A2MA2M Experimental and modeling approaches to optimize an algae-to-methane coupled bioreactor...

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A2M Experimental and modeling approaches to optimize an algae-to-methane coupled bioreactor system Ruby An – 2015 SURF Metcalf Student Principal Investigators : Joe Vallino & Zoe Cardon The University of Chicago Chicago IL MA Woods Hole Marine Biological Laboratory

Transcript of A2MA2M Experimental and modeling approaches to optimize an algae-to-methane coupled bioreactor...

Page 1: A2MA2M Experimental and modeling approaches to optimize an algae-to-methane coupled bioreactor system Ruby An – 2015 SURF Metcalf Student Principal Investigators.

A2MExperimental and modeling approaches to optimize

an algae-to-methane coupled bioreactor system

Ruby An – 2015 SURF Metcalf StudentPrincipal Investigators : Joe Vallino & Zoe Cardon

The University of Chicago – Chicago – IL – MA – Woods Hole – Marine Biological Laboratory

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Algae-to-methane (A2M) has potential as an efficient and practical renewable energy strategy

• Algal biomass: minimal land & water usage• Methane: efficiently stored & energy on demand

www.prx.orgwww.wageningenur.nl

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A2M Research Aims

1. Experimental – Develop closed system with 100% nutrient recycling– Maximize methane production

2. Modeling – Develop accurate description of system– Predict system performance to achieve experimental

objectives

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A2M Design

Temperature: 25 °C

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A2M Design

Aerobic Algal Reactor

Inputs:• Air • CO2

• Light – Diel 12h Cycle

Temperature: 25 °C

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Chlamydomonas rienhardtii CW15

25 μm

Green algae mutant lacking a cell wall

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A2M Design

Temperature: 25 °C

Anaerobic Microbial Digester

Output: • CO2 and methane gas• Digested algae as nutrients & detritus

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Aim 1: Experimental Set-upA2M IRL

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Liquid Volume:• pH• Dissolved oxygen (DO)

Headspace:• Oxygen (O2 ) • Carbon Dioxide (CO2 )• Methane (CH4)

Data Monitoringin both reactors

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Key Features of the Data

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Lights on Lights off

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Lights on Lights off

CO2 + H2O CH2O + O2 light

algae

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Key Features of Data

Installed spargers

Doubled light levels

Elevated CO2 input0.039% => 2%

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Key Features of Data

Day 1 Yesterday

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Aim 2a: Algal Reactor Mass Balance Model

rate of change = gain - loss

State Variables:1. CAlgae

2. CDIC(aq)

3. CO2(aq)

4. pCO2(g)

5. pO2(g)

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Inflow & Outflow

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Inflow & Outflow

MassTransfer

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Inflow & Outflow

MassTransfer

Algal Growth & Respiration

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CO2 + H2O CH2O + O2lightalgae

Algal Growth Equation

Light Limitation CO2 Limitation

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Adjustable Parameters

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Model & Data Comparison

Model fit to days 57-60

ModelData

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Model & Data ComparisonModel predictions for days 30-33

Data

Model

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In Summary:

• Experimentally - achieved high algal growth • Accurately modeled algal reactor dynamics

• Establish and maximize methane production• Develop the full coupled bioreactor model to

simulate methanogenisis

Next Steps:

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Acknowledgements

Joe VallinoZoe Cardon

Suzanne Thomas

Anonymous DonorKen Foreman & Wyntin Goodman

Zeiss Microscopy StaffJim & Joey

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Questions/Discussion

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Supplementary Info

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Anaerobic Microbial Community

www.oceanscience.com

Inoculated Day 71

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Methane

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• Microscopic analysis of algal cellular disintegration

• Jumpstart methanogenic pathway : new inoculum

• Genomic analysis of microbial community?

Methane Production Strategies

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