airlift efficiency (0.25). The head loss is 6

∆𝑃𝑃 = ∆𝑃𝑃𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠ℎ𝑡𝑡 + ∆𝑃𝑃𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 = 𝐿𝐿 ∙

�𝛽𝛽 2 ∙𝑉𝑉 2 � 4 𝑅𝑅𝐻𝐻 3

𝑉𝑉 2

+ 𝐾𝐾𝐿𝐿 ∙ �2𝑔𝑔�

[𝑊𝑊]

where ∆𝑃𝑃𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠ℎ𝑡𝑡 is the head loss for the straight PBR tubes, ∆𝑃𝑃𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 is the head loss for the

bends, 𝐿𝐿 is the straight tube length (488 m), 𝛽𝛽 is the manning coefficient (0.01), 𝑉𝑉 is the velocity

(0.4 m/s), 𝑅𝑅𝐻𝐻 is the hydraulic radius (0.115 m), 𝐾𝐾𝐿𝐿 is the total minor loss coefficient for the six

90-degree bends (6), and g is the gravity constant (9.81 m/s2). The total head loss for one PBR is 0.19 m. The PBR airlift efficiency was determined by reading the power consumption from an actual Elektror blower curve needed to produce the required air flow (8.85 SCFM/PBR as shown in Equation 7) at the specified pressure (21 kPa (gage) from Equation 8), which was determined to be 3,680 W and compared with the theoretical power requirement to move the fluid in the PBR from Equation 5, which is 926 W, yielding a 25% efficiency. The power required to move the fluid in one PBR is 77 W. The PBRs are circulated 24 hours per day. The compressed airflow required for each PBR is calculated as, 7

𝑄𝑄𝑎𝑎𝑎𝑎𝑎𝑎 =

𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 ∙𝜂𝜂𝑃𝑃𝑃𝑃𝑃𝑃

𝜌𝜌∙𝑔𝑔∙ℎ𝑟𝑟 𝑅𝑅∙𝑇𝑇∙ln(1+ ) 𝑃𝑃𝑎𝑎𝑎𝑎𝑎𝑎

�

𝑘𝑘𝑘𝑘𝑘𝑘𝑘𝑘 𝑠𝑠

�

15

where 𝑅𝑅 is the gas constant, 𝑇𝑇 is the temperature (298 K), ℎ𝑟𝑟 is the riser height (2 m), and 𝑃𝑃𝑎𝑎𝑎𝑎𝑎𝑎 is atmospheric pressure (101 kPa). The outlet blower pressure, 𝑃𝑃𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏 , was determined as, 8

𝑃𝑃𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏 = 𝑃𝑃𝑓𝑓 ∙ 𝑒𝑒

𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 ∙𝜂𝜂𝑃𝑃𝑃𝑃𝑃𝑃 𝑅𝑅∙𝑇𝑇∙𝑄𝑄𝑎𝑎𝑎𝑎𝑎𝑎

where 𝑃𝑃𝑓𝑓𝑓𝑓 is the final air pressure (106 kPa).[3, 4]

[𝑃𝑃𝑃𝑃]

All of the PBRs are harvested at 50% per day to inoculate the 1-day ponds via the following pipelines: 0.1 m diameter PBR outlets (2 m in length, 2 corners, 0.57 m/s flow), 0.5 m diameter manifold pipe (826 m in length, 3 corners, 1.55 m/s flow), two 0.4 m diameter 1-day pond inoculum pipelines (155 m on each tier, 2 corners, 1.21 m/s), and 1-day pond inlets with 0.4 m diameter (5 m in length, 1 corner, 1.21 m/s). The total head loss for each tier in the PBR drain line is 2.66 m, driven by 3.5 m of elevation head (2m in the PBR riser and 1.55 m per tier). The PBRs are filled from the seawater reservoir through the following pipelines: there are 10 outlet ports from the seawater reservoir of 0.3 m diameter (3 m in length, 1 corner, 3.69 m/s flow) that feed into a PBR-fill manifold with 0.5 m diameter (826 m in length, 0 corners, 0.66 m/s), PBR inlet lines with 0.1 m diameter (2 m in length, 2 corners, 0.61 m/s flow). The total head loss for the PBR fill system is 1.46 m, driven by a 1.5 m elevation between the reservoir and PBRs. Ponds The pond design is described in detail by Huntley et al. [1] and illustrated in Figure A-3. In brief, there are 16 1-day ponds and 64 2-day ponds, each containing 1,500 m3 of fluid volume with 0.15 m average depth and occupying 10,600 m2. For circulation, paddlewheels are used in Case 1 and airlifts are used in Cases 2-10.[3-5] For both scenarios, the power required to move the fluid in the pond is calculated as,

16

9

𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 =

𝜌𝜌∙𝑔𝑔∙∆𝑃𝑃∙𝑄𝑄 𝜂𝜂𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝

[𝑊𝑊]

where 𝜌𝜌 is the fluid density (1,024 g/L), g is the gravity constant (9.8 m/s2), ∆𝑃𝑃 is the head loss

as determined by Equation 6 (with the following parameters: 𝐿𝐿 = 679 m, 𝛽𝛽 = 0.01, 𝑉𝑉 = 0.4 m/s, 𝑅𝑅𝐻𝐻 = 0.147 m, 𝐾𝐾𝐿𝐿 = 8 (2 bends and a sump)). The total head loss for one pond is 0.21 m.

The paddlewheel efficiency was taken to be 0.1 [5] and the airlift blower efficiency was assumed to be the same as that for the PBRs (0.25). The power required to move the fluid in one pond is 1,820 W. The pond circulation duty cycles are: 24 hours/day for Case 1, 16 hours/day for Cases 2-8, and 12 hours/day for Cases 9 and 10. The 1-day ponds are drained each day and transferred to the 2-days ponds with a 155 m long pipeline on each tier with a 0.5 m diameter (3 corners, 2.08 m/s flow). Draining takes 1 hour. The 1-day ponds are inoculated from PBRs and filled with new seawater from the following pipelines: reservoir drain port with 0.5 m diameter (250 m in length, 1 corner, 1.07 m/s flow), pipeline to 1-day ponds with 0.4 m diameter (155 m in length per tier, 2 corners, 1.67 m/s flow), 1-day pond inlet lines with 0.35 m diameter (5 m in length, 1 corner, 2.19 m/s flow). The total head loss per tier for the 1-day pond seawater fill lines is 2.48 m, driven by 3.55 m of elevation head (2 m in the PBR riser and 1.55 m for each tier). Half of the 2-day ponds are harvested each day using an adjustable standpipe to first drain off the supernatant (for recycle, excepting the lowest terrace) and then, when lowered, to drain the sludge for processing. The 2-day pond drain lines are 0.5 m in diameter and 155 m in length (7 corners, 1.68 m/s flow for supernatant and 0.43 m/s for the sludge). Because only half of the ponds are drained each day, the four 2-day ponds on each terrace share two drain lines. The supernatant is sent to the ponds on the next terrace, which takes 1 hour and 12 minutes, and the sludge is directed into a 0.4 m diameter pipeline along the road and sent to processing (at the

17

bottom of the facility), which takes 18 minutes. The total head loss for the supernatant draining from one terrace to the next varies between 1.4 m and 1.5 m, driven by 1.55 m of elevation between terraces. The total head loss for the sludge draining varies between 0.6 and 1.4 m per terrace, driven by 3.1 m of elevation (the elevation of two terraces, as the drain line spans on terrace and the sludge pipeline spans another). The upper-most 2-day pond terrace is supplied with new seawater from the seawater reservoir using the following pipelines: 0.5 m diameter line from the reservoir (250 m in length, 1 corner, 1.93 m/s flow), a manifold line with 0.5 m diameter (155 m in length, 2 corners, 0.96 m/s flow), and inlets to each pond with 0.2 m diameter (3 m in length, 1 corner, 3.0 m/s flow). The total head loss for this flow is 3.27 m, driven by 4.6 m of head between the reservoir and the uppermost ponds.

18

B. Appendix B: Daily Facility Operations Volume Transfers The daily volume transfers for each terrace are shown in Table B-1. The transfers are the same for all cases. As shown in Table B-2, harvesting begins at the lowest terrace (#10) and progresses uphill. Table B-1. Volume transfers for each terrace. All cases are identical. Terraces #8 - #3 are identical to terrace #9. System Summary Total System Growth Volume (m3) Total Growth System Area (m2) Total Cultivation Area (Pond, PBR, Berm, ha) Total Facility Area (ha) Total New Sea Water Intake (m3/day) Total New Fresh Water Intake (m3/day) Total Saline Discharge (m3/day) Total Sludge Output (m3/day) Total New Seawater Intake (gal/gal oil) Hours of Pumping (hr) Total New Seawater Intake (gpm) Pond Terrace Dimensions Number of 2-day ponds per Pod Number of 1-day ponds per Pod Number of "Pond Pods" Rows of Pods Number of Terraces

All Cases 114006 919638 103 111 27399 17 19137 1260 9298 18 6703

4 1 16 2 8.00

Lower Terrace (#10) Volume Balance: Total Volume on Terrace (m3) Sludge Produced (m3/terrace-day) 2-day ponds Evaporation (m3/terrace-day) Discharge Saline Water (m3/day) New Seawater for 1-day ponds (m3/terrace-day) Inoculum from 1-day ponds (m3/terrace-day) Supernatent Intake (m3/terrace-day) Growth Volume Retained (m3/terrace-day) Salt in 2-day pond Day 1 (kg) Initial Salt Concentration 2-day pond (kg/m3) Salt in 2-day pond Day 2 (kg) Final Salt Concentration (kg/m3)

6001.25 104.96 168.03 2811.65 0.00 1458.30 1626.34 2916.61 57074.59 38.04 58460.88 38.97

Terrace #9 Volume Balance: Total Volume on Terrace (m3)

7501.56

19

Sludge Produced (m3/terrace-day) 2-day pond Evaporation (m3/terrace-day) 1-Day Pond Evaporation (m3/terrace-day) Supernatent To Next Terrace (m3/terrace-day) Inoculum to Next Terrace (m3/terrace-day) Supernatent Discharge (m3/terrace-day) Growth Volume Retained (m3/terrace-day) Inoculum from 1-day ponds (m3/terrace-day) Inoculum from PBR's (m3/terrace-day) New Seawater for 1-day ponds (m3/terrace-day) Supernatent Intake (m3/terrace-day) Additional Intake (m3/terrace-day) Salt in 2-day pond Day 1 (kg) Initial Salt Concentration 2-day pond (kg/m3) Salt in 2-day pond Day 2 (kg) Final Salt Concentration (kg/m3)

104.96 168.03 42.01 1626.34 1458.30 1185.31 2916.61 1458.30 722.60 777.71 1626.34 777.71 55812.28 37.20 57198.56 38.12

Upper 1-Day Pond Terrace (#2) Volume Balance: Total Volume on Terrace (m3) 1-Day Pond Evaporation (m3/terrace-day) Inoculum to Next Terrace (m3/terrace-day) Inoculum from PBRs (m3/terrace-day) Upper 1-Day Pond Rinsing (m3/terrace-day) Additional Intake (m3/terrace-day) Salt in 1-Day Pond (kg) Initial Salt Concentration 1-Day Pond (kg/m3) Final Salt Concentration (kg/m3)

1500.31 42.01 1458.30 722.60 395.10 777.71 51293.24 34.19 35.17

PBR (Terrace #1) Volume Balance: Total PBR Volume (m3) PBR Evaporation (m3/day) PBR Inoculum to 1-day ponds (m3/day) Intake (m3/day) PBR Area (m2) Sea Water Salt Concentration (kg/m3) Steady-state PBR Salinity (kg/m3) Salt in PBR Day 1 (kg) Initial Salt Concentration PBR (kg/m3) Salt in PBR Pond Day 2 (kg) Final Salt Concentration (kg/m3)

23986.86 863.53 11561.66 12425.19 178022.40 33.00 35.47 1708.59 34.19 1708.59 35.47

20

Table B-2. Daily operations schedule for the facility. Terrace numbers are listed in Appendix A. Step Drain Terrace 10 Supernatent Drain Terrace 10 Sludge Drain Terrace 9 Supernatent Rinse Terrace 10 2-day ponds Inoculate Terrace 10 from Terrace 9 1D Pond Drain Terrace 9 Sludge Drain Terrace 8 Supernatent Rinse Terrace 9 2-day ponds Rinse Terrace 9 1-day pond Inoculate Terrace 9 from Terrace 8 1-day pond Inoculate Terrace 9 1-day pond Drain Terrace 8 Sludge Drain Terrace 7 Supernatent Rinse Terrace 8 2-day ponds Rinse Terrace 8 1-day pond Inoculate Terrace 8 from Terrace 7 1-day pond Inoculate Terrace 8 1-day pond Drain Terrace 7 Sludge Drain Terrace 6 Supernatent Rinse Terrace 7 2-day ponds Rinse Terrace 7 1-day pond Inoculate Terrace 7 from Terrace 6 1-day pond Inoculate Terrace 7 1-day pond Drain Terrace 6 Sludge Drain Terrace 5 Supernatent Rinse Terrace 6 2-day ponds Rinse Terrace 6 1-day pond Inoculate Terrace 6 from Terrace 5 1-day pond Inoculate Terrace 6 1-day pond Drain Terrace 5 Sludge Drain Terrace 4 Supernatent Rinse Terrace 5 2-day ponds Rinse Terrace 5 1-day pond Inoculate Terrace 5 from Terrace 4 1-day pond Inoculate Terrace 5 1-day pond Drain Terrace 4 Sludge Drain Terrace 3 Supernatent Rinse Terrace 4 2-day ponds Rinse Terrace 4 1-day pond Inoculate Terrace 4 from Terrace 3 1-day pond Inoculate Terrace 4 1-day pond Drain Terrace 3 Sludge

Duration (hr) Start Time End Time 1.70 18.00 19.70 0.22 19.70 19.91 1.15 19.91 21.06 0.30 19.91 20.21 0.99 20.21 21.21 0.30 21.06 21.36 1.15 21.36 22.51 0.30 21.36 21.66 0.30 21.36 21.66 0.99 21.66 22.66 1.50 21.66 23.16 0.30 22.51 22.81 1.15 22.81 23.96 0.30 22.81 23.11 0.30 22.81 23.11 0.99 23.11 0.11 1.50 23.11 0.61 0.30 23.96 0.26 1.15 0.26 1.41 0.30 0.26 0.56 0.30 0.26 0.56 0.99 0.56 1.56 1.50 0.56 2.06 0.30 1.41 1.71 1.15 1.71 2.86 0.30 1.71 2.01 0.30 1.71 2.01 0.99 2.01 3.01 1.50 2.01 3.51 0.30 2.86 3.16 1.15 3.16 4.31 0.30 3.16 3.46 0.30 3.16 3.46 0.99 3.46 4.46 1.50 3.46 4.96 0.30 4.31 4.61 1.15 4.61 5.76 0.30 4.61 4.91 0.30 4.61 4.91 0.99 4.91 5.91 1.50 4.91 6.41 0.30 5.76 6.06

21

Rinse Terrace 3 2-day ponds and 1-day pond Fill Terrace 3 New Seawater Inoculate Terrace 3 from Upper 1-day pond Inoculate Terrace 3 1-day pond Rinse Terrace 2 1-day pond Inoculate Terrace 2 1-day pond Fill Upper Terrace 2 1-day pond New Seawater Clean PBR's Refill PBR's Add PBR Nutrients Refill Reservoir Secondary Settling

0.70 1.00 0.99 1.50 0.50 1.50 0.90 1.00 1.50 1.50 18.00 4.00

6.06 6.76 6.76 6.76 7.76 8.26 8.26 4.96 5.96 5.96 7.46 3.16

6.76 7.76 7.76 8.26 8.26 9.76 9.16 5.96 7.46 7.46 1.46 7.16

Salinity Due to evaporation (2.8% per day in all growth volumes), the salinity of the culture medium in each phase of the facility is as follows: Table B-3. Salinity progression in facility terraces.

Seawater Reservoir PBR 1-Day Pond Terrace #3 2-Day Pond Terrace #4 2-Day Pond Terrace #5 2-Day Pond Terrace #6 2-Day Pond Terrace #7 2-Day Pond Terrace #8 2-Day Pond Terrace #9 2-Day Pond Terrace #10 2-Day Pond

Initial Salinity (g/L) 33.00 33.00 34.19 33.53 34.63 35.46 36.09 36.57 36.93 37.20 38.04

Final Salinity (g/L) 33.00 35.47 35.17 34.45 35.55 36.38 37.01 37.49 37.85 38.12 38.97

22

C. Appendix C: Process Flow Diagrams and Processing Step Descriptions Table C-1. Case descriptions.

Data based directly on experimental measurements are identified in bold font. Data based on processes that were experimentally tested with biomass produced during this project are identified in italic; those data are modeled, rather than based on direct measurements due to insufficient data. The remainder of the data is modeled based on literature reports and technical specifications. Case 1

Case 2

Case 3

Case 4

Case 5

Grid

Grid

Grid

Grid

Grid

Staurosira sp.

Staurosira sp.

Staurosira sp.

Desmodesmus sp.

Desmodesmus sp.

Facility Productivity (g DW/m2-d)

19

19

33

24

24

Carbon Input (MT/day)

8.6

8.6

14.9

13.5

13.5

Nitrogen Input (MT/day)

0.6

0.6

1.4

1.4

1.4

Phosphorus Input (MT/day)

0.1

0.0

0.1

0.1

0.1

Silicon Input (MT/day)

0.2

0.2

0.4

None

None

DW Concentration at Harvest (g/L)

0.359

0.359

0.618

0.445

0.445

AFDW Concentration at Harvest (g/L)

0.246

0.246

0.424

0.433

0.433

Lipid Fraction (g lipid/g DW)

0.312

0.312

0.248

0.369

0.369

Total Biomass Output (MT/day)

17.7

17.7

30.5

21.9

21.9

24

16

16

16

16

PBR Circulation Energy (MJ/d)

12,847

12,847

12,847

12,847

12,847

Pond Circulation Energy (MJ/d)

125,917

33,578

33,578

33,578

33,578

Pond Construction/Cost ($/m2)

30

13

13

13

13

Electricity Source Cultivation Algal Species

Pond Circulation Time (hrs/d)

Harvesting

23

Step 1

In-pond settling

In-pond settling

In-pond settling

In-pond settling

In-pond settling

Step 2

Secondary settling

Secondary settling

Secondary settling

Secondary settling

Secondary settling

Step 3

Centrifuge

Filter Press

Filter Press

Filter Press

Filter Press

Step 4

Ring Dryer

None

None

None

None

Overall Efficiency (mass out/mass in)

93%

92%

92%

92%

92%

Total Biomass Yield (MT/day)

16.5

16.3

28.1

20.2

20.2

Percent Solids (%)

90%

20%

20%

20%

20%

Hexane extraction

Valicor, CHG+CHP

Valicor, CHG+CHP

Valicor, CHG+CHP

Valicor, Fermentation

Lipid Recovery (% Lipids Recovered)

50%

90%

90%

90%

90%

Lipid Yield (MT/day)

2.6

4.6

6.3

6.7

6.7

Dry Animal Feed Yield (MT/day)

13.9

9.9

18.6

10.2

10.2

Ethanol Yield (MT/day)

0.0

0.0

0.0

0.0

1.5

Case 6

Case 7

Case 8

Case 9

Case 10

Wind Power

Grid

Grid

Wind Power

Wind Power

Desmodesmus sp.

Desmodesmus sp.

Desmodesmus sp.

Desmodesmus sp.

Desmodesmus sp.

24

24

24

24

24

Carbon Input (MT/day)

13.5

13.5

13.5

13.5

13.5

Nitrogen Input (MT/day)

1.4

1.4

1.4

1.4

1.4

Phosphorus Input (MT/day)

0.1

0.0

0.1

0.0

0.1

None

None

None

None

None

Extraction Method

Electricity Source Cultivation Algal Species Facility Productivity (g DW/m2-d)

Silicon Input (MT/day)

24


0.445

0.445

0.445

0.445

0.445

AFDW Concentration at Harvest (g/L)

0.433

0.433

0.433

0.433

0.433

Lipid Fraction (g lipid/g AFDW)

0.369

0.369

0.369

0.369

0.369

Total Biomass Output (MT/day)

21.9

21.9

21.9

21.9

21.9

16

16

16

12

12

PBR Circulation Energy (MJ/d)

12,847

12,847

12,847

12,847

12,847

Pond Circulation Energy (MJ/d)

33,578

33,578

33,578

25,183

25,183

Pond Construction/Cost ($/m2)

13

13

13

3

3

Step 1

In-pond settling

In-pond settling

In-pond settling

In-pond settling

In-pond settling

Step 2

Secondary settling

Secondary settling

Secondary settling

Secondary settling

Secondary settling

Step 3

Filter Press

Filter Press

Filter Press

Filter Press

Filter Press

Step 4

None

None

None

None

None

Overall Efficiency (mass out/mass in)

92%

92%

92%

92%

92%

Total Biomass Yield (MT/day)

20.2

20.2

20.2

20.2

20.2

Percent Solids (%)

20%

20%

20%

20%

20%

Valicor, CHG+CHP

HTL, CHG+CHP

OpenAlgae

HTL, CHG+CHP

OpenAlgae

90%

50% of Biomass

75%

50% of Biomass

75%

Lipid Yield (MT/day)

6.7

10.1

5.6

10.1

5.6

Dry Animal Feed Yield (MT/day)

10.2

0.0

14.6

0.0

14.6

Ethanol Yield (MT/day)

0.0

0.0

0.0

0.0

0.0

Pond Circulation Time (hrs/d)

Harvesting

Extraction Method Lipid Recovery (% Lipids Recovered)

25

Harvesting and Dewatering: In-pond settling and secondary settling The settling characteristics of the two species used in this study, determined experimentally during strain selection, were exploited to harvest tons of dry biomass in hundreds of production runs using in-pond settling as described by Huntley et al.[1] Roughly 0.5 hours before harvesting, circulation is stopped to allow the algae to settle for 1 hour and the supernatant is drained, yielding a 95% in-pond harvesting efficiency (on a mass basis) and a sludge algal concentration of 10 g of algae/L. The sludge is delivered to secondary settling reservoirs located on the lowest terrace in the facility in which thickening is increased to 20 g of algae/L over a period of 4 hours with a 99% harvesting efficiency (on a mass basis). Thus, the total settling efficiency is 94% with minimal energy input. The sludge produced after secondary settling is pumped to the tertiary harvesting process over a 24 hour period (as processing operates in a continuous mode), requiring 26 J per L of sludge (calculated from Equation 1 with the following parameters: 5 corners, 1.5 m of elevation increase, 50 m of 0.2 m diameter pipe, with roughly 0.01 m3/s in all cases and a 60% pump efficiency). The total sludge volume following secondary settling ranges from 800 – 1,400 m3/day. Centrifugation Centrifugation is only used in Case 1 and there are 10 centrifuges (based on Westfalia clarifier 300-96-777 that was constructed at the KDF) required to dewater the sludge (830 m3/day) with the following conditions: 3,750 L of sludge throughput per hour per centrifuge, 37 kW motor in each centrifuge operated 24 hours/day, 99% harvesting efficiency (on a mass basis), yielding a dense sludge at 200 g of algae/L.

26

Ring Dryer In Case 1 only, the thickened sludge is dried using a propane ring dryer similar to the unit that was constructed at the KDF facility (based on Dedert ring dryers [6]). The dryer draws 255 kW and consumes 0.05 kg of LPG per kg of sludge. Thus, the total daily consumption of electricity and LPG for the ring dryer in Case 1 is 22,000 MJ (0.27 MJ/kg of sludge) and 4,100 kg. The dried algal biomass is 90% solids. Filter Press The filter press modeled in Cases 2-10 is based on the KM-TEC K1 filter press [7] that consumes 1.08 MJ of electricity per m3 of sludge processed and yields a thickened product at 200 g/L (20% solids). The filter press recovers 98% of the input algal biomass. Extraction/Conversion: Hexane Extraction (POS) Case 1 implements direct solvent extraction based on the POS hexane extraction process that was experimentally validated using tons of biomass from the KDF facility. The extraction process recovers 50% of the lipids in the biomass as biocrude with a 1% solvent loss (0.009 g of solvent loss per g of algae) and 11.8 kg of phosphoric acid consumed per day (0.005 g per g of biocrude recovered). There are 1,200 kg of LPG and 1,300 MJ of electricity consumed each day (0.07 g of LPG and 80 J of electricity per g of algae). Valicor Thermochemical Conversion Cases 2 – 6 use the Valicor conversion process that yields biocrude, dried biomass for animal feed, and an aqueous phase.[8] The lipid recovery efficiency is 90%. The conversion consumes 2.5 mg of hexane, 26 mg of LPG, 1.1 mg of phosphoric acid, 15 mg of a proprietary chemical, and 208 J of electricity per g of algae. Mass and element flows are described in Table C-2 and Table C-3.

27

Hydrothermal Liquefaction The HTL process used in Cases 7 and 9 is based on the processes developed at Pacific Northwest National Lab (PNNL).[9] The process requires 411 J of heat, which is provided by onsite combined heat and power (CHP, described below), and 84 J of electricity per g of algae processed. It is assumed that 50% of the algal biomass is converted into biocrude and the residual aqueous phase is used for catalytic hydrothermal gasification (CHG). OpenAlgae Lipid Extraction The OpenAlgae lipid extraction process is modeled for Cases 8 and 10, recovering 75% of the algal lipids as biocrude.[10, 11] The process requires 7.6 mg of LPG (for solvent distillation and biomass drying) and 311 J of electricity (for lysing and extraction) per gram of algae processed, with a heptane solvent loss of 0.03 mg per g of algae processed. The residual biomass is 95% solids. Mass and element flows are described in Table C-2 and Table C-3. Catalytic Hydrothermal Gasification CHG is based on Genifuel’s process that converts the carbon in the aqueous phase yields of the Valicor process and HTL into methane. The aqueous phase is pumped through CHG with an electricity requirement determined from Equation 8 with a total pressure drop of 20.5 Mpa and a pump efficiency of 60%. For each g of carbon supplied to CHG, 0.53 g of methane are produced and 10% of the methane product is consumed to operate the CHG process. There is a small amount of ammonia produced, but the overall nitrogen and phosphorus recovery is 99.2% and 100%, respectively – these nutrients are recycled to the growth volumes. Combined Heat and Power The methane produced by CHG is used to generate heat and power in CHP with a 35% electricity generation efficiency and a 33% heat recovery efficiency.[12] The heat exchanger

28

area (with a LMTD of 108 °C and a heat transfer coefficient of 65 W/m2-C) required for CHP varies between 7 and 17 m2 depending on the amount of heat generated in each case. Fermentation Fermentation is modeled in Case 5 as an alternative to producing methane from the aqueous phase yield of the Valicor and HTL processes with an ethanol yield of 1.27 kg per kg of carbon supplied to the fermenter. The electricity and heat requirements are 0.53 MJ and 6.52 MJ (from LPG) per kg of ethanol produced, respectively. Additionally, fermentation consumes 9.8 g of sulfuric acid, 20.7 g of ammonium sulfate, and 16.5 g of soda ash per kg of ethanol produced. [13]

Mass and Nutrient Balances Table C-2. Mass and nutrient balances for Cases 1-5. Case 1

Case 2

Case 3

Case 4

Case 5

0.25

0.25

0.42

0.43

0.43

Lipid Content (g/g AFDW)

0.46

0.46

0.36

0.38

0.38

Protein & NA Content (g/g AFDW)

0.31

0.31

0.41

0.40

0.40

Carbohydrate Content (g/g AFDW)

0.23

0.23

0.21

0.21

0.21

Chlorophyll Content (g/g AFDW)

0.01

0.01

0.02

0.00

0.00

Ash Content (g/g AFDW)

0.00

0.00

0.00

0.00

0.00

Carbon Content (g/g AFDW)

0.56

0.56

0.56

0.50

0.50

Nitrogen Content (g/g AFDW)

0.05

0.05

0.07

0.06

0.06

Phosphorus Content (g/g AFDW)

0.00

0.00

0.01

0.01

0.01

Silicon Content (g/g AFDW)

0.00

0.00

0.00

0.00

0.00

Ash Content at Harvest (g/L)

0.11

0.11

0.19

0.01

0.01


0.36

0.36

0.62

0.44

0.44

DW/AFDW Ratio (-)

1.46

1.46

1.46

1.03

1.03

Carbon Content (g/g DW)

0.38

0.38

0.39

0.48

0.48

Nitrogen Content (g/g DW)

0.0335

0.0335

0.0453

0.0630

0.0630

Phosphorus Content (g/g DW)

0.0031

0.0031

0.0041

0.0057

0.0057

Silicon Content (g/g DW)

0.0091

0.0091

0.0122

0.0000

0.0000

AFDW Concentration at Harvest (g/L) AFDW Biomass Composition

29

Case 1

Case 2

Case 3

Case 4

Case 5

Lipid Content (g/g DW)

0.31

0.31

0.25

0.37

0.37

Carbon Content in Lipid (g/g lipid)

0.70

0.70

0.70

0.60

0.60

Nitrogen Content in Lipid (g/g lipid) Phosphorus Content in Lipid (g/g lipid)

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

Silicon Content in Lipid (g/g lipid)

0.00

0.00

0.00

0.00

0.00

Protein (& NA) Content (g/g DW) Carbon Content in Protein (g/g protein) Nitrogen Content in Protein (g/g protein) Phosphorus Content in Protein (g/g protein) Silicon Content in Protein (g/g protein)

0.21

0.21

0.28

0.39

0.39

0.53

0.53

0.53

0.45

0.45

0.16

0.16

0.16

0.16

0.16

0.01

0.01

0.01

0.01

0.01

0.00

0.00

0.00

0.00

0.00

Carbohydrate Content (g/g DW)

0.16

0.16

0.14

0.21

0.21

Carbon Content in Carb (g/g carb)

0.40

0.40

0.40

0.34

0.34

Nitrogen Content in Carb (g/g carb)

0.00

0.00

0.00

0.00

0.00

Phosphorus Content in Carb (g/g carb)

0.00

0.00

0.00

0.00

0.00

Silicon Content in Carb (g/g carb)

0.00

0.00

0.00

0.00

0.00

Chlorophyll Content (g/g DW)

0.01

0.01

0.01

0.00

0.00

Carbon Content in Chl (g/g Chl)

0.73

0.73

0.73

0.62

0.62

Nitrogen Content in Chl (g/g Chl)

0.06

0.06

0.06

0.06

0.06

Phosphorus Content in Chl (g/g Chl)

0.00

0.00

0.00

0.00

0.00

Silicon Content in Chl (g/g Chl)

0.00

0.00

0.00

0.00

0.00

Ash Content (g/g DW)

0.32

0.32

0.31

0.0270

0.03

Carbon Content in Ash (g/g Ash)

0.00

0.00

0.00

0.00

0.00

Nitrogen Content in Ash (g/g Ash)

0.00

0.00

0.00

0.00

0.00

Phosphorus Content in Ash (g/g Ash)

0.00

0.00

0.00

0.00

0.00

Silicon Content in Ash (g/g Ash)

0.03

0.03

0.04

0.00

0.00

8,626.62

8,626.62

14,886.71

13,479.07

13,479.07

Nitrogen Added (kg/day)

591.66

591.66

1,379.66

1,380.26

1,380.26

Phosphorus Added (kg/day)

53.95

53.95

125.75

125.80

125.80

Silicon Added (kg/day)

160.05

160.05

371.86

0.00

0.00

1,828.84

1,828.84

3,155.98

2,857.56

2,857.56

Nitrogen Loss (kg/day)

0.00

0.00

0.00

0.00

0.00

Phosphorus Loss (kg/day)

0.00

0.00

0.00

0.00

0.00

Silicon Lost (kg/day)

0.00

0.00

0.00

0.00

0.00

Cultivation Carbon Added (kg/day)

Carbon Loss from PBRs & Ponds (kg/day)

30

Case 1

Case 2

Case 3

Case 4

Case 5

DW Biomass Produced (kg/day)

17,677.82

17,677.82

30,467.55

21,925.96

21,925.96

Lipid Produced (kg/day)

5,506.83

5,506.83

7,556.60

8,085.16

8,085.16

Protein & NA Produced (kg/day)

3,691.39

3,691.39

8,621.20

8,618.48

8,618.48

Carbohydrate Produced (kg/day)

2,759.47

2,759.47

4,383.66

4,543.90

4,543.90

Nucleic Acid Producted (kg/day)

145.24

145.24

333.99

64.00

64.00

Ash Produced (kg/day)

5,574.90

5,574.90

9,592.97

593.08

593.08

Carbon in Biomass Yield (kg/day)

6,797.78

6,797.78

11,730.73

10,621.51

10,621.51

Nitrogen in Biomass Yield (kg/day)

591.66

591.66

1,379.66

1,380.26

1,380.26

Phosphorus in Biomass Yield (kg/day)

53.95

53.95

125.75

125.80

125.80

Silicon in Biomass Yield (kg/day)

160.05

160.05

371.86

0.00

0.00

0.95

0.95

0.95

0.95

0.95

883.89

883.89

1,523.38

1,096.30

1,096.30

0.99

0.99

0.99

0.99

0.99

167.94

167.94

289.44

208.30

208.30

0.99

0.98

0.98

0.98

0.98

166.26

332.52

573.09

412.43

412.43

1.00

n/a

n/a

n/a

n/a

0.00

0.00

0.00

0.00

0.00

16,459.73

16,293.47

28,081.64

20,208.94

20,208.94

0.93

0.92

0.92

0.92

0.92


5,127.38

5,075.59

6,964.84

7,452.01

7,452.01

Protein& NA Produced (kg/day)

3,437.04

3,402.32

7,946.08

7,943.57

7,943.57


2,569.33

2,543.37

4,040.38

4,188.07

4,188.07


135.23

133.86

307.84

58.99

58.99

Ash Produced

5,190.76

5,138.33

8,841.74

546.64

546.64


6,329.38

6,265.44

10,812.09

9,789.74

9,789.74


550.89

545.33

1,271.62

1,272.17

1,272.17


50.23

49.73

115.90

115.95

115.95

Silicon in Biomass Yield (kg/day)

149.03

147.52

342.74

0.00

0.00

Harvesting Primary Harvesting Efficiency Biomass Lost in Primary Supernatent (kg/day) Secondary Harvesting Efficiency Biomass Lost in Secondary Supernatent (kg/day) Tertiary Harvesting Efficiency Biomass Lost in Tertiary Supernatent (kg/day) Quaternary Harvesting Efficiency Biomass Lost in Quarternary Supernatent (kg/day) Biomass Yield after Harvesting (kg/day) Overall harvesting Efficiency (kg/day)

Separations Lipid Recovery Efficiency

0.50

0.90

0.90

0.90

0.90

Biocrude Yield (kg/day)

2,563.69

4,568.03

6,268.36

6,706.81

6,706.81

Lipid in Biocrude (kg/day)

2,563.69

4,568.03

6,268.36

6,706.81

6,706.81

Protein & NA in Biocrude (kg/day)

0.00

0.00

0.00

0.00

0.00

Carbohydrate in Biocrude (kg/day)

0.00

0.00

0.00

0.00

0.00

31

Case 1

Case 2

Case 3

Case 4

Case 5

Nucleic Acid in Biocrude (kg/day)

0.00

0.00

0.00

0.00

0.00

Ash in Biocude (kg/day)

0.00

0.00

0.00

0.00

0.00

Biomass in Biocrude (kg/day)

2,563.69

4,568.03

6,268.36

6,706.81

6,706.81

Carbon in Biocrude (kg/day)

1,794.58

3,197.62

4,387.85

3,997.26

3,997.26

Nitrogen in Biocrude (kg/day)

0.00

0.00

0.00

0.00

0.00

Phosphorus in Biocrude (kg/day)

0.00

0.00

0.00

0.00

0.00

Silicon in Biocrude (kg/day)

0.00

0.00

0.00

0.00

0.00

Lipid in Biomass Yield (kg/day) Protein & NA in Biomass Yield (kg/day) Carbohydrate in Biomass Yield (kg/day) Nucleic Acids in Biomass Yield (kg/day)

2,563.69

507.56

696.48

745.20

745.20

3,437.04

3,062.09

7,151.47

7,149.21

7,149.21

2,569.33

1,017.35

1,616.15

1,675.23

1,675.23

135.23

133.86

307.84

58.99

58.99

Ash in Biomass Yield (kg/day)

5,190.76

5,138.33

8,841.74

546.64

546.64

Biomass Yield (kg/day)

13,896.04

9,859.18

18,613.68

10,175.26

10,175.26


4,742.34

2,482.54

5,148.28

4,283.41

4,283.41


558.27

498.20

1,163.24

1,147.52

1,147.52


50.45

44.94

104.97

104.93

104.93

Silicon in Biomass (kg/day)

147.94

146.44

344.83

0.00

0.00

0.00

0.00

0.00

0.00

Lipid in AP Yield (kg/day) Protein in AP Yield (kg/day)

340.23

794.61

794.36

794.36

Carbohydrate in AP Yield (kg/day)

1,526.02

2,424.23

2,512.84

2,512.84

Nucleic Acids in AP Yield (kg/day)

0.00

0.00

0.00

0.00

Ash in AP Yield (kg/day)

0.00

0.00

0.00

0.00

DW in AP Yield (kg/day)

1,866.26

3,218.83

3,307.20

3,307.20

Carbon in AP Yield (kg/day)

790.73

1,390.83

1,215.93

1,215.93

Nitrogen in AP Yield (kg/day)

54.44

127.14

127.10

127.10

Phosphorus in AP Yield (kg/day)

4.99

11.66

11.66

11.66

Silicon in AP Yield (kg/day)

0.00

0.00

0.00

0.00

Biogas from CHG Yield (kg/day) Carbon in Methane in Biogas Yield (kg/day)

377.18

663.43

580.00

314.32

552.86

483.33

Total Carbon in Biogas (kg/day)

790.73

1,390.83

1,215.93

Nitrogen Lost as NH3 (kg/day)

0.44

1.02

1.02

Nitrogen in Biogas Yield (kg/day)

0.00

0.00

0.00

Phosphorus in Biogas Yield (kg/day)

0.00

0.00

0.00

Silicon in Biogas Yield (kg/day) Nitrogen in CHG Recycle Yield (kg/day)

0.00

0.00

0.00

54.00

126.12

126.08

32

Case 1 Phosphorus in CHG Recycle Yield (kg/day) Silicon in CHG Recycle Yield (kg/day) Carbon in CHP Recycle Yield (kg/day) Carbon Emissions from CHP (kg C/day)

Case 2

Case 3

Case 4

4.99

11.66

11.66

0.00

0.00

0.00

0.00

0.00

0.00

790.73

1,390.83

1,215.93

Ethanol Yield (kg/day)

Case 5

1,544.23

Carbon in Ethanol Yield (kg/day)

805.68

Waste Carbon (kg/day)

410.24

Waste N (kg/day)

127.10

Waste P (kg/day)

11.66

Waste Si

0.00

Table C-3. Mass and nutrient balances for Cases 6-10. Case 6

Case 7

Case 8

Case 9

Case 10

0.43

0.43

0.43

0.43

0.43

Lipid Content (g/g AFDW)

0.38

0.38

0.38

0.38

0.38

Protein & NA Content (g/g AFDW)

0.40

0.40

0.40

0.40

0.40

Carbohydrate Content (g/g AFDW)

0.21

0.21

0.21

0.21

0.21

Chlorophyll Content (g/g AFDW)

0.00

0.00

0.00

0.00

0.00

Ash Content (g/g AFDW)

0.00

0.00

0.00

0.00

0.00

Carbon Content (g/g AFDW)

0.50

0.50

0.50

0.50

0.50

Nitrogen Content (g/g AFDW)

0.06

0.06

0.06

0.06

0.06

Phosphorus Content (g/g AFDW)

0.01

0.01

0.01

0.01

0.01

Silicon Content (g/g AFDW)

0.00

0.00

0.00

0.00

0.00

Ash Content at Harvest (g/L)

0.01

0.01

0.01

0.01

0.01


0.44

0.44

0.44

0.44

0.44

DW/AFDW Ratio (-)

1.03

1.03

1.03

1.03

1.03

Carbon Content (g/g DW)

0.48

0.48

0.48

0.48

0.48

Nitrogen Content (g/g DW)

0.0630

0.0630

0.0630

0.0630

0.0630

Phosphorus Content (g/g DW)

0.0057

0.0057

0.0057

0.0057

0.0057

Silicon Content (g/g DW)

0.0000

0.0000

0.0000

0.0000

0.0000

Lipid Content (g/g DW)

0.37

0.37

0.37

0.37

0.37

Carbon Content in Lipid (g/g lipid)

0.60

0.60

0.60

0.60

0.60

AFDW Concentration at Harvest (g/L) AFDW Biomass Composition

33

Case 6

Case 7

Case 8

Case 9

Case 10

Nitrogen Content in Lipid (g/g lipid) Phosphorus Content in Lipid (g/g lipid)

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

Silicon Content in Lipid (g/g lipid)

0.00

0.00

0.00

0.00

0.00

Protein (& NA) Content (g/g DW) Carbon Content in Protein (g/g protein) Nitrogen Content in Protein (g/g protein) Phosphorus Content in Protein (g/g protein) Silicon Content in Protein (g/g protein)

0.39

0.39

0.39

0.39

0.39

0.45

0.45

0.45

0.45

0.45

0.16

0.16

0.16

0.16

0.16

0.01

0.01

0.01

0.01

0.01

0.00

0.00

0.00

0.00

0.00

Carbohydrate Content (g/g DW)

0.21

0.21

0.21

0.21

0.21

Carbon Content in Carb (g/g carb)

0.34

0.34

0.34

0.34

0.34

Nitrogen Content in Carb (g/g carb) Phosphorus Content in Carb (g/g carb)

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

Silicon Content in Carb (g/g carb)

0.00

0.00

0.00

0.00

0.00

Chlorophyll Content (g/g DW)

0.00

0.00

0.00

0.00

0.00

Carbon Content in Chl (g/g Chl)

0.62

0.62

0.62

0.62

0.62

Nitrogen Content in Chl (g/g Chl)

0.06

0.06

0.06

0.06

0.06

Phosphorus Content in Chl (g/g Chl)

0.00

0.00

0.00

0.00

0.00

Silicon Content in Chl (g/g Chl)

0.00

0.00

0.00

0.00

0.00

Ash Content (g/g DW)

0.03

0.03

0.03

0.03

0.03

Carbon Content in Ash (g/g Ash)

0.00

0.00

0.00

0.00

0.00

Nitrogen Content in Ash (g/g Ash)

0.00

0.00

0.00

0.00

0.00

Phosphorus Content in Ash (g/g Ash)

0.00

0.00

0.00

0.00

0.00

Silicon Content in Ash (g/g Ash)

0.00

0.00

0.00

0.00

0.00

Carbon Added (kg/day)

13,479.07

13,479.07

13,479.07

13,479.07

13,479.07

Nitrogen Added (kg/day)

1,380.26

1,380.26

1,380.26

1,380.26

1,380.26

125.80

125.80

125.80

125.80

125.80

0.00

0.00

0.00

0.00

0.00

Cultivation

Phosphorus Added (kg/day) Silicon Added (kg/day) Carbon Loss from PBRs & Ponds (kg/day)

2,857.56

2,857.56

2,857.56

2,857.56

2,857.56

Nitrogen Loss (kg/day)

0.00

0.00

0.00

0.00

0.00

Phosphorus Loss (kg/day)

0.00

0.00

0.00

0.00

0.00

Silicon Lost (kg/day)

0.00

0.00

0.00

0.00

0.00

DW Biomass Produced (kg/day)

21,925.96

21,925.96

21,925.96

21,925.96

21,925.96


8,085.16

8,085.16

8,085.16

8,085.16

8,085.16

34

Case 6

Case 7

Case 8

Case 9

Case 10

Protein & NA Produced (kg/day)

8,618.48

8,618.48

8,618.48

8,618.48

8,618.48


4,543.90

4,543.90

4,543.90

4,543.90

4,543.90


64.00

64.00

64.00

64.00

64.00

Ash Produced (kg/day)

593.08

593.08

593.08

593.08

593.08


10,621.51

10,621.51

10,621.51

10,621.51

10,621.51

Nitrogen in Biomass Yield (kg/day) Phosphorus in Biomass Yield (kg/day(

1,380.26

1,380.26

1,380.26

1,380.26

1,380.26

125.80

125.80

125.80

125.80

125.80

0.00

0.00

0.00

0.00

0.00

0.95

0.95

0.95

0.95

0.95

1,096.30

1,096.30

1,096.30

1,096.30

1,096.30

0.99

0.99

0.99

0.99

0.99

208.30

208.30

208.30

208.30

208.30

0.98

0.98

0.98

0.98

0.98

412.43

412.43

412.43

412.43

412.43

n/a

n/a

n/a

n/a

n/a

0.00

0.00

0.00

0.00

0.00

20,208.94

20,208.94

20,208.94

20,208.94

20,208.94

0.92

0.92

0.92

0.92

0.92


7,452.01

7,452.01

7,452.01

7,452.01

7,452.01

Protein& NA Produced (kg/day)

7,943.57

7,943.57

7,943.57

7,943.57

7,943.57


4,188.07

4,188.07

4,188.07

4,188.07

4,188.07


58.99

58.99

58.99

58.99

58.99

Ash Produced

546.64

546.64

546.64

546.64

546.64


9,789.74

9,789.74

9,789.74

9,789.74

9,789.74

Nitrogen in Biomass Yield (kg/day) Phosphorus in Biomass Yield (kg/day)

1,272.17

1,272.17

1,272.17

1,272.17

1,272.17

115.95

115.95

115.95

115.95

115.95

0.00

0.00

0.00

0.00

0.00

0.90

n/a

0.75

n/a

0.75

Biocrude Yield (kg/day)

6,706.81

10,104.47

5,589.01

10,104.47

5,589.01

Lipid in Biocrude (kg/day)

6,706.81

5,589.01

5,589.01

Protein & NA in Biocrude (kg/day)

0.00

0.00

0.00

Carbohydrate in Biocrude (kg/day)

0.00

0.00

0.00

Silicon in Biomass Yield (kg/day) Harvesting Primary Harvesting Efficiency Biomass Lost in Primary Supernatent (kg/day) Secondary Harvesting Efficiency Biomass Lost in Secondary Supernatent (kg/day) Tertiary Harvesting Efficiency Biomass Lost in Tertiary Supernatent (kg/day) Quaternary Harvesting Efficiency Biomass Lost in Quarternary Supernatent (kg/day) Biomass Yield after Harvesting (kg/day) Overall harvesting Efficiency (kg/day)

Silicon in Biomass Yield (kg/day) Separations Lipid Recovery Efficiency

35

Case 6

Case 7

Case 8

Case 9

Case 10

Nucleic Acid in Biocrude (kg/day)

0.00

0.00

0.00

Ash in Biocude (kg/day)

0.00

0.00

0.00

Biomass in Biocrude (kg/day)

6,706.81

10,104.47

5,589.01

10,104.47

5,589.01

Carbon in Biocrude (kg/day)

3,997.26

7,780.44

3,331.05

7,780.44

3,331.05

Nitrogen in Biocrude (kg/day)

0.00

0.00

0.00

0.00

0.00

Phosphorus in Biocrude (kg/day)

0.00

0.00

0.00

0.00

0.00

Silicon in Biocrude (kg/day)

0.00

0.00

0.00

0.00

0.00

Lipid in Biomass Yield (kg/day) Protein & NA in Biomass Yield (kg/day) Carbohydrate in Biomass Yield (kg/day) Nucleic Acids in Biomass Yield (kg/day) Ash in Biomass Yield (kg/day)

745.20

1,863.00

1,863.00

7,149.21

7,943.57

7,943.57

1,675.23

4,188.07

4,188.07

58.99

58.99

58.99

546.64

546.64

546.64

Biomass Yield (kg/day)

10,175.26

0.00

14,600.26

0.00

14,600.26


4,283.41

6,165.55

6,165.55

Nitrogen in Biomass Yield (kg/day) Phosphorus in Biomass Yield (kg/day)

1,147.52

1,274.61

1,274.61

104.93

116.59

116.59

Silicon in Biomass (kg/day)

0.00

0.00

0.00

Lipid in AP Yield (kg/day)

0.00

0.00

0.00

794.36

0.00

0.00

Carbohydrate in AP Yield (kg/day)

2,512.84

0.00

0.00

Nucleic Acids in AP Yield (kg/day)

0.00

0.00

0.00

Ash in AP Yield (kg/day)

0.00

0.00

0.00

DW in AP Yield (kg/day)

3,307.20

10,104.47

0.00

10,104.47

0.00

Carbon in AP Yield (kg/day)

1,215.93

2,009.30

0.00

2,009.30

0.00

Nitrogen in AP Yield (kg/day)

127.10

1,272.17

0.00

1,272.17

0.00

Phosphorus in AP Yield (kg/day)

11.66

115.95

0.00

115.95

0.00

Silicon in AP Yield (kg/day)

0.00

0.00

0.00

0.00

0.00

580.00

958.44

958.44

483.33

798.70

798.70

Total Carbon in Biogas (kg/day)

1,215.93

2,009.30

2,009.30

Nitrogen Lost as NH3 (kg/day)

1.02

0.00

0.00

Nitrogen in Biogas Yield (kg/day)

0.00

0.00

0.00

Phosphorus in Biogas Yield (kg/day)

0.00

0.00

0.00

Silicon in Biogas Yield (kg/day)

0.00

0.00

0.00

Nitrogen in CHG Recycle Yield

126.08

1,272.17

1,272.17

Protein in AP Yield (kg/day)

Biogas from CHG Yield (kg/day) Carbon in Methane in Biogas Yield (kg/day)

36

Case 6

Case 7

Case 8

Case 9

11.66

115.95

115.95

0.00

0.00

0.00

0.00

0.00

0.00

1,215.93

2,009.30

2,009.30

Case 10

(kg/day) Phosphorus in CHG Recycle Yield (kg/day) Silicon in CHG Recycle Yield (kg/day) Carbon in CHP Recycle Yield (kg/day) Carbon Emissions from CHP (kg C/day) Ethanol Yield (kg/day) Carbon in Ethanol Yield (kg/day) Waste Carbon (kg/day) Waste N (kg/day) Waste P (kg/day) Waste Si

37

D. Appendix D: Production Costs: Energy and Materials Table D-1. Operating energy and material inputs and outputs for Case 1 - 5.

*On-site electricity and heat are shown as credits and outputs but they are not double-counted in energy and cost balances. Inputs Cultivation Water Supply Electricity for Facility (Wells) (MJ/d) Water Supply Electricity for Facility (Pipeline) (MJ/d) PBR Airlift Circulation Electricity for Facility (MJ/d) Pond Circulation Electricity for Facility (MJ/d) Carbon Transport to Site (MJ/d) Nitrogen & Phosphorus Stock Tank Mixer (MJ/d) Silica Stock Tank Mixer (MJ/d) Carbon Dioxide Consumed for Facility (kg/d) Nitrogen Fertilizer Consumed for Facility (kg/d) Phosphorus Fertilizer Consumed for Facility (kg/d) Silicon Fertilizer Consumed for Facility (kg/d) On-site Electricity Credit (MJ/d) PBR Plastic (m2/d) Filter Cartridges (num/d) - (Pipeline) Total Cultivation Energy (MJ/d) Total Cultivation Energy (kWh/d) Total Cultivation Energy (kWh/ha-d)

Case 1 Value (X)

Case 2 Value (X)

Case 3 Value (X)

Case 4 Value (X)

Case 5 Value (X)

11,581.03 51,304.24 12,847.49 125,916.97 8,350.04 385.10 355.39 31,630.95 3,585.81 209.11 1,211.83 0.00 6.38 0.01 159,436.03 44,287.79 400.38

11,577.29 51,575.15 12,847.49 33,577.86 8,350.04 260.66 355.39 31,630.95 600.13 209.22 1,211.83 -6,600.64 6.38 0.01 60,368.09 16,768.92 150.53

11,487.02 51,027.07 12,847.49 33,577.86 14,409.42 511.75 825.70 54,584.59 1,399.25 487.55 2,815.53 -11,609.98 6.38 0.01 62,049.26 17,235.90 154.72

11,552.29 51,423.23 12,847.49 33,577.86 13,046.91 512.00 0.00 49,423.26 1,399.95 487.80 0.00 -10,149.96 6.38 0.01 61,386.60 17,051.83 153.07

11,553.86 51,432.72 12,847.49 33,577.86 13,046.91 564.08 0.00 49,423.26 1,540.49 537.63 0.00 0.00 6.38 0.01 71,590.20 19,886.17 178.51

Harvesting Pump Secondary Sludge to Centrifuge/Press (MJ/d) Centrifuge/Press Operation (MJ/d) Cooling Water Consumed (m3/d) Dryer Heat Consumption (MJ/d) Dryer Electricity Consumption (MJ/d)

21.24 29,527.76 39.90 190,370.15 22,036.33

21.24 897.80 0.00 0.00 0.00

38.13 1,547.36 0.00 0.00 0.00

26.65 1,113.55 0.00 0.00 0.00

26.65 1,113.55 0.00 0.00 0.00

38

Total Harvesting Energy (MJ/d) Total Harvesting Energy (kWh/d) Total Harvesting Energy (kWh/ha-d)

241,955.48 67,209.85 607.60

919.05 255.29 2.29

1,585.49 440.41 3.95

1,140.20 316.72 2.84

1,140.20 316.72 2.84

Extraction Extraction Electricity (MJ/d) Extraction Heat (MJ/d) Solvent Consumed (kg/d) Valicor Chemical A (kg/d) Electricity for CHG (MJ/d) Electricity for Fermentation (MJ/d) Fermentation Heat (MJ/d) Sulfuric Acid Fermentation (kg/d) Ammonium Sulfate for Fermentation (kg/d) Soda Ash for Fermentation (kg/d) Total Extraction Energy (MJ/d) Total Extraction Energy (kWh/d) Total Extraction Energy (kWh/ha-d)

1,314.90 51,185.05 146.16 0.00 0.00 0.00 0.00 0.00 0.00 0.00 52,499.95 14,583.32 131.84

3,895.30 23,761.48 40.73 244.40 2,273.70 0.00 0.00 0.00 0.00 0.00 25,885.23 7,190.34 64.55

5,345.22 31,041.78 70.20 421.22 3,916.00 0.00 0.00 0.00 0.00 0.00 33,187.75 9,218.82 82.75

5,719.10 34,605.54 50.52 303.13 2,857.50 0.00 0.00 0.00 0.00 0.00 36,961.66 10,267.13 92.17

5,719.10 40,826.01 50.52 303.13 0.00 818.44 10,068.37 15.13 32.03 25.48 57,431.93 15,953.31 143.21

Total Energy Input (MJ/d) Total Energy Input (kWh/d) Total Energy Input (kWh/ha-d)

453,891.46 126,080.96 1,139.82

87,172.37 24,214.55 217.37

96,822.50 26,895.14 241.43

99,488.46 27,635.68 248.08

130,162.33 36,156.20 324.56

Outputs Lipids (kg/d) Non-lipid Biomass (kg/d) On-site Electricity (MJ/d) On-site Heat (MJ/d) Ethanol (kg/d)

2,563.69 13,896.04 0.00 0.00 0.00

4,568.03 9,859.18 6,600.64 4,045.25 0.00

6,268.36 18,613.68 11,609.98 7,115.26 0.00

6,706.81 10,175.26 10,149.96 6,220.48 0.00

6,706.81 10,175.26 0.00 0.00 1,544.23

39

Table D-2. Operating energy and material inputs and outputs for Case 5 - 10.

*On-site electricity and heat are shown as credits and outputs but they are not double-counted in energy and cost balances. Inputs Cultivation Water Supply Electricity for Facility (Wells) (MJ/d) Water Supply Electricity for Facility (Pipeline) (MJ/d) PBR Airlift Circulation Electricity for Facility (MJ/d) Pond Circulation Electricity for Facility (MJ/d) Carbon Transport to Site (MJ/d) Nitrogen & Phosphorus Stock Tank Mixer (MJ/d) Silica Stock Tank Mixer (MJ/d) Carbon Dioxide Consumed for Facility (kg/d) Nitrogen Fertilizer Consumed for Facility (kg/d) Phosphorus Fertilizer Consumed for Facility (kg/d) Silicon Fertilizer Consumed for Facility (kg/d) On-site Electricity Credit (MJ/d) PBR Plastic (m2/d) Filter Cartridges (num/d) - (Pipeline) Total Cultivation Energy (MJ/d) Total Cultivation Energy (kWh/d) Total Cultivation Energy (kWh/ha-d) Harvesting Pump Secondary Sludge to Centrifuge/Press (MJ/d) Centrifuge/Press Operation (MJ/d) Cooling Water Consumed (m3/d) Dryer Heat Consumption (MJ/d) Dryer Electricity Consumption (MJ/d) Total Harvesting Energy (MJ/d) Total Harvesting Energy (kWh/d)

Case 6 Value (X)

Case 7 Value (X)

Case 8 Value (X)

Case 9 Value (X)

Case 10 Value (X)

11,552.29 51,423.23 12,847.49 33,577.86 13,046.91 512.00 0.00 49,423.26 1,399.95 487.80 0.00 -10,149.96 6.38 0.01 61,386.60 17,051.83 153.07

11,538.26 51,338.00 12,847.49 33,577.86 13,046.91 44.17 0.00 49,423.26 120.64 42.10 0.00 -16,772.62 6.38 0.01 54,282.08 15,078.36 135.35

11,553.86 51,432.72 12,847.49 33,577.86 13,046.91 564.08 0.00 49,423.26 1,540.49 537.63 0.00 0.00 6.38 0.01 71,590.20 19,886.17 178.51

11,572.44 51,545.67 12,847.49 25,183.39 13,046.91 44.17 0.00 49,423.26 120.64 42.10 0.00 -16,772.62 6.38 0.01 45,921.80 12,756.05 114.51

11,622.35 51,849.26 12,847.49 25,183.39 13,046.91 564.08 0.00 49,423.26 1,540.49 537.63 0.00 0.00 6.38 0.01 63,264.23 17,573.40 157.75

26.65 1,113.55 0.00 0.00 0.00 1,140.20 316.72

26.65 1,113.55 0.00 0.00 0.00 1,140.20 316.72

26.65 1,113.55 0.00 0.00 0.00 1,140.20 316.72

26.65 1,113.55 0.00 0.00 0.00 1,140.20 316.72

26.65 1,113.55 0.00 0.00 0.00 1,140.20 316.72

40

Total Harvesting Energy (kWh/ha-d)

2.84

2.84

2.84

2.84

2.84

Extraction Extraction Electricity (MJ/d) Extraction Heat (MJ/d) Solvent Consumed (kg/d) Valicor Chemical A (kg/d) Electricity for CHG (MJ/d) Electricity for Fermentation (MJ/d) Fermentation Heat (MJ/d) Sulfuric Acid Fermentation (kg/d) Ammonium Sulfate for Fermentation (kg/d) Soda Ash for Fermentation (kg/d) Total Extraction Energy (MJ/d) Total Extraction Energy (kWh/d) Total Extraction Energy (kWh/ha-d)

5,719.10 34,605.54 50.52 303.13 2,857.50 0.00 0.00 0.00 0.00 0.00 36,961.66 10,267.13 92.17

1,687.45 0.00 0.00 0.00 3,107.12 0.00 0.00 0.00 0.00 0.00 4,794.57 1,331.82 11.96

6,284.33 6,753.32 0.51 0.00 0.00 0.00 0.00 0.00 0.00 0.00 13,037.65 3,621.57 32.51

1,687.45 0.00 0.00 0.00 3,107.12 0.00 0.00 0.00 0.00 0.00 4,794.57 1,331.82 11.96

6,284.33 6,753.32 0.51 0.00 0.00 0.00 0.00 0.00 0.00 0.00 13,037.65 3,621.57 32.51

Total Energy Input (MJ/d) Total Energy Input (kWh/d) Total Energy Input (kWh/ha-d)

99,488.46 27,635.68 248.08

60,216.85 16,726.90 150.15

85,768.05 23,824.46 213.87

51,856.57 14,404.60 129.31

77,442.08 21,511.69 193.10

Outputs Lipids (kg/d) Non-lipid Biomass (kg/d) On-site Electricity (MJ/d) On-site Heat (MJ/d) Ethanol (kg/d)

6,706.81 10,175.26 10,149.96 6,220.48 0.00

10,104.47 0.00 16,772.62 10,279.22 0.00

5,589.01 14,619.93 0.00 0.00 0.00

10,104.47 0.00 16,772.62 10,279.22 0.00

5,589.01 14,619.93 0.00 0.00 0.00

41

Table D-3. Prices for energy and material inputs and outputs, as well as the energy impact factors for each input and output.

Prices were scaled by the RS Means geographic cost modifiers (Texas - 0.88, Hawaii – 1.37) to obtain location-specific prices when local prices were not available. Material Prices Ammonia DAP Silicate Cooling Water Heptane Hexane Valicor Chemical A Sulfuric Acid Ammonium Sulfate Soda Ash PBR Plastic Filters

Texas 0.79 0.71 0.33 1.06 4.62 7.65 0.50 0.30 0.15 0.30 30.00 250.00

Energy Prices Industry Electricity Price 0.06 Wind Power Price 0.07 LPG 14.77 LPG Heat 0.014 Biocrude 17.24 0.58 Animal Feed 0.60 Ethanol 0.59

Hawaii 1.22 1.10 0.51 1.65 7.19 11.90 0.78 0.47 0.23 0.46 46.70 389.20

$/kg $/kg $/kg $/kg $/kg $/kg $/kg $/kg $/kg $/kg $/m2 $/unit

Reference [14] [14] [15] [16] [16] [15, 17] Estimate [15] [15] [15] Estimate Estimate

0.31 $/kWh [18] 0.07 $/kWh [19, 20] 36.91 $/MMBtu [21] 0.035 $/MJ [21] 26.84 $/MMBtu [22] 0.91 $/L 0.93 $/kg [23] 0.93 $/L [24]

Reference: [25]

Texas Hawaii

Energy Impacts Grid Electricity

Total 3.81

Total 3.89

Texas

MJ/MJ

Hawaii

Non-Ren Non-Ren 3.46 3.69 MJ/MJ

42

Wind Power Sodium Nitrate Ammonia Monosodium Phosphate DAP Silicon Fertilizer Cooling Water Heat (Natural Gas) Hexane Heptane Biocrude Animal Feed Valicor Chem (Estimate) LPG Sulfuric Acid Ammonium Sulfate Soda Ash Ethanol PBR Plastic (Estimate) Filter (Estimate)

1.13 38.69 41.56 17.93 14.37 20.62 0.01 1.17 20.47 23.96 53.09 25.08 20.00 58 7.07 25.64 5.07 41.86 5 100

1.13 38.69 41.56 17.93 14.37 20.62 0.01 1.17 20.47 23.96 53.09 25.08 20.00 58 7.07 25.64 5.07 41.86 5 100

MJ/MJ MJ/kg MJ/kg MJ/kg MJ/kg MJ/kg MJ/kg MJ/MJ MJ/kg MJ/kg MJ/kg MJ/kg MJ/kg MJ/kg MJ/kg MJ/kg MJ/kg MJ/kg MJ/m2 MJ/unit

0.05 37.03 40.84 17.55 13.93 18.97 0.01 1.17 20.47 23.75 53.09 3.58 20.00 58 6.96 24.07 4.47 16.25 5 100

0.05 37.03 40.84 17.55 13.93 18.97 0.01 1.17 20.47 23.75 53.09 3.58 20.00 58 6.96 24.07 4.47 16.25 5 100

MJ/MJ MJ/kg MJ/kg MJ/kg MJ/kg MJ/kg MJ/kg MJ/MJ MJ/kg MJ/kg MJ/kg MJ/kg MJ/kg MJ/kg MJ/kg MJ/kg MJ/kg MJ/kg MJ/m2 MJ/unit

E. Appendix E: Labor Estimates The labor estimates are taken directly from Huntley et al. [1] and listed in Table E-1 and Table E-2. Table E-1. Labor estimates for the Texas facility. Per

Position

Function

Base ($ h-1)

Hourly Annual Fringe Total Total -1 -1 ($ h ) ($ h ) ($ yr-1)

No. FTE

Facility Total Total -1 ($000s yr ) ($000s ha-1 yr-1)

43

Operations Staff Summary Harvest/inoculate production Harvest technician Dewatering technician Operate filter press Physical plant engineer Physical plant maintenance Lab + scale-up technician Scale-up + QA/QC IT engineer Process control system Production manager Operations Total Operations Administrative Staff Franchise manager Overall administration Sales manager Sales & marketing Accounting Fiscal management Human resources Personnel Total Administration Personnel Summary Total Operations Total Administration Total Personnel

$8.00 $8.50 $16.50 $13.75 $17.75 $22.50

$2.40 $2.55 $4.95 $4.13 $5.33 $6.75

$10.40 $11.05 $21.45 $17.88 $23.08 $29.25

$21,632 $22,984 $44,616 $37,180 $47,996 $60,840

17 3 5 10 2 1 38

$368 $69 $223 $372 $96 $61 $1,188

$3.50 $0.66 $2.12 $3.54 $0.91 $0.58 $11.3

$32.00 $20.00 $15.00 $15.00

$9.60 $6.00 $4.50 $4.50

$41.60 $26.00 $19.50 $19.50

$86,528 $54,080 $40,560 $40,560

1 1 0.5 0.5 3

$87 $54 $20 $20 $181

$0.82 $0.52 $0.19 $0.19 $1.7

38 3 41

$1,188 $181 $1,370

44

Table E-2. Labor estimates for the Hawaii facility. Per Employee

Position Function Operations Staff Summary Harvest/inoculate production Harvest technician Dewatering technician Operate filter press Physical plant engineer Physical plant maintenance Lab + scale-up technician Scale-up + QA/QC IT engineer Process control system Production manager Operations Total Operations Administrative Staff Summary Franchise manager Overall administration Sales manager Sales & marketing Accounting Fiscal management Human resources Personnel Total Administration Personnel Summary Total Operations Total Administration Total Personnel

Base ($ h-1) $11.50 $12.50 $24.00 $20.00 $26.00 $32.50

Fringe ($ h-1) $3.45 $3.75 $7.20 $6.00 $7.80 $9.75

Hourly Total ($ h-1) $14.95 $16.25 $31.20 $26.00 $33.80 $42.25

Annual Total ($ yr-1)

Facility No. Total Total FTE ($000s yr-1) ($000s ha-1 yr-1)

$31,096 $33,800 $64,896 $54,080 $70,304 $87,880

17 3 5 10 2 1 38

$529 $101 $324 $541 $141 $88 $1,724

$5.03 $0.97 $3.09 $5.15 $1.34 $0.84 $16.4

$45.00 $13.50 $58.50 $121,680 $29.00 $8.70 $37.70 $78,416 $22.00 $6.60 $28.60 $59,488 $22.00 $6.60 $28.60 $59,488

1 1 0.5 0.5 3

$122 $78 $30 $30 $260

$1.16 $0.75 $0.28 $0.28 $2.5

38 3 41

$1,724 $260 $1,983

45

F. Appendix F: Capital Cost Estimates and Discounted Cash Flow The capital cost for each case was estimated using RS Means.[26] The model was built to calculate costs on a per unit basis (e.g., cost per ha or per paddlewheel) so that the same formulas are used for each case and so that revisions to the model during this study automatically updated the results. The total capital cost for each line item are listed in Table F-4. Table F-1. Capital cost unit values for all 10 cases.

