The authors would like to thank the Sandtown Landfill in Felton, DE for sharing their knowledge and leachate.

1. System Setup
Note: A &#39;paired system&#39; refers to one aquarium tank and one raceway pond, run in parallel.
<ol>
	<li>For one paired system, use one 100 L aquaria tanks (AT), with an overhead mixer for the small-scale vessel, and one 1,000 L raceway pond (RWP), with a paddle wheel mixer for the large-scale vessel. Vessels used in this system are pictured in Figure 1.</li>
	<li>Inoculate all vessels with the same algae culture. Use a high density of the inoculation, resulting in a final density of no less than 0.1 g/L once diluted to the full volume in the tank or pond 10. It may take a considerable amount of time (weeks to months) to grow enough algae for this step.</li>
	<li>Use untreated landfill leachate as the nutrient source. Use leachate taken from a landfill that accepts mostly domestic waste and has low levels of toxins. Composition analysis for the leachate should be available from the landfill. The amount of leachate used in each tank or pond can vary depending on the strength of the wastewater, but final ammonia concentrations should measure 5-75 mg NH3-N/L.</li>
	<li>Start the 100 L aquaria tank with a 60 L working volume, and the raceway pond with a 600 L working volume. This study started with approximately 1 L leachate in 59 L of water in the aquaria tank, and 10 L leachate in 590 L of water in the raceway pond. Increase the concentration of leachate used over the course of this study.</li>
</ol>
<img alt="Figure 1" src="/files/ftp_upload/55256/55256fig1.jpg" /> 
Figure 1. Examples of an aquarium tank and raceway pond. An example of an aquarium tank (A) and raceway pond (B) are shown. <a href="http://cloudfront.jove.com/files/ftp_upload/55256/55256fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
2. Weekly Operation and Sampling
<ol>
	<li>Operate the aquaria tank and raceway pond as semi-batch reactors with hydraulic retention times of three weeks. Each sampling period spans one week.</li>
	<li>Take a 125 mL sample from each vessel. This is the beginning of the week sample. Test samples according to the Sample Analysis protocol in sections 3.1-3.3.</li>
	<li>At the end of the week, take 125 mL samples from each vessel for analysis. After the end-of-week samples have been taken, empty the entire volume of the aquarium tank into the raceway pond.
	<ol>
		<li>Once per week, pump the entire volume of the aquarium tank into the raceway pond.</li>
	</ol>
	</li>
	<li>Remove one-third of the volume (for an average hydraulic retention time of 3 weeks) from the raceway pond. Replace volume removed with water and untreated leachate.</li>
	<li>Transfer approximately 60 L from the raceway pond back into the aquarium tank. This ensures that the aquarium tank and the raceway pond are starting with the same nutrient and biological conditions each week.</li>
	<li>Take 125 mL samples from all vessels for the analysis of the starting conditions for the next week.</li>
</ol>
3. Sample Analysis
<ol>
	<li>Test all beginning-of-the-week and end-of-the-week samples for ammonia-N, nitrate-N, nitrite-N, and biomass density.</li>
	<li>Measure biomass by standard total suspended solids (TSS) protocol, ASTM-D5907, using 0.45 &#181;m filters.
	<ol>
		<li>First weigh a filter paper and then filter 20-40 mL of sample using a vacuum filtration system. Dry the biomass/filter paper in an oven at 105 &#176;C for one hour, or until the weight of the biomass/filter paper no longer changes.</li>
		<li>Weigh biomass/filter paper, and subtract the initial mass of the filter paper. Divide this mass by the volume filtered to calculate the biomass density. Run in duplicate 11.</li>
	</ol>
	</li>
	<li>Measure ammonia, nitrate, and nitrite spectrophotometrically using a spectrophotometer.
	<ol>
		<li>Use 100 &#181;L of sample in the commercial method kit to determine ammonia concentration. