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Yanhui Yuan, Ryan Adams, Laura Belicka, Josee Bouchard, Kofi Dalrymple, Harlan L Miller III,

William Porubsky, Ed Malkiel, Karl Ziegler, and Ron Chance

Algenol Biofuels, Fort Myers, Florida

ABO Summit

October 1, 2014

A Cyanobacteria-Based Photosynthetic Process for Bioethanol Production:

Modeling of Productivities in Laboratory and Outdoor Photobioreactors

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Algenol Overview

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Advanced Industrial

Biotechnology CompanyCommercializing Direct To

Ethanol ® Technology

Research and Development

Facilities

Started up in 2006

Headquartered in Fort

Myers, Florida

200 employees including

70 with advanced

degrees

Process Development UnitFort Myers Research Labs

Algenol Overview

$200M equity capital

$25M Department of

Energy Integrated

Biorefinery grant

$10M economic

development grant from

Lee County, FL

60,000 ft2 of Research

and Development lab

space in Fort Myers and

Berlin, Germany

4 acre Process

Development Unit (PDU)

36 acre Integrated Bio-

Refinery (IBR)

Integrated Biorefinery

[Paul Woods & Ed Legere]

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Energy efficiency is critical

for economics and for low

carbon footprint

Water-ethanol mixture is sent to

patented downstream processing

equipment that provides a 10-fold

increase in concentration, then on

to fuel grade

Spent algae are processed into a

bio-crude that can be refined into

diesel, gasoline, and jet fuel

Cyanobacteria are grown in

saltwater contained in

proprietary PBRs that are

exposed to the sun and are

fed CO2 and nutrients.

Technology Overview

Algenol's Direct to Ethanol® process has three key components:

Proprietary cyanobacteria

make ethanol and biomass

directly from CO2, water,

and sunlight.

2013 ethanol productivity > 8000

gal/acre-yr (gepay)

2014 target 7,000 gepay

“annualized”

A Very Productive Algal

Platform

Specialized VIPER™

Photobioreactors

Energy Efficient

Downstream Processing

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Process Scale-up in 2013 at the IBR

40 Block 400 Block 4000 Block

First Inoculation February 6

4000 Module

10 x Scale Up

First Inoculation March 15 First Inoculation July 19

Still in operation

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Biology and Productivity Modeling

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Metabolic Pathway for Ethanol Production

Enhanced ethanol production via over-expression of fermentation pathway enzymes

• Pyruvate decarboxylase (PDC) and alcohol dehydrogenase (ADH) are found widely

in nature

• PDC catalyzes the non-oxidative decarboxylation of pyruvate to produce

acetaldehyde

• ADH converts acetaldehyde to ethanol

• Ethanol diffuses from the cell into the culture medium and accumulates for eventual

harvesting

2 CO2 + 3 H2O C2H5OH + 3 O2

Metabolically enhanced cyanobacteria: key proprietary component of the Algenol

technology

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Photosynthetic Efficiency and Productivity Targets

Ethanol Production Target

• Algenol target is >7000 gal ethanol/acre-yr

• Corn is about 400 gal/acre-yr; sugarcane about 1000

• 2013 actual outdoor production exceeded 8000 gal/acre-yr at Algenol’s Florida facility

• Target and recent results corresponds to 2-3% solar energy conversion efficiency (all % referenced to average US solar radiation)

• Efficiency similar to commercial biomass conversion for Chlorella (food supplements) as well as more conventional crops

• Absolute theoretical limit (8 photons per C fixed) is about 30,000 gal/acre-yr of ethanol

Potential Yield Limitations

Ethanol branching ratio

Light (photosaturation, photoinhibition)

Contaminants

CO2 and/or Nutrient supply

Photosaturation Illustration

(Melis, Plant Science (2009))

Algenol Vertical Photobioreactors

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Cyano-

bacteria

E0

Fixed

Carbon

Ethanol

Maintenance Respiration (scales with cell count or chlorophyll concentration, C0)

Biomass

φ = ethanol branching ratio

φ =fixed carbon rate serving ethanol production

total fixed carbon rate

Obtainable from short time behavior (dilute limit)Range = 0 % – 85 %

Algenol Productivity Model

Areal Ethanol Productivity (mol EtC/m2-s): Pe = αφEk ln(1 + E0/Ek)

Areal Net Biomass Productivity (mol BmC/m2-s): Pb = α(1-φ)Ek ln(1 + E0/Ek) – R0C0D

α = limiting quantum yield (Cfix/photon)

Ek = photosaturation parameter (μmol photons/m2-sec)

R0 = maintenance respiration rate (µmol C/mg Chl.a-min)

D = culture depth or thickness (m)

All light

absorbed

(kD>>1)

“Static”

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A Recent Culture Management Experiment

Objective:

Compare productivity of two ethanologenic modifications of Strain 2

Compare photobiological responses of the ethanologenic strains with wild type

Treatment Strain # of PBRs

Controls Strain 2a 2

New Strain Strain 2b 3

Wild Type Strain 2-WT 2

Operating Conditions:

Outdoors (Florida)

pH-controlled CO2 delivery

Vertical PBRs constructed in-house

Inoculation Day: 14 May 2013

Collect samples periodically for

Ethanol/biomass concentrations

Productivity-Irradiance (PE) curves

Optical absorption spectra

Enzymatic activities

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Net Fixed C (TC) = all non-ethanol organic C plus 3/2 C in ethanol

Net Ethanol C (EtC) = 3/2 C in ethanol

Modeling an Outdoor Experiment in Florida (Strain 2b)

Experimental data from Algenol aquaculture group (Dr. Laura Belicka, Dr. Lanny Miller)

Average Daily PAR irradiance

May 14 - July 4, 2013

0

10

20

30

40

50

60

0 10 20 30 40 50 60

PA

R, m

olp

ho

ton

s/m

2 -d

ay

Time-days

Experimental Data in Triplicate

Optical Absorption Spectra

(integrating sphere)

Model Fit: α, 𝝋0, and R0

Ek taken from PE curves

α = 0.09 (11 photons/fixed C)

𝝋0= 72 %

R0 = 0.05 µmol C/mg Chl.a-min

(consistent with dark O2 consumption)

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Net Fixed C (TC) = all non-ethanol organic C plus 3/2 C in ethanol

Net Ethanol C (EtC) = 3/2 C in ethanol

Modeling an Earlier Strain with Lower Ethanol Branching

(Strain 1)

Experimental data from Algenol aquaculture group (Dr. Laura Belicka, Dr. Lanny Miller)

0

10

20

30

40

50

0 10 20 30 40 50 60 70

PA

R,

mo

lp

ho

ton

s/m

2-d

ay

Time-days

Average Daily PAR irradiance

Sept 12, 2012 - Nov 25, 2012

Experimental Data in Duplicate

Model Fit: α, 𝝋0, and R0

Ek taken from PE curves

α = 0.09 (11 photons/fixed C)

𝝋0= 40 %

R0 = 0.05 µmol C/mg Chl.a-min

(consistent with dark O2 consumption)

Optical Absorption Spectra

(integrating sphere)

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Modeling a Laboratory Experiment

Strain 2c, 12-12 constant light-dark cycle

Model Fit: α, 𝝋0, and R0

α = 0.09 (12 photons/fixed C)

𝝋0= 75%, Qe=0.5, R0=0.08

R0 consistent with dark O2 consumption

Ek derived from PE measurements on

samples extracted at various time points

• Same modeling approach as outdoors

• Experiment designed to be highly predictive of

outdoor (vertical) configuration

• Same model parameters derived for range of

irradiance levels (E0 = 90 – 350 µE/m2-sec)

• Ek acclimation derived from PE curves

Experimental Data in Triplicate

E0 = 350 µE/m2-sec

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Ce

ll d

en

sity [O

D7

50

nm

]

Biomass Production Model (φ = 0)

Laboratory Experiment (n=6)

Strain 2 Wild Type, E0=230 µE/m2-s

Productivity Model

Note: Biomass concentration (g/L) = 0.4 OD750

α = 0.10 molC/molphotons, R0 = 0.05 µmolC/mgChl.a-min

α = 0.075 molC/molphotons, R0 = 0.10 µmolC/mgChl.a-min

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Conclusions

A relatively simple model based on Michaelis-Menten kinetics is

remarkably successful in describing biomass and ethanol

production in long term indoor and outdoor cultures

Application of the model to Algenol’s ethanologenic strains yields:

Very high limiting quantum yields (α ~ 0.08-0.10) corresponding to quantum

demands of 10-12 photons/fixed carbon

High branching ratios, with about 80% of the fixed carbon diverted to the

ethanol pathway

Reasonable estimates of maintenance respiration that are quite consistent

with inferences from measured rates of oxygen consumption in the dark

Reasonable estimates of the impact of light-related acclimation on culture

productivity

High confidence in the translation of laboratory experiments to outdoor

conditions

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Acknowledgements

Berlin

Research Lab

Fort Myers

Research Lab