This work was supported through the Regional Algal Feedstock Testbed project, U.S. Department of Energy DE-EE0006269. We also thank Esteban Jimenez, Jessica Peebles, Francisco Acedo, Jose Cisneros, RAFT Team, Mark Mansfield, UA power plant staff, and TEP power plant staff for all their help.

1. Growth system: outdoor open raceway pond settings
<ol>
	<li>Set up the open raceway ponds close to the flue gas source (containing 8&#8211;10% CO2). Ensure water and electricity are available at the pond reactor location and that the reactor is not in the shade the majority of the day (Figure 1).</li>
	<li>Capture flue gas during the post-combustion process using a 0.95 cm fuel hose, a few meters before the flue gas enters the stack to be discharged into the atmosphere (Figure 2).</li>
	<li>Remove water from the flue gas using a 20 L water trap and a condenser (coil length ~12 m) between the stack and the compressor (Figure 2). 
	NOTE: Flue gas typically contains approximately 9&#8210;13.8% water28. In addition, the condenser and pipeline cool the flue gas16.</li>
	<li>Connect the following sensors to a datalogger to monitor algal growth: (1) a real time optical density sensor29, which measures absorbance at two wavelengths&#8212;650 and 750 nm&#8212;and can detect a maximum algal cell concentration of 1.05 g/L; (2) a DO sensor; (3) air and pond thermocouples; (4) a pH sensor; and (5) an EC sensor. 
	NOTE: Additionally, the pH and EC sensors are connected to a transmitter. The data logger unit configuration is shown in Figure 3.</li>
	<li>Ensure that all components of the algal growth system are calibrated and properly working before inoculation.</li>
</ol>
2. pH control system
<ol>
	<li>Manage flue gas injection by using a compressor, a control valve system, and the data logger program, as shown in Figure 2 and Figure 3 (Supplementary material A).</li>
	<li>Use a tube to direct the flue gas from the control valve to the bottom of the raceway pond through a stone diffuser.</li>
	<li>Inject the flue gas into the growth system based on pH. When the pH value is greater than 8.05, the system will inject flue gas, whereas when the pH is less than 8.00, the system will stop the flue gas injection in periods of no growth. The flow rate is measured in standard liters per minute (SLPM). 
	NOTE: In the control valve, the inlet flue gas pressure is limited to a maximum of 50 psi.</li>
</ol>
3. Algae selection and strain maintenance (light and temperature)
NOTE: The green algae Chlorella sorokiniana DOE 1412 was isolated by Juergen Polle (Brooklyn College)30,31 and selected by the National Alliance for Advanced Biofuels and Bioproducts (NAABB); its selection was based on the previous strain characterization studies performed by Huesemann et al.32,33 . Their research regarding algal screening, biomass productivity, and climate-simulated culturing (e.g., temperature and light) in the Southwest region when using outdoor open raceway ponds informed the method used in this project.
<ol>
	<li>Maintain cultures at room temperature (25 &#176;C) using a 12 h/12 h light/dark cycle.</li>
	<li>Keep light intensity at 200 &#181;M/m2/s for culture maintenance grown on plates&#160;and in small liquid cultures (50 mL to 500 mL).</li>
	<li>Keep light intensity for scale up grown in liquid cultures 50 mL to 500 mL at 400 &#181;M/m2/s, and liquid cultures 5 L to 20 L at 600&#8210;800 &#181;M/m2/s.</li>
</ol>
4. Scale up and quality control
<ol>
	<li>Prepare the BG11 culture medium using deionized water and the following salts, for macronutrients, in g/L: 1.5 NaNO3, 0.04 K2HPO4, 0.075 MgSO4*H2O, 0.036 CaCl2*H2O, 0.006 (NH4)5Fe(C6H4O7)2, 0.006 Na2EDTA*2H2O, 0.02 Na2CO3; add 1 mL/L of trace element solution, which contains the following micronutrients in g/L: 2.86 H3BO3, 1.81 MnCl2*4H2O, 0.22 ZnSO4*7H2O, 0.39 Na2MoO4*2H2O, 0.079 CuSO4*5H2O, 0.0494 Co(NO3)2*6H2O. 
	NOTE: For plate inoculation and/or long-term storage, add 7.5 g/L of Bacto agar; for culture inoculation, no addition of agar is needed. Sterilize culture medium in the autoclave for 21 min at 121 &#176;C.</li>
	<li>Pour the BG11 medium with agar into Petri dishes in a sterile laminar flow hood or biosafety cabinet. Once plates are firm and cool, pipette 500 &#181;L from a re-suspended frozen algal stock culture and add Ampicillin (100 &#181;g/mL); incubate the algal plates in a shaker table (120 rpm) for 1 to 2 weeks.</li>
	<li>Use a sterile loop to select a single algal colony from a culture plate and inoculate it in a 50 mL tube containing sterile growth medium in a clean biosafety cabinet. Grow the small liquid culture on a shaker table (120 rpm) for one week.</li>
	<li>Transfer 50 mL of algae culture (linear growth phase, OD750nm &#8805; 1) into a 1 L flask with 500 mL liquid medium. Fit each flask with a rubber stopper and stainless-steel tubing to provide aeration. Filter the air using 0.2 &#181;m air sterilization filters. Let the culture grow for one to two weeks. Monitor cell density using a spectrophotometer (OD750nm).</li>
	<li>Place the 500 mL liquid culture&#160;into a 10 L carboy containing 8 L of non-sterile culture medium and inject a mixture of 5% CO2 and 95% air. Then, cultivate algae under the same conditions as in step 4.4.</li>
	<li>Monitor stock plate and liquid cultures (in steps 4.2&#8210;4.5) once a week. Take an aliquot and observe it under the microscope at 10x and 40x magnification to ensure the growth of the desired strain. Kept cultures until they have been compromised or used for experiments. Discard contaminated cultures.</li>
</ol>
5. Concentrated medium preparation for open pond cultivation
<ol>
	<li>To prepare trace elements solution partially fill a 1 L volumetric flask with distilled water (DW). Insert a magnetic stir bar and add the chemicals shown in Table 1 sequentially. Ensure that each ingredient dissolves before the addition of the next constituent. Remove the magnet&#160;and fill the flask to the 1 L volume mark.</li>
	<li>Partially fill a 1 L glass bottle with DW and insert the magnetic stir bar. Place the container on the top of a magnetic stirrer plate and add the chemicals for the reactor&#8217;s final volume, adding them sequentially, ensuring each fully dissolves. Table 2 lists the chemicals to prepare 1 L of medium, so multiply all the values by the reactor&#8217;s final volume. Fill the glass bottle to 1 L.</li>
</ol>
6. Outdoor open raceway pond inoculation
<ol>
	<li>Thoroughly clean the reactor using 30% bleach before each inoculation and after harvesting. It is recommended to leave the bleach overnight. Rinse the reactor well to remove all bleach.</li>
	<li>Calibrate all the sensors before algae inoculation according to their corresponding calibration procedure.</li>
	<li>Dilute the concentrated media (in step 5) using the water source by filling the raceway pond up to 80%.</li>
	<li>Inoculate the reactor using a 10 L carboy filled with algae (linear growth phase OD750nm &#62; 2) and bring it to its&#160;final volume.</li>
	<li>Acclimate microalgae by partially shading the raceway pond with wooden pallets for ~ 3 days (Figure 4), once the exponential phase has passed, as an adaptation strategy to avoid photoinhibition. 
	NOTE:&#160;This period will also provide time for the microalgae to&#160;adapt to the stress caused by the direct injection of flue gas.</li>
</ol>
7. Batch growth experiment at the generating station
<ol>
	<li>Inspect and record any day-to-day variations including water evaporation, paddlewheel motor, sensor functionality, and anything out of the ordinary.</li>
	<li>Drain and inspect the compressor and water trap every day to remove any excess&#160;water to minimize corrosion since flue gas is highly corrosive34.</li>
	<li>Configure the data logger to scan each sensor measurement&#160;every 10 s and to store the average data every 10 min. These include DO, pH, EC, real time optical density as well as air and reactor temperature.</li>
</ol>
8. Discrete sampling and monitoring
<ol>
	<li>Make sure water level remains constant at the reactor&#8217;s final volume otherwise the optical density measurement will be affected.</li>
	<li>After replenishing water in the reactor, take a 5 mL sample for cell mass measurements by optical density (540, 680, and 750 nm) using an ultraviolet-visible spectrophotometer. Repeat the process daily.</li>
	<li>Take a 500 mL sample three times per week for microscope observations and biomass concentration based on ash-free dry weight (AFDW).
	<ol>
		<li>Perform microscope observations with 10x and 40x objective lenses. Additionally, these microscope magnifications are used&#160;as part of the algal quality control described in step 4.6.</li>
		<li>Use 400 mL of the sample in step 8.3 for AFDW
		<ol>
			<li>Set each 0.7 &#181;m pore size glass microfiber filter in an aluminum foil tray and pre-treat each aluminum foil tray/filter using a furnace for 4 h at 540 &#176;C.</li>
			<li>Label each aluminum foil tray using a #2 pencil, record its weight (A), and place it in the vacuum filter apparatus.</li>
			<li>Stir the algae sample vigorously before measuring out a volume to be filtered. Filter enough algae sample to give a pre/post ash weight difference of between 8 and 16 mg. Pick a weight difference to use throughout the course of the experiment and keep this value constant.&#160;&#160;&#160;&#160;</li>
			<li>Place each filter containing the algae sample in its foil tray in the oven at 105 &#176;C for at least 12 h.</li>
			<li>Remove the foil tray/filter from the drying oven and place it in a glass desiccator to prevent water uptake. Record each foil tray/filter weight (B).</li>
			<li>Place the foil tray/filter in the 540 &#176;C muffle furnace for 4 h.</li>
			<li>Turn off the muffle furnace, cool down foil trays/filters, place them into the desiccator, and record each foil tray/filter weight (C).</li>
			<li>Calculate AFDW using gravimetrical analysis: 
			% AFDW= C &#8211; A x&#160;100 / B</li>
		</ol>
		</li>
	</ol>
	</li>
	<li>Hold 2 L of algae before harvesting for microwave-assisted extraction (MAE) lipid extraction analysis using solvents.
	<ol>
		<li>Centrifuge the algae sample at a relative centrifugal force (RFC) of 4,400 x&#160;g for 15 min. Take the algae pellet and dry it using an oven at 80 &#176;C for at least 24 h.</li>
		<li>Grind the algae sample and weigh the algal powder (recommended biomass ranges from 0.3 g to 0.5 g).</li>
		<li>Add the algae powder (dry algal biomass) into the microwave accelerated reaction system (MARS) Xpress vessels, add 10 mL of chloroform:methanol (2:1, v/v) solvent solution under the hood, close the vessels, and let stand overnight.</li>
		<li>Place the vessels into the MARS machine using the solvent sensor for 60 min at 70 &#176;C and 800 W of power.</li>
		<li>Take vessels out of the MARS and let them cool down under the hood.</li>
		<li>Use a funnel and glass wool to separate the liquid part which contains chloroform, methanol, and lipids by transferring each liquid sample to a pre-weighed glass test tube and keep the solids (biomass free of lipids) for other analyses.</li>
		<li>Take the test tubes containing the lipids to the nitrogen evaporator, remove them once the liquid has been evaporated, and then leave the tubes overnight under the hood to ensure complete dryness.</li>
		<li>Calculate lipid content (wt. %) using gravimetric analysis: 
		Lipid content (wt. %) = Dry biomass of lipids x&#160;100/ Dry Algal mass</li>
	</ol>
	</li>
</ol>
9. Algal harvesting and crop rotation
<ol>
	<li>Harvest 75% of the total algae culture volume when the culture is close to reaching the stationary phase. Take 2&#8210;5 L of culture to perform biomass productivity analyses in the laboratory. Process and convert the rest of the algae into the desired algal products.</li>
	<li>Re-grow the open raceway pond by using the 25% algae remaining as inoculum. Add water up to 80% of the total reactor&#8217;s volume, add the concentrated media, and then finish filling up to the reactor&#8217;s final volume if necessary.</li>
	<li>Cultivate the appropriate algae strain according to the season, based on temperature and light intensity conditions.</li>
</ol>
10. Data management
<ol>
	<li>Record data in the data logger and collect for analysis as in step 7.3.</li>
	<li>Consider saving raw and analyzed data in the Regional Algal Feedstock Testbed (RAFT) share drive. RAFT project collaborators contribute&#160;their data to simulate and model algal productivity and validate outdoor cultivation.</li>
</ol>

The authors have nothing to disclose.

In this study, we demonstrate that synergistically coupling flue gas carbon capture and microalgae cultivation is possible in a hot semi-arid climate. The experimental protocol for the semi-automated raceway pond system integrates state-of-the-art technology to monitor relevant parameters in real time that correlate to algal growth when using flue gas as a carbon source. The proposed protocol is intended to reduce uncertainty in algal cultivation, which is one of the main drawbacks of raceway ponds20,21,36. In our experience, the protocol&#8217;s most critical steps involve the pH control system and an effective method to inoculate the system (Figure 2). The pH control system delivers flue gas/CO2&#160;and represents a strategy to optimize efficiency in CO2 capture and utilization (Figure 3)37. This controlled system has been proven to be more efficient than a continuous injection system for the microalgae cultivation process because it reduces outgassing while delivering enough flue gas to attain the maximum algal growth rate20,37. When the flue gas injection is based on pH, a key factor for algal cultivation is selecting an adequate pH value for the microalgae species before inoculating the raceway pond38,39. Qiu et al.40 found that a pH value of 8 is the best for the freshwater species Chlorella sorokiniania when considering cell growth and lipid production40. Moreover, Molina Grima et al.41 recommend a pH below 8 to reduce nitrogen loss and achieve better nitrogen uptake by the microalgae/biomass41. However, Yuvraj et al.42 suggest that pH is not an appropriate method to evaluate the CO2 content in the water because of the effect of nitrogen fertilization on the medium&#8217;s acidity42. Our results show that pH can be effectively used to manage CO2 injection for the system presented here (Figure 6); our flue gas injection management, which kept the culture at pH 8, resulted in high biomass yields and replicability (Figure 7).
After inoculation, the algae must acclimate to the system to avoid photoinhibition and to adjust to the high temperature of the raceway media. In this hot semi-arid climate, we have observed algal photoinhibition due to high solar radiation39,43,44 (Figure 9). This effect can not only delay but also inhibit microalgae inoculation during the exponential phase32,35,45,46,47. To reduce the impact of acclimation on the microalgae, we designed a successful and feasible strategy consisting of partially shading the raceway pond with wooden pallets. This strategy allows the microalgae to be exposed repeatedly but for short periods of time to the solar conditions. Another stress factor is the high temperature of the flue gas and the ambient air33,48 (Figure 8). The flue gas temperature is quite high at the post-combustion stage10,48,49. Utilizing the flue gas by directly injecting it from the dispatched pipeline into the raceway pond can contribute to further increasing the medium&#8217;s temperature. Hence, a condenser followed by a water trap located before the compressor will not only reduce the heat transfer but also the amount of water reaching the compressor (Figure 2). We found that both devices were necessary to reduce the compressor failure rate. Additionally, humidity, flue gas temperature, and the corrosive nature of the flue gas must be considered when estimating the compressor&#8217;s life cycle and maintenance. Furthermore, high temperatures cause higher evaporation rates.
This protocol is subject to some limitations. According to Figure 6, the control valve was not able to inject enough flue gas when photosynthesis was at its peak. This effect can be attributed to low mass transfer from the gaseous to the liquid phase due to the reactor design5,16,50,51. Mendoza et al.36,52 and de&#160;Godos et al.16 stated that raceway ponds have a poor gas/liquid mass transfer, which represents one of the most severe design constraints16,36,52. Their shallow channel design limits CO2 mass transfer due to the short interface area between the gas and the culture medium, which causes an increase in CO2 off-gassing (Figure 2). Thus, devices and novel configurations have been proposed to increase the gas/liquid contact time, including sumps, mixing columns, permeable silicone, and sparging-diffusion systems36,52,53. All these systems have been used in an attempt to enhance CO2 mass transfer; however, some of these systems also improve nutrient distribution, control pH, and remove excess O25,24,36,52. Finally, outages are other limitations that can arise when capturing and utilizing real flue gas from a power plant. These outages are not always scheduled. Thus, temporary alternative sources of CO2 should be considered, for example, relocation or connecting the CO2 mainline to multiple power units (Figure 1).
The ability to produce microalgae with this protocol is supported by our results on algal productivity (Figure 5), algal responses to the selected parameters (Figure 6, Figure 8, Figure 9), and successful cultivation of the desired algal species when nurtured by direct flue gas injection. Open reactors are cheaper to operate, and thus, this protocol builds upon their strengths to accelerate commercial-scale deployment of this form of carbon capture and utilization16,20,54,55,56. This hot semi-arid region experiences high solar radiation and significant temperature fluctuations year-round (Figure 8 and Figure 9)57; hence, it is a prime location to test this sort of protocol. The optical density sensor provided consistent OD readings for our outdoor open system (Figure 5); this type of data collection would be impractical using other sensors. Also, the sensors responded well to the significant temperature variations from day to night (Figure 8), enabling us to make timely algal productivity decisions29. Furthermore, the proposed optimized medium has the critical advantage of being based on commercial fertilizer and readily available nutrient sources58 (Table 1 and 2); this medium can be easily produced in-house or could be sourced upon request from agricultural liquid fertilizer companies58. Finally, the semi-automated protocol was tested in an additional natural gas power plant. The results of that confirmation study are not presented in this paper. In that confirmation study, the protocol was successful despite the extreme weather conditions in Tucson and the exceptionally hot temperatures at the generation station due to the reactor&#8217;s location within the power plant layout. Therefore, protocol replicability has been examined for Tucson&#8217;s environment when natural gas is used as fuel to produce electricity.
The following steps are recommended to further develop this protocol and to improve and enhance the automation of the processes involved. The first recommendation is to make the flue gas injection a completely variable-rate process, thus improving CO2 and pH management; the current program fully opens the injection valve when the pH rises above&#160;8 and closes it when the pH reaches 8 again. Improving the way CO2 is injected is also necessary. The aim is to reduce the size of the CO2 bubbles, i.e., to generate microbubbles to enhance CO2 diffusion in the medium without resorting to injecting flue gas at higher pressure. Using improved injectors, thus reducing operational energy costs, is deemed necessary in a commercial application of the protocol. The inclusion of predictive tools based on the weather forecast and current microalgae status for controlling the flue gas and fertilizer, mainly N, to improve N use efficiency, is also recommended. The use of computational fluid dynamic modeling is considered a vital tool in developing the proposed protocol further; modeling can help optimize the design, configuration, and operation of all the hardware involved in the monitoring and management of the microalgae. Another area that could be explored in the future is the application of environmental DNA (eDNA) and real time PCR techniques to monitor the health and composition of the microalgae crop. Water samples could be analyzed, and the results would indicate whether the objective microalgae are the predominant species in the medium or whether it is competing or has been&#160;replaced by a different organism.

Global warming is one of the most important environmental issues that the world faces today1. Studies suggest that the major cause is the increase in greenhouse gas (GHG) emissions, mainly CO2, in the atmosphere due to human activities2,3,4,5,6,7. In the U.S., the largest density of CO2 emissions originates mainly from fossil fuel combustion in the energy sector, specifically electric power generation plants3,7,8,9. Thus, carbon capture and utilization (CCU) technologies have emerged as one of the major strategies to reduce GHG emissions2,7,10. These include biological systems that utilize sunlight to convert CO2 and water via photosynthesis, in the presence of nutrients, to biomass. The use of microalgae has been proposed due to the fast growth rate, high CO2 fixation ability, and high production capacity. Additionally, microalgae have broad bioenergy potential because the biomass can be converted into products of interest, such as biofuels that can replace fossil fuels7,9,10,11,12.
Microalgae can grow and achieve biological conversion in a variety of cultivation systems or reactors, including open raceway ponds and closed photobioreactors13,14,15,16,17,18,19. Researchers have studied the advantages and limitations that determine the success of the bioprocess in both cultivation systems, under either indoor or outdoor conditions5,6,16,20,21,22,23,24,25. Open raceway ponds are the most common cultivation systems for carbon capture and utilization in situations where flue gas can be distributed directly from the stack. This type of cultivation system is relatively inexpensive, is easy to scale up, has low energy costs, and has low energy requirements for mixing. Additionally, these systems can easily be co-located with the power plant to make the CCU process more efficient. However, there are some drawbacks that need to be considered, such as the limitation in CO2 gas/liquid mass transfer. Although there are limitations, open raceway ponds have been proposed as the most suitable system for outdoor microalgal biofuel production5,9,11,16,20.
In this article, we detail a method for microalgae cultivation in open raceway ponds that combines carbon capture from the flue gas of a natural gas power plant. The method consists of a semi-automated system that controls flue gas injection based on the culture pH; the system monitors and records the Chlorella sorokiniana culture status in real time using optical density, dissolved oxygen (DO), electroconductivity (EC), and air and pond temperature sensors. Algal biomass and flue gas injection data are collected by a data logger every 10 min at the Tucson Electric Power facility. Algae strain maintenance, scale up, quality control measurements, and biomass characterization (e.g., correlation between optical density, g/L, and lipid content) are performed in a laboratory setting at the University of Arizona. A previous protocol outlined a method for optimizing flue gas settings to promote microalgae growth in photobioreactors via computer simulation26. The protocol presented here is unique in that it utilizes open raceway ponds and is designed to be implemented on-site at a natural gas power plant in order to make direct use of the flue gas produced. Additionally, real time optical density measurements are part of the protocol. The system as described is optimized for a hot semiarid climate (K&#246;ppen BSh), which exhibits low precipitation, significant variability in precipitation from year to year, low relative humidity, high evaporation rates, clear skies, and intense solar radiation27.

<table><tbody><tr><td>Adjustable speed motor (paddle wheel system)</td><td>Leeson</td><td>174307</td><td>Lesson 174307.00, type: SCR Voltage; Amps:10</td></tr><tr><td>Aluminum weight boats</td><td>Fisher Scientific</td><td>08-732-102</td><td>Fisherbrand Aluminum Weighing Dishes</td></tr><tr><td>Ammonium Iron (III) (NH?)?[Fe(C?H?O?)?]</td><td>Fisher Scientific</td><td>1185 - 57 - 5</td><td>Medium preparation. Ammonium iron(III) citrate</td></tr><tr><td>Ammonium Phosphate</td><td>Sigma-Aldrich</td><td>7722-76-1</td><td>This chemical is used for the optimized medium</td></tr><tr><td>Ampicillin sodium salt</td><td>Sigma Aldrich</td><td>A9518-5G</td><td>This chemical is used for avoiding algae contamination</td></tr><tr><td>Autoclave</td><td>Amerex Instrument Inc</td><td></td><td>Hirayama HA300MII</td></tr><tr><td>Bacto agar</td><td>Fisher Scientific</td><td>BP1423500</td><td>Fisher BioReagents Granulated Agar</td></tr><tr><td>Bleach</td><td>Clorox</td><td></td><td>Germicidal Bleach, concentrated clorox</td></tr><tr><td>Boric Acid (H3BO3)</td><td>Fisher Scientific</td><td>10043-35-3</td><td>Trace Elelements: Boric acid</td></tr><tr><td>Calcium chloride dihydrate (CaCl2*2H2O)</td><td>Sigma-Aldrich</td><td>10035-04-8</td><td>Medium preparation. Calcium chloride dihydrate</td></tr><tr><td>Carboys (20 L)</td><td>Nalgene - Thermo Fisher Scientific</td><td>2250-0050PK</td><td>Polypropylene Carboy w/Handles</td></tr><tr><td>Centrifuge</td><td>Beckman Coulter, Inc</td><td></td><td>J2-21</td></tr><tr><td>Chloroform</td><td>Sigma-Aldrich</td><td>67-66-3</td><td>This chemical is used for lipid extraction</td></tr><tr><td>Citraplex 20% Iron</td><td>Loveland Products</td><td>SDS No. 1000595582 -17-LPI</td><td>https://www.fbn.com/direct/product/Citraplex-20-Iron#product_info</td></tr><tr><td>Cobalt (II) nitrate hexahydrate (Co(NO3)2*6H2O)</td><td>Sigma-Aldrich</td><td>10026-22-9</td><td>Trace Elements: Cobalt (II) nitrate hexahydrate</td></tr><tr><td>Compressor</td><td>Makita</td><td>MAC700</td><td>This equipment is used for the injection CO2 system</td></tr><tr><td>Control Valve</td><td>Sierra Instruments</td><td>SmartTrak 100</td><td>This item needs to be customized for your application. In our case, it was used a 5% CO2 and 95% air mixture.</td></tr><tr><td>Copper (II) Sulfate Pentahydrate (CuSO4*5H2O)</td><td>Sigma-Aldrich</td><td>7758-99-8</td><td>Trace Elements: Copper (II) Sulfate Pentahydrate</td></tr><tr><td>Data Logger: Campbell unit CR3000</td><td>Scientific Campbell</td><td>CR3000</td><td>This equipment is used for controlling all the system, motoring and recording data</td></tr><tr><td>Dissolvde Oxygen Solution</td><td>Campbell Scientific</td><td>14055</td><td>Dissolved oxygen electrolyte solution DO6002 - Lot No. 211085</td></tr><tr><td>Dissolved Oxygen probe</td><td>Sensorex</td><td>?</td><td>DO6400/T Dissolved Oxygen Sensor with Digital Communication</td></tr><tr><td>Electroconductivity calibration solution</td><td>Ricca Chemical Company</td><td>2245 - 32 ( R2245000-1A )</td><td>Conductivity Standard, 5000 uS/cm at 25C (2620 ppm TDS as NaCl)</td></tr><tr><td>Electroconductivity probe sensor</td><td>Hanna Instruments</td><td>HI3003/D</td><td>Flow-thru Conductivity Probe - NTC Sensor, DIN Connector, 3m Cable</td></tr><tr><td>Ethylenediaminetetraacetic acid disodium salt dihydrate (Na2EDTA*2H2O)</td><td>Sigma-Aldrich</td><td>6381-92-6</td><td>Medium Preparation: Ethylenediaminetetraacetic acid disodium salt dihydrate</td></tr><tr><td>Filters</td><td>Fisher Scientific</td><td>09-874-48</td><td>Whatman Binder-Free Glass Microfiber Filters</td></tr><tr><td>Flasks</td><td>Fisher scientific</td><td>09-552-40</td><td>Pyrex Fernbach Flasks</td></tr><tr><td>Furnace</td><td>Hogentogler</td><td>Model: F6020C-80</td><td>Thermo Sicentific Thermolyne F6020C - 80 Muffle Furnace</td></tr><tr><td>Glass dessicator</td><td>VWR International LLC</td><td>75871-430</td><td>Type 150, 140 mm of diameter</td></tr><tr><td>Glass funnel</td><td>Fisher Scientific</td><td>FB6005865</td><td>Fisherbrand Reusable Glass Long-Stem Funnels</td></tr><tr><td>Laminar flow hood</td><td>Fisher Hamilton Safeair</td><td></td><td>Fisher Hamilton Stainless Safeair hume hood</td></tr><tr><td>Magnesium sulfate heptahydrate (MgSO4*7H2O)</td><td>Fisher Scientific</td><td>10034 - 99 - 8</td><td>Medium Preparation: Magnesium sulfate heptahydrate</td></tr><tr><td>Methanol</td><td>Sigma-Aldrich</td><td>67-56-1</td><td>Lipid extraction solvent</td></tr><tr><td>Micro bubble Diffuser</td><td>Pentair Aquatic Eco-Systems</td><td>1PMBD075</td><td>This equipment is used for the injection CO2 system</td></tr><tr><td>Microalgae: Chlorella Sorokiniana</td><td>NAABB</td><td>DOE 1412</td><td></td></tr><tr><td>Microoscope</td><td></td><td></td><td>Carl Zeiss 4291097</td></tr><tr><td>Microwave assistant extraction</td><td>MARS, CEM Corportation</td><td></td><td>CEM Mars 5 Xtraction 230/60 Microwave Accelerated Reaction System. Model: 907601</td></tr><tr><td>MnCl2*4H2O</td><td>Sigma-Aldrich</td><td>13446-34-9</td><td>Manganese(II) chloride tetrahydrate</td></tr><tr><td>Mortars</td><td>Fisher Scientific</td><td>FB961B</td><td>Fisherbrand porcelein mortars</td></tr><tr><td>Nitrogen evaporator</td><td>Organomation</td><td></td><td>N-EVAP 112 Nitrogen Evaporatpr (OA-SYS Heating System)</td></tr><tr><td>Oven</td><td>VWR International LLC</td><td>89511-410</td><td>Forced Air Oven</td></tr><tr><td>Paddle Wheel</td><td></td><td></td><td>8-blade horizontal axis propeller. This usually comes as part of the paddlewheel reactor.</td></tr><tr><td>Paddle wheel motor</td><td>Leeson</td><td>M1135042.00</td><td>Leeson, Model: CM34025Nz10C; 1/4 HP; Volts 90; FR 34; 62 RPM.</td></tr><tr><td>Pestles</td><td>Fisher Scientific</td><td>FB961M</td><td>Fisherbrand porcelein pestles</td></tr><tr><td>pH and EC Transmitter</td><td>Hanna Instruments</td><td>HI98143</td><td>Hanna Instruments HI98143-04 pH and EC Transmitter with Galvanic isolated 0-4V.</td></tr><tr><td>pH calibration solutions</td><td>Fisher Scientific</td><td>13-643-003</td><td>Thermo Scientific Orion pH Buffer Bottles</td></tr><tr><td>pH probe sensor</td><td>Hanna Instruments</td><td>HI1006-2005</td><td>Hanna Instruments HI1006-2005 Teflon pH Electrode with matching pin 5m.</td></tr><tr><td>Pippete tips</td><td>Fisher Scientific</td><td>1111-2821</td><td>1000 ul TipOne graduated blue tip in racks</td></tr><tr><td>Pippetter</td><td>Fisher Scientific</td><td>13-690-032</td><td>Eppendorf Reserch plus Variable Adjustable Volume Pipettes: Single-channel</td></tr><tr><td>Plastic cuvettes</td><td>Fisher scientific</td><td>14377017</td><td>BrandTech BRAND Plastic Cuvettes</td></tr><tr><td>Plates</td><td>Fisher scientific</td><td>08-757-100D</td><td>Corning Falcon Bacteriological Petri Dishes with Lid</td></tr><tr><td>Potash</td><td></td><td></td><td>This chemical is used for the optimazed medium preparation. It was bought in a fertilizer local company</td></tr><tr><td>Potassium phosphate dibasic (K2HPO4)</td><td>Sigma-Aldrich</td><td>7758 -11 - 4</td><td>Medium Preparation: Potassium phosphate dibasic</td></tr><tr><td>Pyrex reusable Media Storage Bottles</td><td>Fisher scientific</td><td>06-414-2A</td><td>1 L and 2 L bottels - PYREX GL45 Screw Caps with Plug Seals</td></tr><tr><td>Raceway Pond</td><td></td><td></td><td>Similar equipment can be bought at https://microbioengineering.com/products</td></tr><tr><td>Real Time Optical Density Sensor</td><td>University of Arizona</td><td></td><td>This equipment was design and build by a member of the group</td></tr><tr><td>RS232 Cable</td><td>Sabrent</td><td></td><td>Sabrent USB 2.0 to Serial (9-Pin) DB-9 RS-232 Converter Cable, Prolific Chipset, Hexnuts, [Windows 10/8.1/8/7/VISTA/XP, Mac OS X 10.6 and Above] 2.5 Feet (CB-DB9P)</td></tr><tr><td>Shaker Table</td><td></td><td></td><td>Algae agitation 150 rpm</td></tr><tr><td>Sodium Carbonate (Na2CO3)</td><td>Sigma-Aldrich</td><td>497-19-8</td><td>Sodium carbonate</td></tr><tr><td>Sodium molybdate dihydrate (Na2MoO4*2H2O)</td><td>Sigma-Aldrich</td><td>10102-40-6</td><td>Medium Preparation: Sodium molybdate dihydrate</td></tr><tr><td>Sodium nitrate (NaNO3)</td><td>Sigma-Aldrich</td><td>7631-99-4</td><td>Medium Preparation: Sodium nitrate</td></tr><tr><td>Spectophotometer</td><td>Fisher Scientific Company</td><td>14-385-400</td><td>Thermo Fisher Scientific - 10S UV-Vis GENESTYS Spectrophotometer cylindrical Longpath cell holder; internal reference dectector, Xenon flash lamp; dual silicon photodiode; 240V, 50 to 60Hz selected automatically.</td></tr><tr><td>Test tubes</td><td>Fisher Scientific</td><td>14-961-27</td><td>Fisherbrand Disposable Borosilicate Glass Tubes with Plain End (10 ml)</td></tr><tr><td>Thermocouples type K</td><td>Omega</td><td>KMQXL-125G-6</td><td></td></tr><tr><td>Urea</td><td>Sigma-Aldrich</td><td>2067-80-3</td><td>Urea</td></tr><tr><td>Vacuum filtration system</td><td>Fisher Scientific</td><td>XX1514700</td><td>MilliporeSigma Glass Vacuum Filter Holder, 47 mm. The system includes: Ground glass flask attachment, coarse-frit glass filter support, and flask</td></tr><tr><td>Vacuum pump</td><td>Grainger</td><td></td><td>Marathon Electric AC Motor Thermally protected G588DX - MOD 5KH36KNA510X. HP 1/4. RPM 1725/1425</td></tr><tr><td>Zinc sulfate heptahydrate (ZnSO4*7H2O)</td><td>Sigma-Aldrich</td><td>7446-20-0</td><td>Zinc sulfate heptahydrate</td></tr></tbody></table>

coupling carbon capture from a power plant with semi-automated open raceway ponds for microalgae cultivation

In the United States, 35% of the total carbon dioxide (CO2) emissions come from the electrical power industry, of which 30% represent natural gas electricity generation. Microalgae can biofix CO2 10 to 15 times faster than plants and convert algal biomass to products of interest, such as biofuels. Thus, this study presents a protocol that demonstrates the potential synergies of microalgae cultivation with a natural gas power plant situated in the southwestern United States in a hot semi-arid climate. State-of-the-art technologies are used to enhance carbon capture and utilization via the green algal species Chlorella sorokiniana, which can be further processed into biofuel. We describe a protocol involving a semi-automated open raceway pond and discuss the results of its performance when it was tested at the Tucson Electric Power plant, in Tucson, Arizona. Flue gas was used as the main carbon source to control pH, and Chlorella sorokiniana was cultivated. An optimized medium was used to grow the algae. The amount of CO2 added to the system as a function of time was closely monitored. Additionally, other physicochemical factors affecting algal growth rate, biomass productivity, and carbon fixation were monitored, including optical density, dissolved oxygen (DO), electroconductivity (EC), and air and pond temperatures. The results indicate that a microalgae yield of up to 0.385 g/L ash-free dry weight is attainable, with a lipid content of 24%. Leveraging synergistic opportunities between CO2 emitters and algal farmers can provide the resources required to increase carbon capture while supporting the sustainable production of algal biofuels and bioproducts.

Prior experimental results from our lab indicate that microalgae cultivation using a semi-automated open raceway pond can be coupled with carbon capture processes. To better understand the synergy between these two processes (Figure 2), we developed a protocol and tailored it for cultivating the green algal species Chlorella sorokiniana under outdoor conditions in a hot semiarid climate. Natural gas flue gas was obtained from an industrial power generation station. This protocol uses various technologies to assess algal biomass productivity: (1) algae growth using a real time optical density sensor (Figure 5); (2) algae growth with respect to flue gas on-off pulse injections into the culture as a function of pH (Figure 6 and Figure 7); and (3) algae growth correlations with environmental parameters such as temperature, dissolved oxygen, and electroconductivity (Figure 8 and Figure 9).
We test a real time optical density sensor that monitors algae growth and physiological dynamics. This sensor allowed us to establish, via lab correlation, the corresponding ash free dry weight biomass (g/L). Figure 5 shows a comparison between the sensor and laboratory measurements. Both readings show similar trends, increasing as a function of time. However, the in-situ sensor readings can track the day/night algae growth cycle. Said cycle shows that the optical density values increase during the day but decrease at night during respiration, indicating a change in biomass productivity. The integration of the real time optical density sensor makes it possible to make effective management decisions about the overall algal production system.
We deploy a semi-automated on-off flue gas pulse injection system, which is represented in Figure 6 by a 24 h flue gas injection cycle measured during a particularly warm fall season in Tucson, AZ. As shown in Figure 6, flue gas was injected from approximately 8 am to 6 pm (diurnal period) but was not injected between 6 pm and 8 am (nocturnal period). This day/night cycle reflects the daily sunlight exposure and the lack of light during the night, and consequently, the activation of photosynthesis or photorespiration, respectively. Figure 7 presents the cumulative flue gas injected (L) during this algal batch. In this case, 6,564 L of flue gas, corresponding to 538 L CO2, were used to grown 0.29 g of algal biomass. The graph shows that as the algal growth rate increased, more flue gas (CO2) was required (Figure 6). The experimental results have confirmed that the on-off flue gas pulse injection system is effective at facilitating carbon capture and utilization through microalgae cultivation.
We measure and monitor other physicochemical parameters to establish a correlation between them and algal growth and productivity (Figure 8 and Figure 9). The environmental parameters measured were dissolved oxygen, electroconductivity (EC), and both air and pond temperatures. As expected, all the parameters, except EC, displayed similar trends that were highly correlated with solar radiation. The results indicate that these environmental variables had the most significant impact on algal growth and are used for algal biomass modeling35. The EC did not change significantly during the batch process. Thus, it did not provide any relevant information regarding algal growth. For cultivation of Chlorella sorokiniana using non-saline water, EC measurements can be omitted.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/61498/61498fig1.jpg" /> 
Figure 1: Pilot site location at Tucson Electric Power for coupling carbon capture from power plant and semi-automatized open-pond reactors for microalgae cultivation. The two locations are represented by: 1) Algae Site U3 (unit 3) and 2) Algae Site U4 (unit 4) photo credit: Jose Manuel Cisneros Vazquez. <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/61498/61498fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/61498/61498fig2.jpg" /> 
Figure 2: Process flow chart for coupling carbon capture and semi-automatized open raceway ponds for microalgae cultivation in a hot semiarid climate. (A) Open Raceway Paddlewheel design; (B) Real experimental facility; (C) Process: coupling carbon capture and microalgae cultivation modified from Van Den Hende28. Legends: T = Temperature; DO = Dissolved oxygen; OD = Optical density; EC = Electrical conductivity; Data Logger. <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/61498/61498fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/61498/61498fig3.jpg" /> 
Figure 3: Schematic representation of sensor&#160;set up. (A) Representation of the overall outdoor open-pond sensors set up, in which CV1 and CV2 are the control valves, DL is the&#160;data logger, and T1 and T2 are the transmitters. (B) Representation of a control valve. (C) Representation of the sensors&#8217; connection to the data logger; dark blue circle: real time optical density, orange triangle: pH and EC, black triangle: thermocouples, red triangle: dissolved oxygen, light blue: control valve. (D) pH and EC transmitter. <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/61498/61498fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/61498/61498fig4.jpg" /> 
Figure 4: Algae under the acclimation process. Microalgae acclimation strategy using wooden pallets during the exponential phase. <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/61498/61498fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/61498/61498fig5.jpg" /> 
Figure 5: Representation of algae growth monitoring. (A) Graph for AFDW biomass concentration (g/L) vs. time of laboratory measurements; (B) Graph for correlation between optical density sensor and laboratory measurements at 650 nm; and (C) graph for real time optical density sensor vs time for an experimental batch. <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/61498/61498fig5large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/61498/61498fig6.jpg" /> 
Figure 6: Graph for on/off flue gas pulse injection as a fuction of pH. The data logger was set up to start flue gas injection (controlled valve on) at pH = 8.05 and to end flue gas injection (controlled valve off) at pH = 8.00. <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/61498/61498fig6large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 7" class="xfigimg" src="/files/ftp_upload/61498/61498fig7.jpg" /> 
Figure 7: Graph for algal growth (g/L), amount of flue gas injected, and amount of CO2 injected as a function of time. <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/61498/61498fig7large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 8" class="xfigimg" src="/files/ftp_upload/61498/61498fig8.jpg" /> 
Figure 8: Representation of temperature&#160;monitoring. Legends: solid yellow line = raceway pond reactor temperature; solid grey line = air temperature; and dashed blue line = AZMET Station temperature (The Arizona Meteorological Network). <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/61498/61498fig8large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 9" class="xfigimg" src="/files/ftp_upload/61498/61498fig9.jpg" /> 
Figure 9: Monitoring of algae growth parameters. Legends: orange solid line = solar radiation; grey solid line = electroconductivy (EC); and yellow solid line = dissolved oxygen (DO). <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/61498/61498fig9large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<table border="1" fo:keep-together.within-page="1">
	<tbody>
		<tr>
			<td>Components</td>
			<td>Concentration in solution (g/L)</td>
		</tr>
		<tr>
			<td>H3BO3</td>
			<td>0.00286</td>
		</tr>
		<tr>
			<td>MnCl2&#183;4H2O</td>
			<td>0.00181</td>
		</tr>
		<tr>
			<td>ZnSO4&#183;7H2O</td>
			<td>0.0001373</td>
		</tr>
		<tr>
			<td>Na2MoO4&#183;2H2O</td>
			<td>0.00039</td>
		</tr>
		<tr>
			<td>CuSO4&#183;5H2O</td>
			<td>0.000079</td>
		</tr>
		<tr>
			<td>Co(NO3)2&#183;6H2O</td>
			<td>0.00005518</td>
		</tr>
		<tr>
			<td>NiCl2&#183;6 H2O</td>
			<td>0.0001</td>
		</tr>
	</tbody>
</table>
Table 1: Trace elements solution recipe.
<table border="1" fo:keep-together.within-page="1">
	<tbody>
		<tr>
			<td>Components</td>
			<td>Common name</td>
			<td>Concentration in solution (g/L)</td>
		</tr>
		<tr>
			<td>(NH2)2CO</td>
			<td>Urea</td>
			<td>0.1</td>
		</tr>
		<tr>
			<td>MgSO4&#183;7H2O</td>
			<td>Magnesium Sulfate</td>
			<td>0.012</td>
		</tr>
		<tr>
			<td>NH4H2PO4</td>
			<td>Ammonium Phosphate</td>
			<td>0.035</td>
		</tr>
		<tr>
			<td>KCl</td>
			<td>Potash</td>
			<td>0.175</td>
		</tr>
		<tr>
			<td>FeCl3</td>
			<td>Ferric Citrate (Citraplex)</td>
			<td>0.005423</td>
		</tr>
		<tr>
			<td>Trace Metal Solution</td>
			<td>Volume of 1000x Micros (ml)</td>
			<td>1</td>
		</tr>
	</tbody>
</table>
Table 2: Optimized media recipe for 1 L.
Supplemental Coding Files.&#160; <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/61498/Supplementary_Material_A.docx" target="_blank">Please click here to download this file.</a>

Watch this Scientific Journal Video about Coupling Carbon Capture from a Power Plant with Semi-automated Open Raceway Ponds for Microalgae Cultivation at JoVE.com

Coupling Carbon Capture from a Power Plant with Semi-automated Open Raceway Ponds for Microalgae Cultivation

A protocol is described to utilize the carbon dioxide in natural gas power plant flue gas to cultivate microalgae in open raceway ponds. Flue gas injection is controlled with a pH sensor, and microalgae growth is monitored with real time measurements of optical density.

In the United States, 35% of the total carbon dioxide (CO2) emissions come from the electrical power industry, of which 30% represent natural gas ...

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Nanyang Technological University

Research

JoVE Journal

Environment

4.9K Views.  University of Arizona. A protocol is described to utilize the carbon dioxide in natural gas power plant flue gas to cultivate microalgae in open raceway ponds. Flue gas injection is controlled with a pH sensor, and microalgae growth is monitored with real time measurements of optical density.

Video: Coupling Carbon Capture from a Power Plant with Semi-automated Open Raceway Ponds for Microalgae Cultivation

Methods for Performing Crosses in Setaria viridis, a New Model System for the Grasses

Setaria viridis is an emerging model system for C4 grasses. It is closely related to the bioenergy feed stock switchgrass and the grain crop foxtail millet. Recently, the 510 Mb genome of foxtail millet, S. italica, has been sequenced 1,2 and a 25x coverage genome sequence of the weedy relative S. viridis is in progress. S. viridis has a number of characteristics that make it a potentially excellent model genetic system including a rapid generation time, small stature, simple growth requirements, prolific seed production 3 and developed systems for both transient and stable transformation 4. However, the genetics of S. viridis is largely unexplored, in part, due to the lack of detailed methods for performing crosses. To date, no standard protocol has been adopted that will permit rapid production of seeds from controlled crosses.
The protocol presented here is optimized for performing genetic crosses in S. viridis, accession A10.1. We have employed a simple heat treatment with warm water for emasculation after pruning the panicle to retain 20-30 florets and labeling of flowers to eliminate seeds resulting from newly developed flowers after emasculation. After testing a series of heat treatments at permissive temperatures and varying the duration of dipping, we have established an optimum temperature and time range of 48 &deg;C for 3-6 min. By using this method, a minimum of 15 crosses can be performed by a single worker per day and an average of 3-5 outcross progeny per panicle can be recovered. Therefore, an average of 45-75 outcross progeny can be produced by one person in a single day. Broad implementation of this technique will facilitate the development of recombinant inbred line populations of S. viridis X S. viridis or S. viridis X S. italica, mapping mutations through bulk segregant analysis and creating higher order mutants for genetic analysis.

Methods for Performing Crosses in Setaria viridis, a New Model System for the Grasses

We have developed a methodology for performing crosses in Setaria viridis (S. viridis). The method involves pruning the panicle prior to a hot water treatment to kill viable pollen. Crosses are performed following a well-controlled growth regime and typically result in the recovery of 1 to 7 cross-pollinated seed/s per panicle.

Setaria viridis is an emerging model system for C4 grasses. It is closely related to the bioenergy feed stock switchgrass and the grain crop foxtail ...

Analysis of Fatty Acid Content and Composition in Microalgae

A method to determine the content and composition of total fatty acids present in microalgae is described. Fatty acids are a major constituent of microalgal biomass. These fatty acids can be present in different acyl-lipid classes. Especially the fatty acids present in triacylglycerol (TAG) are of commercial interest, because they can be used for production of transportation fuels, bulk chemicals, nutraceuticals (&omega;-3 fatty acids), and food commodities. To develop commercial applications, reliable analytical methods for quantification of fatty acid content and composition are needed. Microalgae are single cells surrounded by a rigid cell wall. A fatty acid analysis method should provide sufficient cell disruption to liberate all acyl lipids and the extraction procedure used should be able to extract all acyl lipid classes.
With the method presented here all fatty acids present in microalgae can be accurately and reproducibly identified and quantified using small amounts of sample (5 mg) independent of their chain length, degree of unsaturation, or the lipid class they are part of.
This method does not provide information about the relative abundance of different lipid classes, but can be extended to separate lipid classes from each other.
The method is based on a sequence of mechanical cell disruption, solvent based lipid extraction, transesterification of fatty acids to fatty acid methyl esters (FAMEs), and quantification and identification of FAMEs using gas chromatography (GC-FID). A TAG internal standard (tripentadecanoin) is added prior to the analytical procedure to correct for losses during extraction and incomplete transesterification.

A method for the determination of fatty acid content and composition in microalgae based on mechanical cell disruption, solvent based lipid extraction, transesterification, and quantification and identification of fatty acids using gas chromatography is described. A tripentadecanoin internal standard is used to compensate for the possible losses during extraction and incomplete transesterification.

A method to determine the content and composition of total fatty acids present in microalgae is described. Fatty acids are a major constituent of ...

Optimize Flue Gas Settings to Promote Microalgae Growth in Photobioreactors via Computer Simulations

Flue gas from power plants can promote algal cultivation and reduce greenhouse gas emissions1. Microalgae not only capture solar energy more efficiently than plants3, but also synthesize advanced biofuels2-4. Generally, atmospheric CO2 is not a sufficient source for supporting maximal algal growth5. On the other hand, the high concentrations of CO2 in industrial exhaust gases have adverse effects on algal physiology. Consequently, both cultivation conditions (such as nutrients and light) and the control of the flue gas flow into the photo-bioreactors are important to develop an efficient &ldquo;flue gas to algae&rdquo; system. Researchers have proposed different photobioreactor configurations4,6 and cultivation strategies7,8 with flue gas. Here, we present a protocol that demonstrates how to use models to predict the microalgal growth in response to flue gas settings. We perform both experimental illustration and model simulations to determine the favorable conditions for algal growth with flue gas. We develop a Monod-based model coupled with mass transfer and light intensity equations to simulate the microalgal growth in a homogenous photo-bioreactor. The model simulation compares algal growth and flue gas consumptions under different flue-gas settings. The model illustrates: 1) how algal growth is influenced by different volumetric mass transfer coefficients of CO2; 2) how we can find optimal CO2 concentration for algal growth via the dynamic optimization approach (DOA); 3) how we can design a rectangular on-off flue gas pulse to promote algal biomass growth and to reduce the usage of flue gas. On the experimental side, we present a protocol for growing Chlorella under the flue gas (generated by natural gas combustion). The experimental results qualitatively validate the model predictions that the high frequency flue gas pulses can significantly improve algal cultivation.

Flue gas from power plants is a cheap CO2 source for algal growth. We have built prototype &#34;flue gas to algal cultivation&#34; systems and described how to scale up the algal cultivation process. We have demonstrated the use of a mass-transfer bio-reaction model to simulate and to design the optimal operation of flue gas for the growth of Chlorella sp. in algal photo-bioreactors.

Flue gas from power plants can promote algal cultivation and reduce greenhouse gas emissions1. Microalgae not only capture solar energy more efficiently ...

Quantification of Heavy Metals and Other Inorganic Contaminants on the Productivity of Microalgae

Increasing demand for renewable fuels has researchers investigating the feasibility of alternative feedstocks, such as microalgae. Inherent advantages include high potential yield, use of non-arable land and integration with waste streams. The nutrient requirements of a large-scale microalgae production system will require the coupling of cultivation systems with industrial waste resources, such as carbon dioxide from flue gas and nutrients from wastewater. Inorganic contaminants present in these wastes can potentially lead to bioaccumulation in microalgal biomass negatively impact productivity and limiting end use. This study focuses on the experimental evaluation of the impact and the fate of 14 inorganic contaminants (As, Cd, Co, Cr, Cu, Hg, Mn, Ni, Pb, Sb, Se, Sn, V and Zn) on Nannochloropsis salina growth. Microalgae were cultivated in photobioreactors illuminated at 984 &#181;mol m-2 sec-1 and maintained at pH 7 in a growth media polluted with inorganic contaminants at levels expected based on the composition found in commercial coal flue gas systems. Contaminants present in the biomass and the medium at the end of a 7 day growth period were analytically quantified through cold vapor atomic absorption spectrometry for Hg and through inductively coupled plasma mass spectrometry for As, Cd, Co, Cr, Cu, Mn, Ni, Pb, Sb, Se, Sn, V and Zn. Results show N. salina is a sensitive strain to the multi-metal environment with a statistical decrease in biomass yieldwith the introduction of these contaminants. The techniques presented here are adequate for quantifying algal growth and determining the fate of inorganic contaminants.

Integration of microalgal cultivation with industrial flue gas will ultimately introduce heavy metals and other inorganic compounds into the growth media. This study presents a procedure used to determine the end fate and impact of heavy metals and inorganic contaminants on the growth of Nannochloropsis salina grown in photobioreactors.

Increasing demand for renewable fuels has researchers investigating the feasibility of alternative feedstocks, such as microalgae. Inherent advantages ...

Comparison of Scale in a Photosynthetic Reactor System for Algal Remediation of Wastewater

An experimental methodology is presented to compare the performance of two different sized reactors designed for wastewater treatment. In this study, ammonia removal, nitrogen removal and algal growth are compared over an 8-week period in paired sets of small (100 L) and large (1,000 L) reactors designed for algal remediation of landfill wastewater. Contents of the small and large scale reactors were mixed before the beginning of each weekly testing interval to maintain equivalent initial conditions across the two scales. System characteristics, including surface area to volume ratio, retention time, biomass density, and wastewater feed concentrations, can be adjusted to better equalize conditions occurring at both scales. During the short 8-week representative time period, starting ammonia and total nitrogen concentrations ranged from 3.1-14 mg NH3-N/L, and 8.1-20.1 mg N/L, respectively. The performance of the treatment system was evaluated based on its ability to remove ammonia and total nitrogen and to produce algal biomass. Mean &#177; standard deviation of ammonia removal, total nitrogen removal and biomass growth rates were 0.95&#177;0.3 mg NH3-N/L/day, 0.89&#177;0.3 mg N/L/day, and 0.02&#177;0.03 g biomass/L/day, respectively. All vessels showed a positive relationship between the initial ammonia concentration and ammonia removal rate (R2=0.76). Comparison of process efficiencies and production values measured in reactors of different scale may be useful in determining if lab-scale experimental data is appropriate for prediction of commercial-scale production values.

An experimental methodology is presented to compare the performance of small (100 L) and large (1,000 L) scale reactors designed for algae remediation of landfill wastewater. System characteristics, including surface area to volume ratio, retention time, biomass density, and wastewater feed concentrations, can be adjusted based on application.

An experimental methodology is presented to compare the performance of two different sized reactors designed for wastewater treatment. In this study, ...

Cultivation of Green Microalgae in Bubble Column Photobioreactors and an Assay for Neutral Lipids

There is significant interest in the study of microalgae for engineering applications such as the production of biofuels, high value products, and for the treatment of wastes. As most new research efforts begin at laboratory scale, there is a need for cost-effective methods for culturing microalgae in a reproducible manner. Here, we communicate an effective approach to culture microalgae in laboratory-scale photobioreactors, and to measure the growth and neutral lipid content of that algae. Instructions are also included on how to set up the photobioreactor system. Although the example organisms are species of Chlorella and Auxenochlorella, this system can be adapted to cultivate a wide range of microalgae, including co-cultures of algae with non-algae species. Stock cultures are first grown in bottles to produce inoculum for the photobioreactor system. Algae inoculum is concentrated and transferred to photobioreactors for cultivation in batch mode. Samples are collected daily for the optical density readings. At the end of the batch culture, cells are harvested by centrifuge, washed, and freeze dried to obtain a final dry weight concentration. The final dry weight concentration is used to create a correlation between the optical density and the dry weight concentration. A modified Folch method is subsequently used to extract total lipids from the freeze-dried biomass and the extract is assayed for its neutral lipid content using a microplate assay. This assay has been published previously but protocol steps were included here to highlight critical steps in the procedure where errors frequently occur. The bioreactor system described here fills a niche between simple flask cultivation and fully-controlled commercial bioreactors. Even with only 3-4 biological replicates per treatment, our approach to culturing algae leads to tight standard deviations in the growth and lipid assays.

Here, we present a protocol to construct lab-scale bubble column photobioreactors and use them to culture microalgae. It also provides a method for the determination of the culture growth rate and neutral lipid content.

There is significant interest in the study of microalgae for engineering applications such as the production of biofuels, high value products, and for the ...

