Carbelim
Microalgae Carbon Capture CalculatorSequestration Estimator
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Live0.60 t CO₂/yr
🌿Adjust any parameter — outputs update in real time. Defaults match the Carbelim study report (PRO15 / 500 L).
Real-timev2.0V·P·τ·D·η

Live Results

Updates live on every input change
Annual CO₂ Sequestration
602.1
kg CO₂ per year
0.60tonnes/yr
≈ 26.8 mature oak trees absorbing CO₂ for a year
Offsets 3,627 km of passenger-car driving
Monthly Capture
50.2
kg CO₂ / month
Daily CO₂ Capture
1,649.7
g CO₂ / day
Daily Biomass Yield
0.900
kg dry mass / day
Annual Biomass
328.5
kg dry mass / year
Annual O₂ Released
437.9
kg O₂ / year
Oak Tree Equivalent
26.8
mature oak trees
System Summary

A 500 L flat-panel PBR at OD 3.00 (effective productivity 1.80 g/L/day), operating under the Standard scenario for 365 days/yr at 100% efficiency, will sequester approximately 0.60 t CO₂ annually, release 437.9 kg O₂, and yield around 328.5 kg of dry algal biomass — equivalent to 26.8 mature oak trees.

01

Sensitivity analysis

OD vs Annual CO₂ CaptureVolume & Days held constant
Volume vs Annual CO₂ CaptureOD & Days held constant · log scale
02

Methodology & assumptions

1 · Core Model Equation

YCO₂ (kg yr⁻¹) = V (L) × P (g·L⁻¹·d⁻¹) × τ × D (days) × η / 1000
VWorking volume of the flat-panel photobioreactor in litres. Default 500 L corresponds to the Carbelim PRO15 culture volume (~495 L in a 500 L tank).
PVolumetric biomass productivity in g·L⁻¹·d⁻¹ (dry weight). Derived from optical density via the calibration P = k × OD, where k = 0.6 maps OD₆₈₀ to measured productivity. At the default OD = 3.0 and k = 0.6, P = 1.8 g·L⁻¹·d⁻¹ — matching the Carbelim study report's validated measurement on the 60 L reference system.[1, 11]
ODOptical density at 680 nm — the chlorophyll a absorption peak. Used as a linear proxy for volumetric biomass concentration under Beer–Lambert conditions (valid for OD₆₈₀ 0–4 in well-mixed cultures).[1, 4]
τCO₂ fixation stoichiometry: 1.833 kg CO₂ per kg dry biomass (= 0.50 × 44.01/12.01). Consistent with the study report's value.[8, 9, 11]
DOperating days per year. Default 365 = continuous operation, matching the study report's annual projection (daily rate × 365).[11]
ηSystem efficiency (0–1). Accounts for scheduled downtime, harvest losses, evaporation, self-shading at high OD, and respiratory CO₂ release (typically 15–25% of gross fixation). Default 100% matches the report's raw-productivity baseline; reduce to 70–90% for real-world annual estimates.[2, 8]

2 · Productivity Scenarios (k calibration)

The calibration constant k translates OD₆₈₀ into volumetric biomass productivity (P = k × OD). The three scenarios bracket the performance range documented in the Carbelim study report and peer-reviewed pilot studies:

Scenariok valueP at OD 3ConditionsRefs
Conservative0.501.5 g/L/dayPAR <150 µmol m⁻² s⁻¹, suboptimal CO₂ supply, non-optimised wild-type strains[2, 6]
Standard0.601.8 g/L/dayValidated Carbelim reference — PRO15 measured productivity at OD 3, CO₂ sparging, controlled pH 7–8[3, 5, 11]
Optimised0.702.1 g/L/dayHigh-PAR (>300 µmol m⁻² s⁻¹), 5–10% CO₂-enriched sparging, selected/engineered strain, automated pH control[3, 7]

3 · CO₂ Fixation Stoichiometry

τ = Cfrac × (MCO₂ / MC) = 0.50 × (44.01 / 12.01) = 1.833 kg CO₂ kg⁻¹ dry biomass

Microalgal dry biomass contains approximately 48–52% carbon by mass across commonly cultivated genera — Chlorella, Scenedesmus, Nannochloropsis, and Spirulina.[1, 8] The representative empirical formula CH₁.₈O₀.₅N₀.₂ implies a carbon mass fraction of 48.8%, yielding τ ≈ 1.79–1.83 kg CO₂/kg.[9] The value τ = 1.833 (50% C assumption) is consistent with the Carbelim study report and the de facto standard in microalgae life-cycle assessment literature.[8, 9, 11]

O₂ Release Stoichiometry

O₂ (kg/yr) = YCO₂ × (MO₂ / MCO₂) = YCO₂ × (32 / 44) = YCO₂ × 0.727

Photosynthesis releases O₂ stoichiometrically with CO₂ fixation. The Carbelim study report uses this ratio to compute annual O₂ output alongside CO₂ capture.[11]

