The Document That Determines Whether a Business Exists
A techno-economic analysis (TEA) is a quantitative model that estimates the cost of producing a product at a specified scale, using a specified technology, under specified market conditions. For microalgae, a TEA answers one question that all others depend on: can this be produced at a cost that allows the business to sell at a price the market will accept, with a margin sufficient to justify the investment?
The TEA is not the same as a business plan, a feasibility study, or a pitch deck financial model. Those documents are written with an audience in mind and can reflect aspirations. A TEA is a technical document grounded in engineering mass balances, equipment costs, and operating data — it is as right or wrong as its assumptions. A TEA that uses optimistic productivity assumptions, underestimates capital costs, or ignores harvesting energy will produce a cost estimate that looks commercially viable and predicts an outcome that is not. The graveyard of algae startups is partly a graveyard of TEAs that were not done honestly.
The most widely referenced TEA framework for microalgae is produced by the National Renewable Energy Laboratory (NREL) in the United States. Their algae TEA models — available publicly at nrel.gov — are the reference point the field uses to compare claims. When you encounter a cost figure for algae production, the first question is: how does it compare to the NREL model under equivalent assumptions? If it is dramatically lower, that is a signal to look at the assumptions with care, not to celebrate.
This module teaches three things: how to read a published TEA critically, what the universal cost drivers are, and how to build a simplified TEA for a SustaBloom scenario using publicly available benchmarks.
What Goes Into the Model
Every credible algae TEA follows the same basic structure: a process description, a mass and energy balance, a capital cost estimate, an operating cost estimate, and a financial analysis that converts those inputs into a minimum selling price (MSP) or minimum cost of sustainable production (MCSP). Each step feeds the next, and errors in early steps compound through the analysis.
Every TEA should report a minimum selling price (MSP) or minimum cost of sustainable production (MCSP) in $/kg (or $/tonne) of the target product. This single number is the one to compare to current market prices. If a paper reports only $/kg biomass but not $/kg product, convert using the product content percentage (e.g. if astaxanthin is 2% of biomass and biomass costs $8/kg, astaxanthin production cost is at minimum $400/kg — before extraction efficiency losses).
These Four Variables Appear in Every Credible Algae TEA
Across the dozens of algae TEA models published since NREL's 2010 baseline work, four cost drivers appear in every analysis as the dominant determinants of production cost. They are not all equally controllable, but understanding them determines what questions to ask about any algae project.
NREL Benchmark: Open Raceway Pond Cost Breakdown
The NREL 2020 harmonised TEA model for open raceway ponds at demonstration scale (100 dry tonnes/year) produces a baseline MCSP of approximately $7.50–9.50/kg dry biomass at 25 g/m²/day productivity. At 100× scale (10,000 dry tonnes/year), economies of scale reduce MCSP to approximately $2.50–4.50/kg. These are the reference numbers; any project claiming significantly lower cost at equivalent scale deserves detailed assumption scrutiny.
Indian labour costs are 60–75% lower than NREL's US reference rate; land costs in Tamil Nadu and Gujarat are substantially lower than US desert southwest reference sites. These adjustments reduce the MCSP meaningfully — Indian Spirulina producers achieve $5–15/kg dry biomass commercially, which is consistent with applying Indian cost factors to an NREL-style model. The capital cost and CO₂ cost components are less location-advantaged because PBR and centrifuge equipment is largely imported and CO₂ pricing depends on industrial partnerships.
What to Look For Before Trusting a Number
A cost of $0.50/kg algae biomass. A cost of $15.00/kg algae biomass. Both appear in the peer-reviewed literature. Both can be correct under their respective assumptions. Understanding which set of assumptions is realistic for your context is the skill this section teaches.
What productivity is assumed, and how does it compare to demonstrated outdoor performance?
The most common source of optimistic TEA results is an assumed productivity that has been demonstrated in controlled lab conditions but not at commercial outdoor scale. The NREL harmonised framework (Venteris et al., 2014) collated outdoor productivity data from 30+ sites globally and found median performance of 14–18 g/m²/day for Chlorella, 10–16 g/m²/day for Nannochloropsis, against lab claims of 25–40 g/m²/day. If a TEA assumes 30 g/m²/day for an outdoor system, ask for the site-specific outdoor productivity data that supports this. If none exists, apply a 60% discount to get a realistic operating estimate.
What is the CO₂ source and what cost is assigned to it?
NREL's reference model uses $0/tonne CO₂ from flue gas. Many project TEAs do the same even when no industrial flue gas source is confirmed or available nearby. If a project is not co-located with a confirmed CO₂ source, the CO₂ cost should be modelled at market rate ($50–200/tonne). A 100 t/year biomass system using $100/tonne CO₂ adds approximately $18,000/year in CO₂ cost alone — small at that scale, but significant when multiplied to 10,000 t/year commercial scale. Ask specifically: is there a confirmed CO₂ off-take agreement with an industrial partner, or is this a model assumption?
What harvesting method is used, and what is the assumed recovery and energy cost?
TEAs vary significantly in how they treat harvesting: some use centrifugation (high energy, high cost, high recovery at 95–98%), some use flocculation (lower energy, lower cost, but recovery 70–85% and potential product contamination), some use a hybrid (flocculation pre-concentration + centrifuge polish). A TEA that assumes flocculation-only for a food-grade product is likely understating harvesting cost and overstating product quality. The harvesting assumption should be consistent with the product specification — you cannot use low-cost harvesting for a premium food-grade extract without a detailed argument for how contamination is managed.
What scale is the TEA modelled at, and has economies of scale been properly accounted for?
Production costs in capital-intensive industries follow a 0.6–0.7 power law with respect to scale: doubling capacity typically increases capital cost by 50–60%, not 100%. TEAs at demonstration scale (100 t/year) will show much higher MCSP than commercial scale (10,000 t/year). Many project proposals take commercial-scale MCSP numbers from published TEAs and claim them for a much smaller planned facility — a category error. The MCSP reported in a published TEA is valid only for the scale modelled. Scaling down significantly increases cost per unit.
Does the TEA include extraction costs, or only biomass production costs?
A TEA that produces a cost of $3/kg dry biomass is not the same as a TEA that produces a cost of $3/kg astaxanthin. The extraction step — cell disruption, SC-CO₂ or solvent extraction, purification, drying — adds substantial cost. SC-CO₂ extraction for astaxanthin at pilot scale adds $500–2,000/kg astaxanthin in equipment depreciation and operating costs. Many published biomass TEAs stop at the dried powder stage and leave extraction costs for a separate analysis. When evaluating a project, confirm whether the quoted cost is biomass production cost or end-product cost, and add extraction costs explicitly if they are not included.
Has a sensitivity analysis been conducted, and what is the sensitivity to the top two variables?
A credible TEA always includes a sensitivity analysis. The standard presentation is a tornado diagram: the most sensitive assumption at the top, least sensitive at the bottom. In virtually every algae TEA, biomass productivity and capital cost are the top two. If a TEA claims a cost of $X/kg but shows in its sensitivity analysis that a 20% reduction in productivity increases MCSP by 40%, then $X is not a safe planning number — it is a best-case number. The planning number should be the MCSP at the productivity achievable with 80% confidence, not the productivity demonstrated at best-case lab conditions.
Sensitivity Analysis — How Each Variable Moves MCSP
| Assumption | Base case value | Pessimistic (-30%) | Optimistic (+30%) | MCSP impact | Priority |
|---|---|---|---|---|---|
| Biomass productivity | 25 g/m²/day | 17.5 g/m²/day → MCSP ×1.6–1.8 | 32.5 g/m²/day → MCSP ×0.65 | ±35–50% on MCSP | Highest priority |
| Total installed capital (TIC) | $28M / 100 ha | +30% → MCSP +20–25% | -30% → MCSP -18–22% | ±20–25% on MCSP | Highest priority |
| CO₂ cost | $50/tonne | $200/tonne → MCSP +18–22% | $0/tonne (flue gas) → MCSP -15% | ±15–22% on MCSP | High priority |
| Harvesting recovery | 90% recovery | 75% recovery → MCSP +12% | 95% recovery → MCSP -5% | ±5–12% on MCSP | Medium priority |
| Energy cost | $0.08/kWh | $0.12/kWh → MCSP +8% | $0.05/kWh → MCSP -5% | ±5–8% on MCSP | Lower priority |
| Labour cost | $50k/FTE/yr (US) | +30% → MCSP +4% | -30% (India context) → MCSP -12% | ±4–12% on MCSP | Location-dependent |
| Lipid/product content | 25% DW lipid | 15% → cost/kg product ×1.7 | 35% → cost/kg product ×0.7 | ±35–40% on $/kg product | Product-specific |
From Concept to Cost Estimate in Five Steps
A full NREL-style TEA with detailed equipment costing and financial modelling takes months to build and requires process engineering expertise. A simplified TEA — sufficient to test whether a business concept is in the right economic neighbourhood — can be built in hours using publicly available benchmarks. Here is the method, applied to two specific SustaBloom scenarios.