The capital cost for the compressor is calculated according to 𝐶𝐶 = 102.2897+1.3604∗LOG10(P)−0.1027∗(LOG10(P))^2 ∗ (567/394) ∗ 2.75 where P is the compressor electricity it kW.[13] 2 The HTL equipment cost is 𝐶𝐶 = 2819.2 ∗ Ṁ 0.6559 where Ṁ is the slurry mass flow rate in kg/day.[9] 3 The CHG equipment cost is 𝐶𝐶 = 2654 ∗ Ṁ 0.6624 where Ṁ is the liquid input in kg/day.[9] 4 The CHP cost is 𝐶𝐶 = (1166 ∗ P + 275262) + 𝐶𝐶𝐻𝐻𝐻𝐻𝐻𝐻 where P is the power output in kW and the heat exchanger cost is 𝐶𝐶𝐻𝐻𝐻𝐻𝐻𝐻 = 102.7652+0.7282∗LOG10(A)+0.0783∗(LOG10(A))^2 ∗ (567/394) ∗ 4.66 where A is the heat exchanger area in m2.[13] 5 The cost of fermentation is 𝐶𝐶 = 27.9 ∗ 106 ∗ (Ṁ /(25 ∗ 106 ))^0.63 ∗ (391/585))/106 where Ṁ is the annual ethanol yield in gal.[13] 6 Pipe costs were estimated directly as shown in Table F-2. 1

UNIT

1

2

3

4

5

6

7

8

9

10

$/ Unit

ha ha ha ha ha ha ha ha ha ha

111 111 111 111 111 111 111 111 111 111

111 111 111 111 111 111 111 111 111 111

111 111 111 111 111 111 111 111 111 111

111 111 111 111 111 111 111 111 111 111

111 111 111 111 111 111 111 111 111 111

111 111 111 111 111 111 111 111 111 111

111 111 111 111 111 111 111 111 111 111

111 111 111 111 111 111 111 111 111 111

111 111 111 111 111 111 111 111 111 111

111 111 111 111 111 111 111 111 111 111

10,556.00 1,500.00 500.00 216.00 1,000.00 150.00 150.00 1,000.00 500.00 1,750.00

DIVISION 1 - GENERAL REQUIREMENTS DIVISION 1 TOTAL 01-041 PROJECT COORDINATION 01-050 SURVEY SUPERVISION/LAYOUT MATERIAL 01-060 REGULATORY REQUIREMENTS (PERMITS & 01-566 DEBRIS CONTROL 01-610 MATERIAL HANDLING 01-529 FIRST AID/SAFETY 01-530 BARRIERS/TEMP. FENCING 01-540 SECURITY 01-561 CONST. CLEANING 01-612 SHIPPING & TRANSPORTATION

46

DIVISION 2 - SITE WORK DIVISION 2 TOTAL 02-100 MASS GRADE (TERRACING) m3 359,109 359,109 02-212 FINISH GRADING m3 9,491 9,495 02-225 UTILITY EXC., BACKFILL, COMPACT m3 7,440 7,440 02-226 PAVEMENT EXC., BACKFILL, COMPACT (AC, m2 9,984 9,984 02-240 SOIL STABILIZATION m2 62,441 62,468 02-275 SEDIMENT CONTROL ha 111 111 02-510 ASPHALTIC PAVING m2 6,805 6,805 02-521 CURB & GUTTER m2 3,720 3,720 02-711 DRYWELLS (DEPTH) m 76 76 02-712 DRILLED WATER SUPPLY WELLS (depth) m 17 17 02-740 SEPTIC SYSTEMS ppl 41 41 02-786 OVERHEAD ELECTRIC SERVICE ha 111 111 02-787 UNDERGROUND ELECTRIC SERVICE ha 111 111 02-810 IRRIGATION SYSTEMS ha 111 111 02-830 FENCES & GATES m 4,638 4,638 02-900 LANDSCAPING ha 111 111

359,109 9,486 7,440 9,984 62,408 111 6,805 3,720 76 17 41 111 111 111 4,638 111

359,109 9,487 7,440 9,984 62,416 111 6,805 3,720 76 17 41 111 111 111 4,638 111

359,109 9,486 7,440 9,984 62,405 111 6,805 3,720 76 17 41 111 111 111 4,638 111

359,109 9,487 7,440 9,984 62,416 111 6,805 3,720 76 17 41 111 111 111 4,638 111

359,109 9,503 7,440 9,984 62,518 111 6,805 3,720 76 17 41 111 111 111 4,638 111

359,109 9,486 7,440 9,984 62,405 111 6,805 3,720 76 17 41 111 111 111 4,638 111

359,109 9,503 7,440 9,984 62,518 111 6,805 3,720 76 17 41 111 111 111 4,638 111

359,109 9,486 7,440 9,984 62,405 111 6,805 3,720 76 17 41 111 111 111 4,638 111

2.27 35.00 112.74 9.61 12.97 1,000.00 13.44 147.00 3,100.00 2,397.00 280.00 306.00 246.00 150.00 0.00 500.00

9,295 0 80

9,295 0 80

9,295 0 80

9,295 0 80

9,295 0 80

9,295 0 80

9,295 0 80

9,295 0 80

91.00 8,000.00 5,000.00

DIVISION 3 - CONCRETE DIVISION 3 TOTAL 03-112 STRUCT. FORMS - SLABS & FLATWORK 03-119 STRUCT. FORMS - PADDLEWHEELS 03-119 STRUCT. FORMS - AIRLIFTS

m2 # #

9,295 80 0

9,295 0 80

DIVISION 4 - MASONRY

47

DIVISION 4 TOTAL 04-221 8" CMU

m2

1,459

1,459

1,459

1,459

1,459

1,459

1,459

1,459

1,459

1,459

135.51

# #

80 0

0 80

0 80

0 80

0 80

0 80

0 80

0 80

0 80

0 80

5,500.00 1,000.00

m2 m2 m2 m2

9,295 9,295 9,295 9,295

9,295 9,295 9,295 9,295

9,295 9,295 9,295 9,295

9,295 9,295 9,295 9,295

9,295 9,295 9,295 9,295

9,295 9,295 9,295 9,295

9,295 9,295 9,295 9,295

9,295 9,295 9,295 9,295

9,295 9,295 9,295 9,295

9,295 9,295 9,295 9,295

65.00 15.00 40.00 4.00

m2

9,295

9,295

9,295

9,295

9,295

9,295

9,295

9,295

9,295

9,295

2.00

m2 m2

9,295 9,295

9,295 9,295

9,295 9,295

9,295 9,295

9,295 9,295

9,295 9,295

9,295 9,295

9,295 9,295

9,295 9,295

9,295 9,295

8.00 6.00

DIVISION 5 - METALS DIVISION 5 TOTAL 05-500 METAL FABRICATIONS PADDLEWHEELS 05-500 METAL FABRICATIONS AIRLIFTS DIVISION 6 - WOOD & PLASTICS DIVISION 6 TOTALS 06-050 FASTENERS AND ADHESIVES 06-100 ROUGH CARPENTRY 06-200 FINISH CARPENTRY 06-240 LAMINATES DIVISION

7

-

THERMAL

&

MOIST.

DIVISION 7 TOTALS 07-900 JOINT SEALERS DIVISION 8 - DOORS & WINDOWS DIVISION 8 TOTAL 08-100 METAL DOORS & FRAMES 08-600 WOOD & PLASTIC WINDOWS

48

08-700 HARDWARE

m2

9,295

9,295

9,295

9,295

9,295

9,295

9,295

9,295

9,295

9,295

3.00

m2 m2 m2 ha

9,295 9,295 9,295 111

9,295 9,295 9,295 111

9,295 9,295 9,295 111

9,295 9,295 9,295 111

9,295 9,295 9,295 111

9,295 9,295 9,295 111

9,295 9,295 9,295 111

9,295 9,295 9,295 111

9,295 9,295 9,295 111

9,295 9,295 9,295 111

50.00 25.00 10.00 650.00

# # # # # # # # # # # #

80 0 0 1 1 2 1 40 16 1 10 1

0 80 0 1 1 2 1 40 16 1 0 0

0 80 0 1 1 2 1 40 16 1 0 0

0 80 0 1 1 2 1 40 16 1 0 0

0 80 0 1 1 2 1 40 16 1 0 0

0 80 0 1 1 2 1 40 16 1 0 0

0 80 0 1 1 2 1 40 16 1 0 0

0 80 0 1 1 2 1 40 16 1 0 0

0 80 0 1 1 2 1 40 16 1 0 0

0 80 0 1 1 2 1 40 16 1 0 0

10,400.00 2,400.00 500,000.0 224,890.0 374,338.0 359,641.0 10,000.00 3,240.00 7,000.00 VARIES 281,250.0 2,750,000

DIVISION 9 - FINISHES DIVISION 9 TOTALS 09-250 GYPSUM BOARD 09-910 EXTERIOR PAINTING 09-920 INTERIOR PAINTING 09-920 OTHER PAINTING DIVISION 10 - SPECIALTIES DIVISION 10 TOTAL

DIVISION 11 - EQUIPMENT DIVISION 11 TOTAL 11-130 PADDLE WHEEL MOTORS & GEAR DRIVE 11-130 POND AIRLIFTS PIPING AND CONTROLS 11-200 WATER SUPPLY EQUIPMENT - HAWAII 11-200 WATER SUPPLY EQUIPMENT - GULF 11-210 WATER SUPPLY PUMP - HAWAII 11-210 WATER SUPPLY PUMP - GULF 11-210 SLURRY PUMP 11-250 AIR BLOWER FOR PBRS 11-250 AIR BLOWER FOR PONDS NA CARBON DIOXIDE COMPRESSOR 11-452 CENTRIFUGE 11-450 RING DRYER

49

11-450 HEXANE EXTRACTOR 11-452 FILTER PRESS 11-452 VALICOR EQUIPMENT 11-452 HYDROTHERMAL LIQUEFACTION 2 11-452 OPENALGAE EQUIPMENT 11-452 CATALYTIC HYDROTHERMAL 3 11-452 COMBINED HEAT AND POWER 4 11-452 FERMENTATION 5 11-454 OTHER PROCESSING EQUIPMENT 11-458 STIRRING DEVICES FOR NUTRIENTS 11-680 OFFICE & LAB EQUIPMENT

# # m3/da kg/da # kg/da kW gal/yr # # #

1 0 0 0 0 0 0 0 1 50 1

0 0 0 0 0 0 1 1 1 1 1 1 81 140 101 101 101 0 0 0 0 0 0 101,045 0 0 0 0 0 0 64,681 111,396 80,327 80,327 80,327 80,836 76 134 117 0 117 194 0 0 0 1 0 0 1 1 1 1 1 1 50 50 50 50 50 50 1 1 1 1 1 1

0 1 0 0 1 0 0 0 1 50 1

0 1 0 101,045 0 80,836 194 0 1 50 1

0 1 0 0 1 0 0 0 1 50 1

2,430,000 2,000,000 6,226.33 POWER 1,360,950 POWER LINEAR EXP 500,000.0 4,201.00 1,000,000

DIVISION 12 - FURNISHINGS DIVISION 12 TOTAL

DIVISION 13 - SPECIAL CONSTRUCTION DIVISION 13 TOTAL 13-052 HYPALON LINER AND GEOTEXTILE 13-052 RPP & SKAPS POND LINER AND GEOTEXTILE 13-052 LOW COST PONDS 13-153 PBR END ASSEMBLIES 13-165 PRE-ENGINEERED METAL BUILDINGS

m2 1,083,46 0 0 0 0 0 0 0 0 0 29.57 1,083,46 1,083,46 1,083,46 1,083,46 1,083,46 1,083,46 1,083,46 m2 0 0 0 13.44 1,083,95 1,084,44 3.40 m2 0 0 0 0 0 0 0 0 # 480 480 480 480 480 480 480 480 480 480 300.00 m2 9,295 9,295 9,295 9,295 9,295 9,295 9,295 9,295 9,295 9,295 237.00

DIVISION 14 - CONVEYING SYSTEMS DIVISION 14 TOTAL

50

DIVISION 15 - MECHANICAL DIVISION 15 TOTAL NA ALL MECHANICAL ALLOWANCE 15-300 FIRE PROTECTION

m2 m2

9,295 9,295

9,295 9,295

9,295 9,295

9,295 9,295

9,295 9,295

9,295 9,295

9,295 9,295

9,295 9,295

9,295 9,295

9,295 9,295

759,704 0.00

15-400 FACILITY PIPING – GULF 6 15-400 FACILITY PIPING – HAWAII 6 15-955 MECHANICAL SYSTEM CONTROLS

# # ha

1 1 111

1 1 111

1 1 111

1 1 111

1 1 111

1 1 111

1 1 111

1 1 111

1 1 111

1 1 111

VARIES VARIES 2,183.36

ha m2 ha # ha ha m2 ha

111 9,295 111 120 111 111 9,295 111

111 9,295 111 120 111 111 9,295 111

111 9,295 111 120 111 111 9,295 111

111 9,295 111 120 111 111 9,295 111

111 9,295 111 120 111 111 9,295 111

111 9,295 111 120 111 111 9,295 111

111 9,295 111 120 111 111 9,295 111

111 9,295 111 120 111 111 9,295 111

111 9,295 111 120 111 111 9,295 111

DIVISION 16 - ELECTRICAL DIVISION 16 TOTAL 16-100 BASIC SYSTEMS (ROUGH-IN) 16-190 BASIC SYSTEMS (TRIM OUT) 16-300 PRIMARY SERVICE (600v - 35kv) 16-400 SECONDARY SERVICE & DISTRIBUTION 16-500 LIGHTING 16-700 COMMUNICATIONS 16-720 ALARM & DETECTION SYSTEMS 16-900 ELECTRICAL SYSTEM CONTROLS

111 3,454.59 9,295 25.00 111 10,000.00 120 1,500.00 111 1,409.58 111 986.70 9,295 2.69 111 2,350.00

51

Table F-2. Pipe cost estimates. TEXAS

1

Pipe Description Length (m) HDPE 0.1 m diameter 3280 HDPE 0.2 m diameter 400 HDPE 0.3 m diameter 2558 HDPE 0.35 m diameter 80 HDPE 0.4 m diameter 9691 HDPE 0.5 m diameter 15708 HDPE 1.02 m diameter 4203 LS25 0.01 m diameter flexible tubing High Pressure 0.1 m diameter LS25 0.03 m diameter flexible tubing High Pressure 0.15 m diameter High pressure 0.2 m diameter HAWAII

2

3

4

5

6

7

8

9

10

Length (m) Length (m) Length (m) Length (m) Length (m) Length (m) Length (m) Length (m) Length (m) 3280 3280 2800 2800 2800 2800 2800 2800 2800 400 400 0 0 0 0 0 0 0 2558 2558 2558 2558 2558 2558 2558 2558 2558 80 80 80 80 80 80 80 80 80 9691 9691 9691 9691 9691 9691 9691 9691 9691 15708 15708 12497 12497 12497 12497 12497 12497 12497 4203 4203 4203 4203 4203 4203 4203 4203 4203

Total Cost ($/m) 47.43 95.94 194.93 237.00 277.24 461.25 1806.58

544

544

544

544

544

544

544

544

544

544

18.15

827

827

827

827

827

827

827

827

827

827

47.43

80

80

80

80

80

80

80

80

80

80

18.15

1614

1614

1614

1614

1614

1614

1614

1614

1614

1614

74.10

15000

15000

15000

15000

15000

15000

15000

15000

15000

15000

95.94

1

2

3

4

5

6

7

8

9

10

Pipe Description Length (m) HDPE 0.1 m diameter 3280 HDPE 0.2 m diameter 400 HDPE 0.3 m diameter 2579 HDPE 0.35 m diameter 80 HDPE 0.4 m diameter 9691 HDPE 0.5 m diameter 9967 HDPE 1.02 m diameter 0

Length (m) Length (m) Length (m) Length (m) Length (m) Length (m) Length (m) Length (m) Length (m) 3280 3280 2800 2800 2800 2800 2800 2800 2800 400 400 0 0 0 0 0 0 0 2579 2579 2579 2579 2579 2579 2579 2579 2579 80 80 80 80 80 80 80 80 80 9691 9691 9691 9691 9691 9691 9691 9691 9691 9967 9967 6756 6756 6756 6756 6756 6756 6756 0 0 0 0 0 0 0 0 0

Total Cost ($/m) 47.43 95.94 194.93 237.00 277.24 461.25 1806.58

52

LS25 0.01 m diameter felxible tubing High Pressure 0.1 m diameter LS25 0.03 m diameter flexible tubing High Pressure 0.15 m diameter High pressure 0.2 m diameter

480

480

480

480

480

480

480

480

480

480

18.15

730

730

730

730

730

730

730

730

730

730

47.43

80

80

80

80

80

80

80

80

80

80

18.15

1614

1614

1614

1614

1614

1614

1614

1614

1614

1614

74.10

15000

15000

15000

15000

15000

15000

15000

15000

15000

15000

95.94

53

Table F-3. Capital costs for all 10 cases. All data are in thousands of dollars. 1