4 · Operating Envelope & Constraints

  • OD₆₈₀ 0–4: Chlorophyll a absorbs maximally near 680 nm; the Beer–Lambert linear relationship between OD and biomass concentration holds in well-stirred suspensions up to OD₆₈₀ ≈ 4. Beyond this threshold, mutual shading limits productive culture depth and the linear model overestimates CO₂ fixation.[4]
  • PAR ≥ 200 µmol photons m⁻² s⁻¹: Light saturation for photoautotrophic growth typically falls in the range 150–350 µmol m⁻² s⁻¹ depending on species and acclimation state. Below this threshold, photosynthetic rate and CO₂ fixation drop non-linearly (photolimitation regime).[5, 6]
  • Flat-panel geometry: Flat-panel PBRs offer surface-to-volume ratios of 80–300 m² m⁻³, outperforming tubular reactors (30–80 m² m⁻³) and open raceways (<10 m² m⁻³), enabling the higher volumetric productivities underpinning the model.[5, 7]
  • System efficiency η: The default 100% represents the report's raw-productivity baseline. Outdoor systems under variable irradiance typically achieve η ≈ 60–80%; factoring in seasonal variation and non-productive periods (cleaning, harvest, maintenance) brings realistic annual η to 70–90%.[2, 3]

5 · CO₂ Equivalence Metrics

CO₂ capture is expressed via two equivalence benchmarks:

Treesequiv = YCO₂ (kg) / 22.44 kg tree⁻¹ yr⁻¹

A mature oak tree absorbs approximately 22.44 kg CO₂/year. This figure is adopted from the Carbelim study report (Kumar 2026).[11]

doffset (km) = YCO₂ (kg) / 0.166 kg km⁻¹

The factor 0.166 kg CO₂ km⁻¹ (= 166 g CO₂ km⁻¹) is derived from the IEA Global Fuel Economy Initiative 2021 report, documenting a global average of 167 g km⁻¹ for new light-duty vehicles.[10]

6 · Model Scope & Limitations

  • OD as biomass proxy: OD₆₈₀ is sensitive to cell size, pigmentation, and suspended debris. A strain-specific OD-to-dry-weight calibration curve is required for quantitative pilot validation.
  • Linear volume scaling: The model assumes constant CO₂ uptake per unit volume. Real systems experience light attenuation at high volume with fixed illumination area — estimates for V > 2,000 L with fixed lighting should be treated as upper bounds without proportional illumination scaling.
  • k calibration uncertainty: The default k = 0.6 is calibrated to the Carbelim PRO15 reference system. Different strains, reactor geometries, and growth conditions may require k recalibration (±20–30%).
  • Steady-state assumption: The model assumes continuous or semi-continuous operation at constant OD. Batch or fed-batch systems will yield lower effective annual capture due to lag and stationary phases.
  • Energy & cost: The study report includes energy (kWh) and cost (₹) per product model; these are product-specific values that do not scale with volume and are not computed by this calculator.
All estimates carry ±20–30% uncertainty at laboratory/pilot scale. This tool is intended for preliminary sizing and scenario comparison — not for bankable yield guarantees. Independent pilot-scale validation is recommended before commercial investment.

References

  1. Chisti, Y. (2007). Biodiesel from microalgae. Biotechnology Advances, 25(3), 294–306. https://doi.org/10.1016/j.biotechadv.2007.02.001
  2. Acién, F.G., Fernández, J.M., Magán, J.J., & Molina, E. (2012). Production cost of a real microalgae production plant and strategies to reduce it. Biotechnology Advances, 30(6), 1344–1353. https://doi.org/10.1016/j.biotechadv.2012.02.005
  3. Slegers, P.M., Wijffels, R.H., van Straten, G., & van Boxtel, A.J.B. (2011). Design scenarios for flat panel photobioreactors. Applied Energy, 88(10), 3342–3353. https://doi.org/10.1016/j.apenergy.2010.12.037
  4. Ugwu, C.U., Aoyagi, H., & Uchiyama, H. (2008). Photobioreactors for mass cultivation of algae. Bioresource Technology, 99(10), 4021–4028. https://doi.org/10.1016/j.biortech.2007.01.046
  5. Posten, C. (2009). Design principles of photo-bioreactors for cultivation of microalgae. Engineering in Life Sciences, 9(3), 165–177. https://doi.org/10.1002/elsc.200900003
  6. Wijffels, R.H., & Barbosa, M.J. (2010). An Outlook on Microalgal Biofuels. Science, 329(5993), 796–799. https://doi.org/10.1126/science.1189003
  7. Molina, E., Fernández, J., Acién, F.G., & Chisti, Y. (2001). Tubular photobioreactor design for algal cultures. Journal of Biotechnology, 92(2), 113–131. https://doi.org/10.1016/S0168-1656(01)00353-4
  8. Lardon, L., Hélias, A., Sialve, B., Steyer, J.-P., & Bernard, O. (2009). Life-Cycle Assessment of Biodiesel Production from Microalgae. Environmental Science & Technology, 43(17), 6475–6481. https://doi.org/10.1021/es900705j
  9. Williams, P.J. le B., & Laurens, L.M.L. (2010). Microalgae as biodiesel & biomass feedstocks: Review & analysis of the biochemistry, energetics & economics. Energy & Environmental Science, 3(5), 554–590. https://doi.org/10.1039/b924978h
  10. IEA (2021). Global Fuel Economy Initiative 2021. International Energy Agency, Paris. https://www.iea.org/reports/global-fuel-economy-initiative-2021
  11. Carbelim (2026). Microalgae-Based Carbon Capture Using Photobioreactors: A Comprehensive Study Report. Carbelim Technologies. Internal validated reference for PRO15 productivity (1.8 g/L/day), CO₂ stoichiometry (1.833), and oak-tree equivalence (22.44 kg CO₂/tree/yr).