The simplified approach uses four inputs: productivity (g/m²/day or g/L/day), scale (total cultivation area or volume), a reference cost benchmark (from NREL or published Indian data), and product content (% DW of target compound). From these, you derive: total biomass production (tonnes/year), production cost (₹/kg biomass using Indian-adjusted benchmarks), and minimum product cost (₹/kg product before extraction). You then compare this to market price. If the gap is large, the concept needs either scale or productivity improvement before it is viable. If the gap is small, a full TEA is worth commissioning.
Market price for food-grade phycocyanin (A620/A280 ≥ 0.4): ₹8,000–40,000/kg depending on purity grade. Gap is substantial — this scenario is viable. A 0.5 ha pilot generating ~3.9 t/yr phycocyanin raw extract, with even 50% sold at food grade (₹8,000/kg), generates ~₹1.56 crore revenue against ~₹60 lakh production cost. The economics work at this scale before any optimisation.
Market price for natural astaxanthin (≥10% astaxanthin in extract): $2,000–4,500/kg. Gap exists but is tight at pilot scale. Viability requires scaling to reduce capital depreciation per kg. At 100,000 L PBR (100×), production cost falls to ₹400–600/kg biomass due to economies of scale, improving astaxanthin cost to ₹25,000–35,000/kg ($300–420/kg) — comfortably profitable. This scenario requires a scale-up capital commitment before it is viable; the pilot itself will operate at or near breakeven.
This is the difference between using a TEA as a presentation tool and using it as a thinking tool. Every algae startup should have a live TEA spreadsheet, not a static slide, updated quarterly as real productivity data comes in. The moment actual outdoor productivity diverges from the model assumption, the MCSP changes — and the business decision changes with it. A founder who says "our TEA shows $3/kg" without knowing which assumptions drive that number, and how the number changes if productivity falls 20%, is not running a TEA. They are running a rounding exercise on someone else's optimism.
Check 1 — Productivity assumption: To reach $0.80/kg, a model almost certainly requires productivity in the range of 30–40 g/m²/day or higher — at the top end or beyond what has been consistently demonstrated outdoors for Nannochloropsis. The NREL harmonised outdoor dataset shows Nannochloropsis achieving 10–18 g/m²/day at most sites under realistic conditions. If this paper uses 35 g/m²/day, that is a laboratory-maximum figure, not a commercial planning figure. Applying a 60% outdoor correction to 35 g/m²/day gives 21 g/m²/day — still above median outdoor performance. Ask: was this productivity achieved in an outdoor pilot at the reference location, or derived from indoor measurements?
Check 2 — CO₂ cost: At $0/tonne (flue gas), a substantial cost item disappears from the model. If the TEA assumes free CO₂ from an industrial partner and that partner is not confirmed, the actual CO₂ cost at $100–150/tonne would add $0.18–0.30/kg to production cost, raising the MCSP to $0.98–1.10/kg before any other adjustments.
Check 3 — Scale: $0.80/kg is plausible only at very large scale — perhaps 1,000–10,000 ha — where capital depreciation per kg is reduced by economies of scale. At 100 ha scale (a realistic initial commercial facility), NREL's model produces $2.50–4.50/kg. Check the modelled scale; if it is above 500 ha for a "demonstration" TEA, the cost is being quoted for a commercial-scale facility and should not be applied to a smaller project.
Check 4 — Harvesting: What harvesting method and what energy cost? To achieve $0.80/kg, harvesting cost must be modelled at $0.10–0.20/kg — achievable only with gravity settling or low-efficiency flocculation, not centrifugation. If the target product is food-grade EPA, centrifugation is required, and harvesting cost alone is $0.50–1.50/kg.
Check 5 — System boundary: Does the $0.80/kg include extraction, drying, and downstream processing? Or is it only the cultivation and harvesting cost? Most low-cost TEA claims stop at dried biomass powder and exclude extraction. If EPA oil is the target product, add $1.00–3.00/kg oil for extraction and refining.
What you are likely to find: The $0.80/kg figure is real within its model assumptions, but those assumptions involve either very large scale (5,000+ ha), free CO₂, productivity above 30 g/m²/day, and inexpensive harvesting — none of which are available simultaneously to a new Indian algae producer. A realistic India-adjusted MCSP for Nannochloropsis at 50–100 ha pilot scale is ₹250–500/kg dry biomass ($3–6/kg), not $0.80/kg. This is a 4–7× discrepancy that would make a project commercially non-viable if the market price is based on the $0.80/kg benchmark.
Step 1 — Total annual biomass: 20 g/m²/day × 10,000 m² (1 ha) × 365 days × 10⁻⁶ = 73 tonnes dry biomass per year.
Step 2 — Total biomass production cost: 73,000 kg × ₹200/kg = ₹1.46 crore per year.
Step 3 — Protein available (pre-extraction): 73,000 kg × 45% = 32,850 kg protein in biomass.
Step 4 — Extracted protein (accounting for extraction yield): 32,850 kg × 70% recovery = 22,995 kg protein concentrate per year, approximately 23 tonnes/year.
Step 5 — Minimum protein cost: ₹1.46 crore ÷ 22,995 kg = ₹635/kg protein concentrate, before extraction equipment cost and operating cost. Add extraction cost (alkaline extraction + precipitation + drying — approximately ₹100–200/kg at this scale) = ₹735–835/kg total production cost for protein concentrate.
Does it close? No. The market price of ₹400/kg for Chlorella protein concentrate for animal feed is below the minimum production cost of ₹735–835/kg by nearly 2×. The gap has three possible solutions: (1) increase scale significantly — at 10 ha (10× larger), capital depreciation per kg falls and production cost may drop to ₹400–500/kg, closing the gap; (2) improve productivity — if productivity reaches 30 g/m²/day instead of 20, the annual output increases by 50% while most fixed costs stay constant, reducing cost per kg; (3) change the target market — human food-grade Chlorella protein or nutraceutical-grade product commands ₹800–2,000/kg, at which point the 1 ha scenario becomes viable. Animal feed at ₹400/kg is the wrong market for a small, high-cost producer. This is the scenario where the simplified TEA does its job: it prevents a ₹1.5 crore capital investment in a facility that cannot produce a profit at the intended product price and scale. The conclusion is not "don't do this" — it is "don't do this at this scale, at this price point, targeting this market."
Why it is systematically underestimated: The NREL reference model — which most subsequent algae TEAs cite or build on — explicitly assumes co-location with an industrial CO₂ source (power plant, ethanol fermentation facility, cement plant) where flue gas CO₂ is available at $0/tonne marginal cost. This assumption is appropriate for a specific facility configuration but does not represent the general case for a standalone algae producer. When subsequent TEAs cite the NREL model as their reference without noting this assumption, they inherit a $0/tonne CO₂ cost that may be unrealistic for their specific context. It is also simply easier to model free CO₂ than to negotiate an off-take agreement, so many TEAs use $0/tonne as a convenient placeholder rather than a committed reality.
The quantitative impact: Algae require approximately 1.8 kg CO₂ per kg dry biomass from stoichiometry; real-world systems with losses in the delivery system require 2.0–2.5 kg CO₂/kg biomass. At 100 tonnes biomass/year and CO₂ at $100/tonne: 100,000 kg × 2.2 kg CO₂/kg × $100/1,000 kg = $22,000/year. At 10,000 tonnes/year commercial scale: $2.2 million/year in CO₂ cost alone. At $0/tonne (flue gas assumption), this cost disappears — a $2.2M/year discrepancy that can make the difference between a viable and non-viable commercial model.
What a realistic CO₂ strategy looks like for an Indian producer: There are three credible approaches. First, co-location with an industrial CO₂ source — a steel plant, cement kiln, or ethanol fermentation facility. India has significant industrial CO₂ sources (sugar mill fermentation in Maharashtra and UP produces large volumes of food-grade CO₂; cement plants in Rajasthan and Andhra Pradesh produce flue gas CO₂). Negotiating a CO₂ off-take agreement with a confirmed industrial partner before commissioning the algae facility is the right approach — but it takes 6–18 months and requires the industrial partner to be interested in the arrangement. Second, atmospheric supplementation for small-scale systems: at pilot scale (under 0.5 ha), CO₂ from the atmosphere plus bicarbonate supplementation may be sufficient for Spirulina (which tolerates alkaline, bicarbonate-buffered media better than other species), avoiding bottled CO₂ cost. Third, for medium-scale systems without a confirmed industrial CO₂ source, budget $80–120/tonne for purchased CO₂ explicitly in the TEA and don't model it as free. A TEA that shows viability with purchased CO₂ at market rate is more credible to investors than one that assumes free CO₂ from an industrial partner that hasn't been contracted.