2

3

4

5

6

7

8

9

10

1,930

1,930

1,930

1,930

1,930

1,930

1,930

1,930

1,930

1,930

1,176 167 56 24 111 17 17 111 56 195

1,176 167 56 24 111 17 17 111 56 195

1,176 167 56 24 111 17 17 111 56 195

1,176 167 56 24 111 17 17 111 56 195

1,176 167 56 24 111 17 17 111 56 195

1,176 167 56 24 111 17 17 111 56 195

1,176 167 56 24 111 17 17 111 56 195

1,176 167 56 24 111 17 17 111 56 195

1,176 167 56 24 111 17 17 111 56 195

1,176 167 56 24 111 17 17 111 56 195

4,062

4,064

4,063

4,063

4,063

4,063

4,065

4,063

4,065

4,063

815 332 839 96 810 111 91 547 236 40

815 332 839 96 810 111 91 547 236 40

815 332 839 96 809 111 91 547 236 40

815 332 839 96 810 111 91 547 236 40

815 332 839 96 809 111 91 547 236 40

815 332 839 96 810 111 91 547 236 40

815 333 839 96 811 111 91 547 236 40

815 332 839 96 809 111 91 547 236 40

815 333 839 96 811 111 91 547 236 40

815 332 839 96 809 111 91 547 236 40

DIVISION 1 - GENERAL REQUIREMENTS DIVISION 1 TOTAL 01- PROJECT COORDINATION 01- SURVEY SUPERVISION/LAYOUT MATERIAL 01- REGULATORY REQUIREMENTS (PERMITS) 01- DEBRIS CONTROL 01- MATERIAL HANDLING 01- FIRST AID/SAFETY 01- BARRIERS/TEMP. FENCING 01- SECURITY 01- CONST. CLEANING 01- SHIPPING & TRANSPORTATION DIVISION 2 - SITE WORK DIVISION 2 TOTAL 02- MASS GRADE (TERRACING) 02- FINISH GRADING 02- UTILITY EXC., BACKFILL, COMPACT 02- PAVEMENT EXC., BACKFILL, COMPACT 02- SOIL STABILIZATION 02- SEDIMENT CONTROL 02- ASPHALTIC PAVING 02- CURB & GUTTER 02- DRYWELLS (DEPTH) 02- DRILLED WATER SUPPLY WELLS (depth)

54

02- SEPTIC SYSTEMS 02- OVERHEAD ELECTRIC SERVICE 02- UNDERGROUND ELECTRIC SERVICE 02- IRRIGATION SYSTEMS 02- FENCES & GATES 02- LANDSCAPING

11 34 27 17 0 55

11 34 27 17 0 56

11 34 27 17 0 56

11 34 27 17 0 56

11 34 27 17 0 56

11 34 27 17 0 56

11 34 27 17 0 56

11 34 27 17 0 56

11 34 27 17 0 56

11 34 27 17 0 56

1,486

1,246

1,246

1,246

1,246

1,246

1,246

1,246

1,246

1,246

846 640 0

846 0 400

846 0 400

846 0 400

846 0 400

846 0 400

846 0 400

846 0 400

846 0 400

846 0 400

198

198

198

198

198

198

198

198

198

198

198

198

198

198

198

198

198

198

198

198

440

80

80

80

80

80

80

80

80

80

440 0

0 80

0 80

0 80

0 80

0 80

0 80

0 80

0 80

0 80

1,153

1,153

1,153

1,153

1,153

1,153

1,153

1,153

1,153

1,153

DIVISION 3 – CONCRETE DIVISION 3 TOTAL 03- STRUCT. FORMS - SLABS & FLATWORK 03- STRUCT. FORMS – PADDLEWHEELS 03- STRUCT. FORMS – AIRLIFTS DIVISION 4 – MASONRY DIVISION 4 TOTAL 04- 8" CMU DIVISION 5 – METALS DIVISION 5 TOTAL 05- METAL FABRICATIONS PADDLEWHEELS 05- METAL FABRICATIONS AIRLIFTS DIVISION 6 - WOOD & PLASTICS DIVISION 6 TOTALS

55

06- FASTENERS AND ADHESIVES 06- ROUGH CARPENTRY 06- FINISH CARPENTRY 06- LAMINATES DIVISION

7

-

THERMAL

DIVISION 7 TOTALS 07- JOINT SEALERS

&

604 139 372 37

604 139 372 37

604 139 372 37

604 139 372 37

604 139 372 37

604 139 372 37

604 139 372 37

604 139 372 37

604 139 372 37

604 139 372 37

19

19

19

19

19

19

19

19

19

19

19

19

19

19

19

19

19

19

19

19

158

158

158

158

158

158

158

158

158

158

74 56 28

74 56 28

74 56 28

74 56 28

74 56 28

74 56 28

74 56 28

74 56 28

74 56 28

74 56 28

862

862

862

862

862

862

862

862

862

862

465 232 93 72

465 232 93 72

465 232 93 72

465 232 93 72

465 232 93 72

465 232 93 72

465 232 93 72

465 232 93 72

465 232 93 72

465 232 93 72

0

0

0

0

0

0

0

0

0

0

MOIST.

DIVISION 8 - DOORS & WINDOWS DIVISION 8 TOTAL 08- METAL DOORS & FRAMES 08- WOOD & PLASTIC WINDOWS 08- HARDWARE DIVISION 9 - FINISHES DIVISION 9 TOTALS 09- GYPSUM BOARD 09- EXTERIOR PAINTING 09- INTERIOR PAINTING 09- OTHER PAINTING DIVISION 10 - SPECIALTIES DIVISION 10 TOTAL

56

DIVISION 11 - EQUIPMENT DIVISION 11 TOTAL - HAWAII DIVISION 11 TOTAL – TEXAS 11- PADDLE WHEEL MOTORS & GEAR DRIVE 11- POND AIRLIFTS PIPING AND CONTROLS 11- WATER TREATMENT EQUIPMENT - HAWAII 11- WATER TREATMENT EQUIPMENT - TEXAS 11- WATER SUPPLY PUMP - HAWAII 11- WATER SUPPLY PUMP - GULF 11- SLURRY PUMP 11- AIR BLOWER FOR PBRS 11- AIR BLOWER FOR PONDS NA CARBON DIOXIDE COMPRESSOR 11- CENTRIFUGE 11- RING DRYER 11- HEXANE EXTRACTOR 11- FILTER PRESS 11- VALICOR EQUIPMENT 11- HYDROTHERMAL LIQUEFACTION EQUIPMENT2 11- OPENALGAE EQUIPMENT 11- CATALYTIC HYDROTHERMAL GASIFICATION 3 11- COMBINED HEAT AND POWER 4 11- FERMENTATION 5 11- OTHER PROCESSING EQUIPMENT 11- STIRRING DEVICES FOR NUTRIENTS 11- OFFICE & LAB EQUIPMENT

11,313 9,649 11,883 10,218

11,963 12,533

10,534 11,104

6,247 6,817

10,534 11,104

15,432 16,001

6,120 6,690

15,432 16,001

6,120 6,690

832 0 0 225 374 719 10 130 112 152 2,813 2,750 2,430 0 0 0 0 0 0 0 500 210 1,000

0 192 0 225 374 719 10 130 112 152 0 0 0 2,000 507 0 0 4,079 382 0 500 210 1,000

0 192 0 225 374 719 10 130 112 253 0 0 0 2,000 874 0 0 5,847 461 0 500 210 1,000

0 192 0 225 374 719 10 130 112 231 0 0 0 2,000 629 0 0 4,708 438 0 500 210 1,000

0 192 0 225 374 719 10 130 112 231 0 0 0 2,000 629 0 0 0 0 858 500 210 1,000

0 192 0 225 374 719 10 130 112 231 0 0 0 2,000 629 0 0 4,708 438 0 500 210 1,000

0 192 0 225 374 719 10 130 112 231 0 0 0 2,000 0 5,402 0 4,728 542 0 500 210 1,000

0 192 0 225 374 719 10 130 112 231 0 0 0 2,000 0 0 1,361 0 0 0 500 210 1,000

0 192 0 225 374 719 10 130 112 231 0 0 0 2,000 0 5,402 0 4,728 542 0 500 210 1,000

0 192 0 225 374 719 10 130 112 231 0 0 0 2,000 0 0 1,361 0 0 0 500 210 1,000

0

0

0

0

0

0

0

0

0

0

DIVISION 12 - FURNISHINGS DIVISION 12 TOTAL

57

DIVISION 13 - SPECIAL CONSTRUCTION DIVISION 13 TOTAL 13- HYPALON AND GEOTEXTILE 13- RPP & SKAPS POND LINER AND GEOTEXTILE 13- LOW COST PONDS 13- PBR END ASSEMBLIES 13- PRE-ENGINEERED METAL BUILDINGS

34,385 16,909

16,909

16,909

16,909

16,909

16,909

16,909

6,032

6,034

32,038 0 0 14,562 0 0 144 144 2,203 2,203

0 14,562 0 144 2,203

0 14,562 0 144 2,203

0 14,562 0 144 2,203

0 14,562 0 144 2,203

0 14,562 0 144 2,203

0 14,562 0 144 2,203

0 0 0 0 3,685 3,687 144 144 2,203 2,203

0

0

0

0

0

0

0

0

10,613 10,613 20,850 30,453

10,613 30,453

9,071 27,368

9,071 27,368

9,071 27,368

9,071 27,368

9,071 27,368

9,071 27,368

9,071 27,368

760 760 0 0 19,840 19,840 9,603 9,603 250 250

760 0 19,840 9,603 250

760 0 18,298 8,061 250

760 0 18,298 8,061 250

760 0 18,298 8,061 250

760 0 18,298 8,061 250

760 0 18,298 8,061 250

760 0 18,298 8,061 250

760 0 18,298 8,061 250

2,480

2,480

2,480

2,480

2,480

2,480

2,480

2,480

2,480

DIVISION 14 - CONVEYING SYSTEMS DIVISION 14 TOTAL

DIVISION 15 - MECHANICAL DIVISION 15 TOTAL - HAWAII DIVISION 15 TOTAL - TEXAS NA ALL MECHANICAL ALLOWANCE 15- FIRE PROTECTION 15- FACILITY PIPING – GULF 6 15- FACILITY PIPING – HAWAII 6 15- MECHANICAL SYSTEM CONTROLS

0

0

DIVISION 16 - ELECTRICAL

DIVISION 16 TOTAL

2,480

58

16- BASIC SYSTEMS (ROUGH-IN) 16- BASIC SYSTEMS (TRIM OUT) 16- PRIMARY SERVICE (600v - 35kv) 16- SECONDARY SERVICE & DISTRIBUTION 16- LIGHTING 16- COMMUNICATIONS 16- ALARM & DETECTION SYSTEMS 16- ELECTRICAL SYSTEM CONTROLS

396 232 1,106 180 161 110 25 262

396 232 1,114 180 161 110 25 262

396 232 1,114 180 161 110 25 262

396 232 1,114 180 161 110 25 262

396 232 1,114 180 161 110 25 262

396 232 1,114 180 161 110 25 262

396 232 1,114 180 161 110 25 262

396 232 1,114 180 161 110 25 262

396 232 1,114 180 161 110 25 262

396 232 1,114 180 161 110 25 262

Table F-4. Capital cost summary.

All data are in thousands of dollars. The totals are scaled by geographic cost modifiers that relate the costs in Texas (0.88) and Hawaii (1.37) with the U.S. average. 1

2

3

4

5

6

7

8

9

10

Texas Total Hawaii Total

79,906 69,099

69,769 49,359

72,082 51,672

67,569 48,702

63,281 44,414

67,569 48,702

72,468 53,600

63,154 44,287

61,592 42,724

52,280 33,412

Texas Total Scaled Hawaii Total Scaled

70,317 94,666

61,396 67,622

63,432 70,791

59,461 66,721

55,687 60,847

59,461 66,721

63,772 73,433

55,576 60,673

54,201 58,532

46,006 45,775

59

Cumulative Discounted Cash Flow The cumulative discounted cash flow is calculated according to equations presented in Section 2.4.2 of the main manuscript. The MACRS depreciation schedule is shown in Table F-5 and the depreciation for Texas and Hawaii is shown in Table F-6. The depreciable investment is the total capital cost less Division 1 and Division 2 from Table F-3. The annual revenue and operating cost (excepting the variable tax and loan payment costs) for each case is listed in Table F-7, while Table F-8 lists the cumulative discounted cash flow for each case. Table F-5. MACRS depreciation schedule. Year MACRS % 0 1 2 3 4 5 6 7 8

0 0.143 0.245 0.175 0.125 0.089 0.089 0.089 0.045

Table F-6. Depreciation for Texas and Hawaii. All values are in millions of dollars. 1

Texas Depreciable Investment Hawaii Depreciable Investment Texas Year 0.00 1.00 2.00 3.00 4.00 5.00 6.00 7.00 8.00 Hawaii Year

2

3

4

5

6

7

8

9

10

65.04 56.12 58.16 54.19 50.41 54.19 58.50 50.30 48.93 40.73 86.46 59.41 62.58 58.51 52.64 58.51 65.22 52.46 50.32 37.57

0.00 9.30 15.94 11.38 8.13 5.79 5.79 5.79 2.93 0.00 0.00

0.00 8.03 13.75 9.82 7.02 4.99 4.99 4.99 2.53 0.00 0.00

0.00 8.32 14.25 10.18 7.27 5.18 5.18 5.18 2.62 0.00 0.00

0.00 7.75 13.28 9.48 6.77 4.82 4.82 4.82 2.44 0.00 0.00

0.00 7.21 12.35 8.82 6.30 4.49 4.49 4.49 2.27 0.00 0.00

0.00 7.75 13.28 9.48 6.77 4.82 4.82 4.82 2.44 0.00 0.00

0.00 8.37 14.33 10.24 7.31 5.21 5.21 5.21 2.63 0.00 0.00

0.00 7.19 12.32 8.80 6.29 4.48 4.48 4.48 2.26 0.00 0.00

0.00 7.00 11.99 8.56 6.12 4.35 4.35 4.35 2.20 0.00 0.00

0.00 5.82 9.98 7.13 5.09 3.63 3.63 3.63 1.83 0.00 0.00

60

0.00 1.00 2.00 3.00 4.00 5.00 6.00 7.00 8.00

0.00 12.36 21.18 15.13 10.81 7.69 7.69 7.69 3.89

0.00 8.50 14.56 10.40 7.43 5.29 5.29 5.29 2.67

0.00 8.95 15.33 10.95 7.82 5.57 5.57 5.57 2.82

0.00 8.37 14.34 10.24 7.31 5.21 5.21 5.21 2.63

0.00 7.53 12.90 9.21 6.58 4.68 4.68 4.68 2.37

0.00 8.37 14.34 10.24 7.31 5.21 5.21 5.21 2.63

0.00 9.33 15.98 11.41 8.15 5.80 5.80 5.80 2.93

0.00 7.50 12.85 9.18 6.56 4.67 4.67 4.67 2.36

0.00 7.20 12.33 8.81 6.29 4.48 4.48 4.48 2.26

0.00 5.37 9.20 6.57 4.70 3.34 3.34 3.34 1.69

Table F-7. Annual revenue and operating costs in millions of dollars. *The total operating costs shown here exclude loan payments and taxes, which vary from year to year. **The loan term is 10-years. Taxes are negligible.