Microalgae Cultivation and Biomass Quantification in a Bench-Scale Photobioreactor with Corrosive Flue Gases

Photobioreactors are illuminated cultivation systems for experiments on phototrophic microorganisms. These systems provide a sterile environment for microalgal cultivation with temperature, pH, and gas composition and flow rate control. At bench-scale, photobioreactors are advantageous to researchers studying microalgal properties, productivity, and growth optimization. At industrial scales, photobioreactors can maintain product purity and improve production efficiency. The video describes the preparation and use of a bench-scale photobioreactor for microalgal cultivation, including the safe use of corrosive gas inputs, and details relevant biomass measurements and biomass productivity calculations. Specifically, the video illustrates microalgal culture storage and preparation for inoculation, photobioreactor assembly and sterilization, biomass concentration measurements, and a logistic model for microalgal biomass productivity with rate calculations including maximum and overall biomass productivities. Additionally, since there is growing interest in experiments to cultivate microalgae using simulated or real waste gas emissions, the video will cover the photobioreactor equipment adaptations necessary to work with corrosive gases and discuss safe sampling in such scenarios.

Bench-scale, axenic cultivation facilitates microalgal characterization and productivity optimization before subsequent process scale-up. Photobioreactors provide the necessary control for reliable and reproducible microalgal experiments and can be adapted to safely cultivate microalgae with the corrosive gases (CO2, SO2, NO2) from municipal or industrial combustion emissions.

Photobioreactors are illuminated cultivation systems for experiments on phototrophic microorganisms. These systems provide a sterile environment for ...

Microalgal Cultivation for Biomethane Obtention from Swine Waste Biogas

Biogas Purification through the use of a Microalgae-Bacterial System in Semi-Industrial High Rate Algal Ponds

In recent years, a number of technologies have emerged to purify biogas into biomethane. This purification entails a reduction in the concentration of polluting gases such as carbon dioxide and hydrogen sulfide to increase the content of methane. In this study, we used a microalgal cultivation technology to treat and purify biogas produced from organic waste from the swine industry to obtain ready-to-use biomethane. For cultivation and purification, two 22.2 m3 open-pond photobioreactors coupled with an absorption-desorption column system were set up in San Juan de los Lagos, Mexico. Several recirculation liquid/biogas ratios (L/G) were tested to obtain the highest removal efficiencies; other parameters, such as pH, dissolved oxygen (DO), temperature, and biomass growth, were measured. The most efficient L/Gs were 1.6 and 2.5, resulting in a treated biogas effluent with a composition of 6.8%vol and 6.6%vol in CO2, respectively, and removal efficiencies for H2S up to 98.9%, as well as maintaining O2 contamination values of less than 2%vol. We found that pH greatly determines CO2 removal, more so than L/G, during cultivation because of its participation in the photosynthetic process of microalgae and its ability to vary pH when solubilized due to its acidic nature. DO, and temperature oscillated as expected from the light-dark natural cycles of photosynthesis and the time of day, respectively. Biomass growth varied with CO2 and nutrient feeding as well as reactor harvesting; however, the trend remained primed for growth.

Author Spotlight: Scaling Microalgal Biotechnology for Enhanced Biomethane Production 

Air pollution impacts the quality of life of all organisms. Here, we describe the use of microalgae biotechnology for the treatment of biogas (simultaneous removal of carbon dioxide and hydrogen sulfide) and the production of biomethane through semi-industrial open high-rate algal ponds and subsequent analysis of treatment efficiency, pH, dissolved oxygen, and microalgae growth.

In recent years, a number of technologies have emerged to purify biogas into biomethane. This purification entails a reduction in the concentration of ...

Construction and Setup of a Bench-scale Algal Photosynthetic Bioreactor with Temperature, Light, and pH Monitoring for Kinetic Growth Tests

The optimal design and operation of photosynthetic bioreactors (PBRs) for microalgal cultivation is essential for improving the environmental and economic performance of microalgae-based biofuel production. Models that estimate microalgal growth under different conditions can help to optimize PBR design and operation. To be effective, the growth parameters used in these models must be accurately determined. Algal growth experiments are often constrained by the dynamic nature of the culture environment, and control systems are needed to accurately determine the kinetic parameters. The first step in setting up a controlled batch experiment is live data acquisition and monitoring. This protocol outlines a process for the assembly and operation of a bench-scale photosynthetic bioreactor that can be used to conduct microalgal growth experiments. This protocol describes how to size and assemble a flat-plate, bench-scale PBR from acrylic. It also details how to configure a PBR with continuous pH, light, and temperature monitoring using a data acquisition and control unit, analog sensors, and open-source data acquisition software.

This paper describes the assembly process and operation of a bench-scale photosynthetic bioreactor that can be used, in conjunction with other methods, to estimate pertinent kinetic growth parameters. This system continuously monitors the pH, light, and temperature using sensors, a data acquisition and control unit, and open-source data acquisition software.

The optimal design and operation of photosynthetic bioreactors (PBRs) for microalgal cultivation is essential for improving the environmental and economic ...

Bioengineering

Operation of Laboratory Photobioreactors with Online Growth Measurements and Customizable Light Regimes

The laboratory study of microalgae can be experimentally challenging. In addition to the cultivation requirements of non-photosynthetic microorganisms, phototrophs also require illumination. Routinely, researchers seek to provide custom light supplies, i.e., vary the light intensity and time over which it is delivered. Such flexibility is difficult with standard benchtop lights. Usually, cultivation studies also require growth comparisons between experimental treatments. Frequently, growth is assessed over an extended duration, e.g., multiple times a day over a week-long trial. Manual measurements can be time-consuming and lack data resolution. Therefore, photobioreactors (PBRs) with automatic growth monitoring and customizable light supply are useful for replicated experiments with multiple treatments. The current work presents the design, construction, and operation of laboratory PBRs. The materials are easily sourced and relatively inexpensive. The design could be duplicated with moderate skill. Each structure has a footprint of ~40 cm2 and hosts three 1 L glass bottles for triplicate replication. Bottles rest upon platforms containing magnetic stirrers and are arranged vertically within a 1 m high and 15 cm diameter polyvinyl chloride (PVC) pipe. The pipe interior is lined with light-emitting diodes (LEDs). These LEDs produce continuous light intensities from 0&#8211;2400 &#181;mol photons m-2 s-1 of photosynthetically active radiation (PAR). Users design a custom lighting program. The light intensity can be adjusted each second or held constant for longer durations. Oxygen produced from photosynthesis exits each bottle via a one-way volumetric gas sensor. Software is used to record gas sensor data. The amount of oxygen produced can be correlated to biomass growth. If biomass samples are required, a syringe can be used to extract culture. The method is suited for microalgae grown with bicarbonate as the carbon source. These PBRs are valuable to a laboratory that requires replicated experiments, light regime flexibility, and continuous high-resolution growth data.

This publication describes the design of laboratory photobioreactors (PBRs) with customizable light regimes. The growth of cyanobacteria or microalgae, using bicarbonate as their carbon source, is monitored continuously by measuring volumetric oxygen production. These PBRs facilitate rapid, replicated laboratory growth comparisons with little user intervention during experiments.

The laboratory study of microalgae can be experimentally challenging. In addition to the cultivation requirements of non-photosynthetic microorganisms, ...

Coupling Carbon Capture from a Power Plant with Semi-automated Open Raceway Ponds for Microalgae Cultivation

Summary

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Chapters in this video

Methods for Performing Crosses in Setaria viridis, a New Model System for the Grasses

Analysis of Fatty Acid Content and Composition in Microalgae

Optimize Flue Gas Settings to Promote Microalgae Growth in Photobioreactors via Computer Simulations

Quantification of Heavy Metals and Other Inorganic Contaminants on the Productivity of Microalgae

Comparison of Scale in a Photosynthetic Reactor System for Algal Remediation of Wastewater

Cultivation of Green Microalgae in Bubble Column Photobioreactors and an Assay for Neutral Lipids

Microalgae Cultivation and Biomass Quantification in a Bench-Scale Photobioreactor with Corrosive Flue Gases

Biogas Purification through the use of a Microalgae-Bacterial System in Semi-Industrial High Rate Algal Ponds

Construction and Setup of a Bench-scale Algal Photosynthetic Bioreactor with Temperature, Light, and pH Monitoring for Kinetic Growth Tests

Operation of Laboratory Photobioreactors with Online Growth Measurements and Customizable Light Regimes