What MCSP is: The minimum cost of sustainable production (MCSP), also called minimum selling price (MSP) in some frameworks, is defined as the price at which the net present value (NPV) of the project equals zero — the price at which total discounted revenue exactly equals total discounted costs over the project lifetime, including the return on invested capital. In simpler terms: it is the price you must charge to recover every cost the project will ever incur, at your required rate of return, over its operating life. If you charge above MCSP, the project generates positive NPV and is worth doing. If you charge below MCSP, you are destroying value even if the annual P&L looks positive — because you are not recovering your capital at an acceptable rate.
How it is calculated: The MCSP calculation requires: (1) total capital cost (CapEx) including installation and indirect costs; (2) annual operating costs (OpEx) broken into fixed and variable components; (3) a discount rate (typically 10–15% for early-stage industrial projects); (4) project life (typically 20–30 years for infrastructure); (5) assumed depreciation schedule, debt/equity split, and tax rate. These are fed into a discounted cash flow model. The MSP is the revenue per unit of output that makes the NPV of the project equal to zero — solved iteratively. A project with CapEx of $10M and OpEx of $2M/year producing 500 tonnes/year with a 20-year life at 10% discount rate might have an MCSP of $8.50/kg. If the market price is $12/kg, the project has a positive NPV and is worth investing in.
Why it is more useful than simple production cost: Simple production cost (OpEx ÷ annual output) ignores capital recovery entirely. A project that appears to have a $2/kg production cost but required $50M in CapEx to build is not actually a $2/kg product — when capital is properly amortised, the true MCSP might be $7–10/kg. Many algae production cost claims in startup pitch materials are operating cost estimates that ignore capital depreciation — the single largest cost component. MCSP forces capital recovery into the analysis, producing a number that reflects the full economic reality. When comparing two algae production approaches with different capital intensities (open raceway vs PBR, for example), MCSP is the correct comparison metric — it captures both the lower operating cost of one system and the higher capital cost of another in a single number that can be directly compared to market price.
Where to focus operational effort: Productivity is the dominant variable by a large margin — ±45% MCSP sensitivity vs ±22% for capital and ±8% for CO₂. This means that $1 invested in productivity improvement (better strain selection, optimised stress induction protocol, CO₂ delivery optimisation to reduce light limitation) generates 2× the return on MCSP as $1 invested in capital cost reduction, and 5× the return as $1 invested in CO₂ cost reduction. Operational effort should prioritise: (1) optimising the two-stage cultivation protocol for maximum astaxanthin yield per litre per day, (2) reducing downtime from contamination events that reduce effective annual productivity, and (3) monitoring and tightly controlling stress induction timing — the single biggest process variable for Haematococcus astaxanthin content.
Where to focus capital allocation: Capital cost is the second-largest sensitivity (±22%), and it is a one-time decision. The best leverage comes from: (1) deferring non-critical equipment until after scale-up — a pilot facility does not need the full commercial-scale extraction train; (2) evaluating whether any equipment can be shared with or leased from an existing food processing or pharmaceutical facility nearby, reducing owned CapEx; (3) sourcing PBR components from Indian manufacturers or fabricators where possible — PBR tubular systems can be fabricated locally at 30–50% of the cost of imported German or Israeli equipment if the right engineering support is available.
Stress-test MCSP under a pessimistic scenario: Pessimistic scenario: productivity at -30% of base case (system achieves 70% of planned productivity due to outdoor variability, monsoon interruptions, and contamination events); capital cost at +30% (equipment costs higher than estimated, additional civil works required). Apply both simultaneously: MCSP × 1.45 (productivity effect) × 1.22 (capital effect) = MCSP × 1.77 = $1,800 × 1.77 = $3,186/kg.
This is above the current market price of $2,500/kg — meaning the project is not viable under the simultaneous pessimistic scenario. This is the critical finding from the stress test. The project has a positive margin in the base case ($700/kg contribution), but that margin is entirely consumed by two realistic downside scenarios occurring together. The business decision this suggests: either (a) secure a long-term offtake agreement at $3,500–4,000/kg (premium quality, certified natural, contracted supply — achievable in the Japanese nutraceutical market), which protects revenue even in the pessimistic scenario; or (b) reduce CapEx below the model base case by 20% (through local fabrication and phased investment) to create more headroom before building. A project that only works in the optimistic scenario is not investment-grade; this analysis shows what it would take to make it robust.