1

2

3

4

5

3.49 3.11 5.33 3.68 4.08 Texas Revenue 5.43 4.85 8.30 5.72 6.35 Hawaii Revenue 0.00 0.00 0.00 0.00 0.00 Texas Land Rent 0.00 0.00 0.00 0.00 0.00 Hawaii Land Rent 0.65 0.56 0.58 0.54 0.50 Texas Insurance 0.86 0.59 0.63 0.59 0.53 Hawaii Insurance 0.65 0.56 0.58 0.54 0.50 Texas Maintenance 0.86 0.59 0.63 0.59 0.53 Hawaii Maintenance 4.34 1.32 1.95 1.57 1.78 Texas Energy and Materials 11.81 3.14 4.26 3.64 4.24 Hawaii Energy and Materials 7.01 3.81 4.48 4.02 4.16 Texas Total Operating Cost* 15.53 6.32 7.49 6.80 7.29 Hawaii Total Operating Cost* 6.29 5.49 5.67 5.32 4.98 Texas Annual Loan Payment** Hawaii Annual Loan Payment** 8.46 6.05 6.33 5.97 5.44

6

7

8

9

10

3.68 5.72 0.00 0.00 0.54 0.59 0.54 0.59 1.64 2.00 4.10 5.16 5.32 5.97

2.35 3.65 0.00 0.00 0.58 0.65 0.58 0.65 0.72 1.97 3.26 5.26 5.70 6.57

4.34 6.76 0.00 0.00 0.50 0.52 0.50 0.52 1.37 3.40 3.75 6.44 4.97 5.43

2.35 3.65 0.00 0.00 0.49 0.50 0.49 0.50 0.73 0.52 3.08 3.51 4.85 5.23

4.34 6.76 0.00 0.00 0.41 0.38 0.41 0.38 1.40 1.52 3.59 4.26 4.11 4.09

Table F-8. Cumulative discounted cash flow each year in millions of dollars. Texas 0 1 2 3 4 5 6 7 8 9

1T

2T

3T

4T

5T

6T

7T

8T

9T

10T

-28.13 -37.05 -45.15 -52.53 -59.23 -65.32 -70.86 -75.89 -80.47 -84.63

-24.56 -30.19 -35.30 -39.95 -44.18 -48.03 -51.52 -54.70 -57.58 -60.21

-25.37 -29.76 -33.75 -37.37 -40.67 -43.67 -46.39 -48.87 -51.12 -53.17

-23.78 -28.93 -33.61 -37.87 -41.73 -45.25 -48.45 -51.35 -53.99 -56.40

-22.27 -26.88 -31.06 -34.86 -38.32 -41.46 -44.32 -46.92 -49.28 -51.43

-23.78 -29.00 -33.74 -38.05 -41.97 -45.53 -48.77 -51.72 -54.39 -56.83

-25.51 -31.52 -36.99 -41.96 -46.47 -50.58 -54.31 -57.71 -60.79 -63.60

-22.23 -26.21 -29.83 -33.12 -36.12 -38.84 -41.31 -43.56 -45.60 -47.46

-21.68 -26.75 -31.36 -35.55 -39.36 -42.83 -45.98 -48.84 -51.44 -53.81

-18.40 -21.46 -24.23 -26.76 -29.05 -31.14 -33.04 -34.76 -36.33 -37.75

61

10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 Hawaii 0 1 2 3 4 5 6 7 8 9 10 11

-88.41 -89.65 -90.77 -91.79 -92.72 -93.56 -94.33 -95.03 -95.66 -96.24 -96.76 -97.24 -97.67 -98.06 -98.42 -98.74 -99.04 -99.31 -99.55 -99.78 -99.98 -100.16 -100.33 -100.48 -100.62 -100.74 -100.86 -100.96 -101.05 -101.14 -101.22 1H -37.87 -54.75 -70.09 -84.04 -96.72 -108.25 -118.73 -128.26 -136.92 -144.79 -151.95 -155.49

-62.60 -62.84 -63.06 -63.27 -63.45 -63.62 -63.77 -63.91 -64.04 -64.15 -64.26 -64.35 -64.44 -64.51 -64.59 -64.65 -64.71 -64.76 -64.81 -64.86 -64.90 -64.93 -64.97 -65.00 -65.02 -65.05 -65.07 -65.09 -65.11 -65.13 -65.14 2H -27.05 -33.88 -40.10 -45.74 -50.88 -55.55 -59.79 -63.65 -67.15 -70.34 -73.24 -73.76

-55.03 -54.73 -54.46 -54.22 -53.99 -53.79 -53.61 -53.44 -53.29 -53.15 -53.02 -52.91 -52.81 -52.71 -52.62 -52.55 -52.48 -52.41 -52.35 -52.30 -52.25 -52.21 -52.17 -52.13 -52.10 -52.07 -52.04 -52.01 -51.99 -51.97 -51.95 3H -28.32 -33.34 -37.91 -42.06 -45.84 -49.27 -52.39 -55.23 -57.81 -60.15 -62.28 -62.00

-58.58 -58.70 -58.81 -58.91 -59.00 -59.09 -59.16 -59.23 -59.29 -59.35 -59.40 -59.45 -59.49 -59.53 -59.56 -59.59 -59.62 -59.65 -59.67 -59.70 -59.71 -59.73 -59.75 -59.76 -59.78 -59.79 -59.80 -59.81 -59.82 -59.83 -59.84 4H -26.69 -33.09 -38.91 -44.20 -49.01 -53.39 -57.36 -60.97 -64.26 -67.25 -69.96 -70.34

-53.38 -53.41 -53.43 -53.46 -53.48 -53.50 -53.51 -53.53 -53.55 -53.56 -53.57 -53.58 -53.59 -53.60 -53.61 -53.62 -53.62 -53.63 -53.64 -53.64 -53.65 -53.65 -53.66 -53.66 -53.66 -53.66 -53.67 -53.67 -53.67 -53.67 -53.68 5H -24.34 -30.14 -35.40 -40.20 -44.55 -48.51 -52.11 -55.38 -58.36 -61.06 -63.52 -63.85

-59.04 -59.19 -59.32 -59.44 -59.55 -59.65 -59.75 -59.83 -59.90 -59.97 -60.04 -60.09 -60.14 -60.19 -60.23 -60.27 -60.31 -60.34 -60.37 -60.40 -60.42 -60.44 -60.46 -60.48 -60.50 -60.51 -60.53 -60.54 -60.55 -60.56 -60.57 6H -26.69 -31.60 -36.06 -40.12 -43.80 -47.16 -50.20 -52.98 -55.49 -57.78 -59.87 -59.67

-66.15 -66.46 -66.75 -67.02 -67.26 -67.48 -67.68 -67.86 -68.02 -68.17 -68.30 -68.43 -68.54 -68.64 -68.73 -68.82 -68.89 -68.96 -69.03 -69.08 -69.14 -69.18 -69.23 -69.27 -69.30 -69.33 -69.36 -69.39 -69.41 -69.44 -69.46 7H -29.37 -36.80 -43.55 -49.69 -55.27 -60.35 -64.96 -69.15 -72.97 -76.43 -79.58 -80.14

-49.15 -48.94 -48.75 -48.58 -48.43 -48.29 -48.16 -48.04 -47.94 -47.84 -47.75 -47.67 -47.60 -47.53 -47.47 -47.42 -47.37 -47.33 -47.28 -47.25 -47.21 -47.18 -47.16 -47.13 -47.11 -47.09 -47.07 -47.05 -47.03 -47.02 -47.01 8H -24.27 -28.91 -33.14 -36.97 -40.46 -43.64 -46.52 -49.14 -51.52 -53.69 -55.66 -55.55

-55.96 -56.21 -56.45 -56.66 -56.85 -57.03 -57.19 -57.33 -57.46 -57.58 -57.69 -57.79 -57.88 -57.96 -58.04 -58.10 -58.16 -58.22 -58.27 -58.32 -58.36 -58.40 -58.43 -58.46 -58.49 -58.52 -58.54 -58.56 -58.58 -58.60 -58.62 9H -23.41 -28.04 -32.25 -36.08 -39.56 -42.72 -45.59 -48.21 -50.58 -52.74 -54.71 -54.66

-39.05 -38.78 -38.54 -38.32 -38.13 -37.95 -37.78 -37.63 -37.50 -37.37 -37.26 -37.16 -37.07 -36.98 -36.91 -36.84 -36.77 -36.72 -36.66 -36.62 -36.57 -36.53 -36.50 -36.47 -36.44 -36.41 -36.38 -36.36 -36.34 -36.32 -36.31 10H -18.31 -19.76 -21.08 -22.28 -23.37 -24.36 -25.26 -26.08 -26.83 -27.51 -28.12 -27.25

62

12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40

-158.71 -161.64 -164.30 -166.72 -168.92 -170.91 -172.73 -174.38 -175.88 -177.25 -178.49 -179.62 -180.64 -181.58 -182.42 -183.19 -183.90 -184.53 -185.11 -185.64 -186.12 -186.55 -186.95 -187.31 -187.63 -187.93 -188.20 -188.45 -188.67

-74.22 -74.65 -75.04 -75.39 -75.71 -76.00 -76.27 -76.51 -76.73 -76.92 -77.10 -77.27 -77.42 -77.55 -77.68 -77.79 -77.89 -77.98 -78.07 -78.15 -78.22 -78.28 -78.34 -78.39 -78.44 -78.48 -78.52 -78.55 -78.59

-61.75 -61.52 -61.30 -61.11 -60.94 -60.78 -60.63 -60.50 -60.38 -60.28 -60.18 -60.09 -60.01 -59.93 -59.87 -59.80 -59.75 -59.70 -59.65 -59.61 -59.57 -59.54 -59.51 -59.48 -59.45 -59.43 -59.41 -59.39 -59.37

-70.68 -70.99 -71.28 -71.53 -71.77 -71.98 -72.18 -72.35 -72.51 -72.66 -72.79 -72.91 -73.02 -73.12 -73.21 -73.29 -73.37 -73.43 -73.50 -73.55 -73.60 -73.65 -73.69 -73.73 -73.76 -73.80 -73.82 -73.85 -73.87

-64.14 -64.41 -64.66 -64.88 -65.09 -65.27 -65.44 -65.59 -65.73 -65.86 -65.98 -66.08 -66.17 -66.26 -66.34 -66.41 -66.48 -66.53 -66.59 -66.64 -66.68 -66.72 -66.76 -66.79 -66.82 -66.85 -66.87 -66.90 -66.92

-59.49 -59.32 -59.17 -59.04 -58.91 -58.80 -58.70 -58.61 -58.52 -58.45 -58.38 -58.31 -58.26 -58.20 -58.16 -58.11 -58.07 -58.04 -58.01 -57.98 -57.95 -57.93 -57.90 -57.88 -57.87 -57.85 -57.83 -57.82 -57.81

-80.66 -81.12 -81.54 -81.93 -82.28 -82.59 -82.88 -83.15 -83.38 -83.60 -83.80 -83.98 -84.14 -84.29 -84.42 -84.55 -84.66 -84.76 -84.85 -84.93 -85.01 -85.08 -85.14 -85.20 -85.25 -85.30 -85.34 -85.38 -85.42

-55.45 -55.36 -55.27 -55.20 -55.13 -55.07 -55.01 -54.96 -54.91 -54.87 -54.83 -54.79 -54.76 -54.73 -54.71 -54.68 -54.66 -54.64 -54.62 -54.60 -54.59 -54.58 -54.56 -54.55 -54.54 -54.53 -54.52 -54.52 -54.51

-54.61 -54.57 -54.54 -54.50 -54.47 -54.44 -54.42 -54.39 -54.37 -54.36 -54.34 -54.32 -54.31 -54.29 -54.28 -54.27 -54.26 -54.25 -54.25 -54.24 -54.23 -54.23 -54.22 -54.21 -54.21 -54.21 -54.20 -54.20 -54.20

-26.45 -25.73 -25.07 -24.47 -23.93 -23.44 -22.99 -22.58 -22.21 -21.91 -21.66 -21.44 -21.24 -21.05 -20.88 -20.73 -20.59 -20.47 -20.35 -20.25 -20.15 -20.07 -19.99 -19.92 -19.85 -19.80 -19.74 -19.69 -19.65

63

G. Appendix G: Life Cycle Inventory and Impact Definitions LCA Inventory Table G-1. Chosen ecoinvent© equivalences (version 3.1) for the different elements of the life cycle inventories.

Whenever available, data specific to location (Hawaii, Texas or USA) have been used. When not available, data for a global average excluding European Union (RoW) have been used. Some of the equivalences, labeled as (E), are individual emissions added to the life cycle inventory vector of emissions and extractions of substances to and from the environment. Name of element N-fertilizer (Case 1) N-fertilizer (other cases) P-fertilizer (Case 1) P-fertilizer (other cases) Si-fertilizer Electricity (Cases 1T-5T, 7T, 8T) Electricity (Cases 1H-5H, 7H, 8H) Electricity (Cases 6, 9,10) Heat Solvent (Cases 1-6) Solvent (Cases 8, 10) Phosphoric acid Low density polyethylene (LDPE) film for PBRs & pond liners Polyvinylchloride (PVC) for headers of PBRs and pipelines Process equipment for processing of algae Disposal of LDPE Disposal of PVC Transport associated with construction and disposal Replaced gasoline Replaced soy in animal feed Replaced corn in animal feed Replaced corn ethanol Solvent loss (Cases 1-6) Solvent loss (Cases 8,10) Land occupied by cultivation Land occupied by processing & access Nitrogen oxides (NOx) emitted by combined heat and power (CHP) Biogenic carbon monoxide (CO)

Corresponding ecoinvent© equivalence calcium nitrate ammonia, liquid (from steam reforming) sodium phosphate phosphate fertilizer, as P2O5 (diammonium phosphate production) sodium metasilicate pentahydrate, 58% active substance, powder electricity, medium voltage electricity, medium voltage electricity production, wind, 1-3MW turbine, onshore heat production, natural gas, at boiler modulating >100kW hexane heptane phosphoric acid, fertiliser grade, without water, in 70% solution state packaging film production, low density polyethylene polyvinylchloride production, bulk polymerisation ethanol fermentation plant (incl. disposal)

Unit Kg Kg Kg Kg

Location RoW RoW RoW RoW

Kg

RoW

kWh kWh kWh MJ

Texas Hawaii Texas/ Hawaii RoW

Kg Kg Kg

RoW RoW RoW

Kg

RoW

Kg

RoW

unit

RoW

waste polyethylene/polypropylene product waste polyvinylchloride product transport, freight, lorry 16-32 metric ton, EURO3

Kg Kg tkm

RoW RoW RoW

petrol, low-sulfur soybean meal corn grain ethanol, without water, in 95% solution state, from fermentation hexane, emitted in air (E) heptane, emitted in air (E) occupation, artificial water bodies (E) occupation, industrial area (E)

kg kg kg kg

RoW US US US

kg kg m2a m2a

-

nitrogen oxides, emitted in air (E)

kg

-

carbon monoxide, biogenic, emitted in air (E)

kg

-

64

emitted by CHP Biogenic methane (CH4) emitted by CHP Non-methane volatile organic compounds emitted by CHP Dinitrogen monoxide (N2O) emitted by CHP Sulfur dioxide (SO2) emitted by CHP Avoided fossil carbon dioxide emissions by replaced gasoline

methane, biogenic, emitted in air (E)

kg

-

NMVOC, emitted in air (E)

kg

-

dinitrogen monoxide, emitted in air (E)

kg

-

sulfur dioxide, emitted in air (E)

kg

-

carbon dioxide, fossil, emitted in air (E)

kg

-

Table G-2. Detailed life cycle inventories for Cases 1 to 5.

The only difference between Texas and Hawaii for the LCA is the electricity consumption in the cultivation. Therefore two different values are given for the total electricity consumption at each location. The values are all presented per hectare of cultivation, which is the functional unit of the LCA, and for the lifetime of the facility, which is assumed to be 30 years. Substituted products by processed algae are displayed with a negative sign. LCI element & unit N-fertilizer, kg P-fertilizer, kg Si-fertilizer, kg Electricity, kWh (Texas) Electricity, kWh (Hawaii) Heat, MJ Solvent, kg Phosphoric acid, kg LDPE, kg PVC, kg LDPE disposal, kg PVC disposal, kg Transports, tkm Replaced gasoline, kg Replaced soy in animal feed, kg Replaced corn in animal feed, kg Replaced corn ethanol, kg Solvent loss, kg Land occup. by cultivation, m2a Land occup. by processing, m2a NOx in air by CHP, kg CO bio in air by CHP, kg CH4 bio in air by CHP, kg NMVOC in air by CHP, kg N2O in air by CHP, kg SO2 in air by CHP, kg Avoided fossil CO2 in air by replaced gasoline, kg

Case 1 61 500 30 108 125 793 7 348 272 6 205 972 25 157 590 14 432 2 012 64 632 231 64 632 231 12 973 -266 209 -1 083 862 -361 287 0 14 432 300 000 57 000 0 0 0 0 0 0 -844 417

Case 2 62 809 4 809 125 098 3 173 135 1 970 835 2 496 468 4 013 0 64 632 231 64 632 231 12 973 -474 336 -783 926 -261 308 0 4 013 300 000 57 000 33 106 51 4 6 46 -1 504 596

Case 3 147 098 10 971 292 230 3 344952 2 142 752 3 301 138 6 915 0 64 632 231 64 632 231 12 973 -659 206 -1 466 017 -488 672 0 6 915 300 000 57 000 50 161 77 7 8 71 -2 091 001

Case 4 147 126 10 971 0 3 255 526 2 053 526 3 540 252 4 977 0 64 632 231 64 632 231 12 973 -702 138 -771 614 -257 205 0 4 977 300 000 57 000 34 108 52 5 6 47 -2 227 182

Case 5 174 175 12 063 0 3 482 255 2 280 555 5 725 415 4 977 0 64 632 231 64 632 231 12 973 -702 138 -771 614 -257 205 -173 215 4 977 300 000 57 000 0 0 0 0 0 0 -2 227 182

65

Table G-3. Detailed life cycle inventories for Cases 6 to 10.

The only difference between Texas and Hawaii for the LCA is the electricity consumption in the cultivation. Therefore two different values are given for the total electricity consumption at each location. The values are all presented per hectare of cultivation, which is the functional unit of the LCA, and for the lifetime of the facility, which is assumed to be 30 years. Substituted products by processed algae are displayed with a negative sign. LCI element & unit N-fertilizer, kg P-fertilizer, kg Si-fertilizer, kg Electricity, kWh (Texas) Electricity, kWh (Hawaii) Heat, MJ Solvent, kg Phosphoric acid, kg LDPE, kg PVC, kg LDPE disposal, kg PVC disposal, kg Transports, tkm Replaced gasoline, kg Replaced soy in animal feed, kg Replaced corn in animal feed, kg Replaced corn ethanol, kg Solvent loss, kg Land occup. by cultivation, m2a Land occup. by processing, m2a NOx in air by CHP, kg CO bio in air by CHP, kg CH4 bio in air by CHP, kg NMVOC in air by CHP, kg N2O in air by CHP, kg SO2 in air by CHP, kg Avoided fossil CO2 in air by replaced gasoline, kg

Case 6 147 126 10 971 0 3 255 526 2 053 526 3 540 252 4 977 0 64 632 231 64 632 231 12 973 -702 138 -771 614 -257 205 0 4 977 300 000 57 000 34 108 52 5 6 47 -2 227 182

Case 7 28 105 938 0 2 948 384 1 753 584 862 948 0 0 64 632 231 64 632 231 12 973 -1 054 260 0 0 0 0 300 000 57 000 71 227 109 9 12 99 -3 344 117

Case 8 159 942 12 064 0 3 587 280 2 292 480 701 276 50 0 64 632 231 64 632 231 12 973 -585 115 -1 137 737 -379 246 0 50 300 000 57 000 0 0 0 0 0 0 -1 855 985

Case 9 28 105 938 0 2 707 184 1 508 684 862 948 0 0 64 632 231 64 632 231 12 973 -1 054 260 0 0 0 0 300 000 57 000 71 227 109 9 12 99 -3 344 117

Case 10 159 942 12 064 0 3 242 380 2 047 680 701 276 50 0 64 632 231 64 632 231 12 973 -585 115 -1 137 737 -379 246 0 50 300 000 57 000 0 0 0 0 0 0 -1 855 985

Impact Definitions Human Health The damage done to humans by carcinogenic and non-carcinogenic toxicity, ozone layer depletion, ionizing radiations, respiratory effects and photo-oxidation. The substances contributing to the effects are weighted and expressed in Disability Adjusted Life Years (DALYs), before final weighting in points using the normalization factors for the USA.[27, 28]

66

Ecosystem Quality The damage done to ecosystems and biodiversity by aquatic and terrestrial ecotoxicity, acidification, eutrophication and land occupation. The substances or land occupation categories are weighted and expressed in potentially damaged fraction of species per unit area and per year (PDF x m2 x yr), before final weighting in points using the normalization factors for the USA.[27, 28] Climate Change The global warming potential over a 500 year time horizon of the different greenhouse gases emissions. They are weighted and expressed in kg CO2-eq), before final weighting in points using the normalization factors for the USA.[27, 28] Non-renewable Resources Includes the extraction of mineral resources and the primary non-renewable energy consumption (i.e., fossil and nuclear). Energy resources represent the lost non-renewable energies. Mineral resources are not lost since they remain in the economic system and the environment, but are diluted. Their aggregation is based on additional energy that will have to be consumed in the future because of the lower ore concentration in mines. The resources are expressed in MJ-eq of primary non-renewable energy, before final weighting in points using the normalization factors for the USA.[27, 28] Water Depletion Potential Characterizes the usage and loss of freshwater. Includes the water consumption from lakes, rivers, wells in groundwater and other unspecified natural origin. Salt or brackish water are not included. The results are expressed in m3 of water consumed.[29]

67

H. Appendix H: Detailed Life Cycle Impact Assessment Results

Figure H-1. Impacts on Human Health calculated with Impact2002+ for all cases in Texas (T) and Hawaii (H). Positive contributions represent harmful impacts, negative ones beneficial substitutions of products.

68

Figure H-2. Impacts on Ecosystem Quality calculated with Impact2002+ for all cases in Texas (T) and Hawaii (H). Positive contributions represent harmful impacts, negative ones beneficial substitutions of products.

69

Figure H-3. Impacts on Climate Change calculated with Impact2002+ for all cases in Texas (T) and Hawaii (H). Positive contributions represent harmful impacts, negative ones beneficial substitutions of products.

70

Figure H-4. Impacts on Resources calculated with Impact2002+ for all cases in Texas (T) and Hawaii (H). Positive contributions represent harmful impacts, negative ones beneficial substitutions of products.

71

Figure H-5. Impacts on Water Depletion Potential calculated with Recipe for all cases in Texas (T) and Hawaii (H). Positive contributions represent harmful impacts, negative ones beneficial substitutions of products.

72

I. Appendix I: Sensitivity Analysis Data Table I-1. Results for the sensitivity analysis with favorable parameters are shown in red and unfavorable parameters are shown in blue. In a few cases, parameters are favorable for some metrics and unfavorable for others. Parameter

EROI

Minimum BC ($/L)

Aggregate LCA

4T 0.93 1.16 1.35

5T 0.94 1.14 1.30

6T 2.28 2.65 2.93

7T 1.05 1.39 1.72

8T 1.01 1.25 1.45

4T 4.12 3.02 2.36

5T 3.85 2.77 2.12

6T 4.15 3.05 2.38

7T 3.19 2.45 2.00

8T 4.22 2.90 2.12

4T 182.1 56.7 -68.8

5T 185.9 48.2 -89.6

6T -279.1 -404.5 -530.0

7T 104.7 -34.2 -173.2

8T 180.9 40.1 -100.8

1.01 1.16 1.29

1.01 1.14 1.26

2.38 2.65 2.88

1.39 1.39 1.39

1.17 1.25 1.32

4.01 3.02 2.42

3.69 2.77 2.22

4.05 3.05 2.44

2.45 2.45 2.45

3.70 2.90 2.43

122.0 56.7 0.2

113.8 48.2 -8.1

-339.2 -404.5 -461.0

-34.2 -34.2 -34.2

-422.4 40.1 13.6

Airlift Efficiency (0.25)

1.00 1.16

1.00 1.14

2.39 2.65

1.14 1.39

1.07 1.25

3.07 3.02

2.82 2.77

3.10 3.05

2.48 2.45

2.97 2.90

193.0 56.7

195.8 48.2

-399.0 -404.5

87.7 -34.2

184.6 40.1

Airlift Efficiency (0.35)

1.24

1.21

2.78

1.53

1.34

3.00

2.75

3.02

2.43

2.88

0.7

-11.4

-404.5

-86.5

-21.4

Biocrude Recovery Eff (0.7/0.35/0.5)

1.11 1.16 1.17

1.10 1.14 1.15

2.60 2.65 2.66

1.20 1.39 1.48

1.15 1.25 1.30

3.71 3.02 2.89

3.39 2.77 2.66

3.74 3.05 2.92

3.47 2.45 1.91

4.10 2.90 2.51

116.6 56.7 43.2

108.3 48.2 34.9

-344.6 -404.5 -418.0

135.9 -34.2 -203.9

103.6 40.1 4.1

0.65 1.16

0.67 1.14

1.72 2.65

0.67 1.39

0.70 1.25

3.31 3.02

3.07 2.77

3.37 3.05

2.65 2.45

3.26 2.90

509.1 56.7

536.5 48.2

-390.6 -404.5

374.0 -34.2

523.2 40.1

1.16 1.16

1.14 1.14

2.65 2.65

1.39 1.39

1.25 1.25

3.27 3.02

3.03 2.77

3.30 3.05

2.62 2.45

3.21 2.90

56.7 56.7

48.2 48.2

-404.5 -404.5

-34.2 -34.2

40.1 40.1

1.12 1.16 1.20

1.10 1.14 1.18

2.45 2.65 2.87

1.38 1.39 1.39

1.20 1.25 1.29

3.07 3.02 2.97

2.83 2.77 2.72

3.10 3.05 2.99

2.45 2.45 2.45

2.97 2.90 2.84

72.5 56.7 42.6

66.9 48.2 31.5

-388.7 -404.5 -418.6

-31.4 -34.2 -36.6

57.4 40.1 24.5

Biomass Productivity (18 g/m2-d) Biomass Productivity (24 g/m2-d) Biomass Productivity (30 g/m2-d) Lipid Conent (0.28) Lipid Conent (0.38) Lipid Conent (0.47) Airlift Efficiency (0.15)

Biocrude Recovery Eff (0.9/0.5/0.75) Biocrude Recovery Eff (0.95/0.65/0.9) CO2 Concentration (0.1) CO2 Concentration (0.94) Cost of CO2 ($20/MT) Cost of CO2 ($0/MT) Stoichiometric N&P (8.1/0.7) Stoichiometric N&P (6.5/0.6) Stoichiometric N&P (4.9/0.4)

73

1.16 1.16 1.16

1.14 1.14 1.14

2.65 2.65 2.65

1.39 1.39 1.39

1.25 1.25 1.25

3.15 3.02 2.89

2.90 2.77 2.65

3.17 3.05 2.92

2.53 2.45 2.36

3.06 2.90 2.75

56.7 56.7 56.7

48.2 48.2 48.2

-404.5 -404.5 -404.5

-34.2 -34.2 -34.2

40.1 40.1 40.1

0.80 1.16

0.76 1.14

1.71 2.65

1.53 1.39

0.71 1.25

2.92 3.02

2.68 2.77

2.95 3.05

2.38 2.45

2.80 2.90

56.7 56.7

48.2 48.2

-404.5 -404.5

-34.2 -34.2

40.1 40.1

1.16 1.16 1.16

1.14 1.14 1.14

2.65 2.65 2.65

1.39 1.39 1.39

1.25 1.25 1.25

3.90 3.02 2.13

3.60 2.77 1.94

3.92 3.05 2.15

3.07 2.45 1.82

3.89 2.90 1.90

56.7 56.7 56.7

48.2 48.2 48.2

-404.5 -404.5 -404.5

-34.2 -34.2 -34.2

40.1 40.1 40.1

Interest (8%) & Loan Term (10 yr)

1.16 1.16

1.14 1.14

2.65 2.65

1.39 1.39

1.25 1.25

4.36 3.02

4.03 2.77

4.39 3.05

3.40 2.45

4.41 2.90

56.7 56.7

48.2 48.2

-404.5 -404.5

-34.2 -34.2

40.1 40.1

Interest (4%) & Loan Term (15 yr)

1.16

1.14

2.65

1.39

1.25

2.46

2.26

2.49

2.06

2.28

56.7

48.2

-404.5

-34.2

40.1

Animal Feed Price ($300/MT)

1.16 1.16 1.16

1.14 1.14 1.14

2.65 2.65 2.65

1.39 1.39 1.39

1.25 1.25 1.25

3.41 3.02 1.83

3.17 2.77 1.59

3.44 3.05 1.86

2.45 2.45 2.45

3.59 2.90 0.86

56.7 56.7 56.7

48.2 48.2 48.2

-404.5 -404.5 -404.5

-34.2 -34.2 -34.2

40.1 40.1 40.1

1.16 1.16 1.16

1.14 1.14 1.14

2.65 2.65 2.65

1.39 1.39 1.39

1.25 1.25 1.25

3.70 3.02 2.33

3.41 2.77 2.13

3.73 3.05 2.36

2.94 2.45 1.96

3.67 2.90 2.14

56.7 56.7 56.7

48.2 48.2 48.2

-404.5 -404.5 -404.5

-34.2 -34.2 -34.2

40.1 40.1 40.1

Operating Days (347)

1.16 1.16

1.14 1.14

2.65 2.65

1.39 1.39

1.25 1.25

3.20 3.02

2.94 2.77

3.22 3.05

2.58 2.45

3.11 2.90

43.8 56.7

32.2 48.2

-400.6 -404.5

-37.5 -34.2

16.0 40.1

Operating Days (360)

1.16

1.14

2.65

1.39

1.25

2.90

2.66

2.93

2.37

2.77

55.7

46.6

-429.8

-40.4

37.6

Labor Rate ($1.7M/yr) Labor Rate ($1.4M/yr) Labor Rate ($1M/yr) Non-Ren vs Tot Energy Impact Non-Ren vs Tot Energy Impact Discount (15%) & Tax (35%) Discount (10%) & Tax (15%) Discount (5%) & Tax (0%) Interest (12%) & Loan Term (5 yr)

Animal Feed Price ($600/MT) Animal Feed Price ($1500/MT) Capital Cost (125%) Capital Cost (100%) Capital Cost (75%) Operating Days (329)

74

References (Reference numbers differ for SI and main manuscript.) 1. 2.

3. 4. 5.

6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18.

19.

20.

21.

Huntley M., et al., Actual large-scale production of marine microalgae for fuels and feed. Algal Research, In Press. Lundquist, T., et al., A realistic technology and engineering assessment of algal biofuel production. 2010, Energy Biosciences Institute, Univerrsity of California: Berkeley, California. p. 178. Ketheesan B. and Mirmalakhandan N., Feasibility of microalgal cultivation in a pilotscale airlift-driven raceway reactor. Bioresource Technology, 2012. 108: p. 196-202. Ketheesan B. and Nirmalakhandan N., Development of a new airlift-driven raceway reactor for algal cultivation. Applied Energy, 2011. 88: p. 3370-3376. Chiaramonti D., et al., Review of energy balance in raceway ponds for microalgae cultivation: Re-thinking a traditional system is possible. Applied Energy, 2013. 102: p. 101-111. Mason P., Dedert Corporation Algae Ring Dryer, Beal C.M., Editor. 2014. KM-TEC, K1 Filter Press, Shell Oil Company, Editor. 2010. Goodall B. and Kadam K., Valicor Conversion Processes, Beal C.M., Editor. 2014, http://www.valicor.com/renewables.aspx. Zhu Y., et al., Development of hydrothermal liquefaction and upgrading technologies for lipid-extracted algae conversion to liquid fuels. Algal Research, 2013. 2: p. 455-464. Thomas H., OpenAlgae Wet Extraction, Beal C.M., Editor. 2014, www.openalgae.com. Beal C.M., et al., Energy Return on Investment for Algal Biofuel Production Coupled with Wastewater Treatment. Water Environment Research, 2012. 84(9): p. 692-710. EPA, U.S., Technology characterization: reciprocating engines. 2008: Washington DC. Turton R., et al., Analysis Synthesis and Design of Chemical Processes. 1998. Nehring R. Fertilizer Use and Price, USDA. 2013 [cited 2014 2014]; Available from: http://www.ers.usda.gov/data-products/fertilizer-use-and-price.aspx#.U_t5GvldVWE. Alibaba. Chemical Market Prices. 2014 2014]; Available from: http://www.alibaba.com. Beal C.M., et al., Comprehensive Evaluation of Algal Biofuel Production: Experimental and Target Results. Energies, 2012. 5(6): p. 1943-1981. Fischer Scientific. Hexanes. 2014; Available from: http://www.fishersci.com. US Energy Information Administration. Table 5.6.A Average Retail price of Electricity to Ultimate Customers by End-Use Sector, by State, June 2014 and 2013. 2014 2014]; Available from: http://www.eia.gov/electricity/monthly/epm_table_grapher.cfm?t=epmt_5_6_a. Austin Energy. Austin City Council Approves New Wind Contract to Reach Renewable Energy Goal. 2014; Available from: http://austinenergy.com/wps/portal/ae/about/news/press-releases/austin-city-councilapproves-new-wind-contract-to-reach-renewable-energy-goal/. Delucchi M.A. and Jacobson M.Z., Providing all global energy with wind, water, and solar power, Part II: Reliability, system and transmission costs, and policies. Energy Policy, 2011. 39: p. 1170 - 1190. US Energy Information Administration. Table ET1. Primary Energy, Electricity, and Total Energy Price and Expenditure Estimates, 1970-2012, Texas/Hawaii. 2014 2014]; Available from: http://www.eia.gov/state/seds/data.cfm?incfile=/state/seds/.

75

22.

23. 24.

25. 26. 27.

28. 29.

US Energy Information Administration. Cushing, OK WTI Spot Price FOB, Crude Oil. 2014 2014]; Available from: http://www.eia.gov/dnav/pet/hist/LeafHandler.ashx?n=PET&s=RWTC&f=D. World Bank. Global Economic Monitor (GEM) Commodities. 2014 2014]; Available from: http://databank.worldbank.org/data/databases/commodity-price-data. Nebraska Ethanol Board Nebraska Energy Office. Ethanol and Unleaded Gasoline Average Rack Prices. 2014 [cited 2014 2014]; Available from: http://www.neo.ne.gov/statshtml/66.html. Frischknecht R., et al., The ecoinvent database: Overview and Methodological Framework. International Journal of Life Cycle Assessment, 2005. 10: p. 3-9. RS Means Heavy Construction Cost Data, BNI News General Construction 2012 Costbook. 2012. Lautier, A., et al., Development of normalization factors for Canada and the United States and comparison with European factors. Science of The Total Environment, 2010. 409(1): p. 33-42. Jolliet O., et al., IMPACT 2002+: A new life cycle impact assessment methodology. International Journal of Life Cycle Assessment, 2003. 8(6): p. 324-330. Goedkoop M., et al., ReCiPe 2008, Ruimte en Milieu., Editor. 2013.

76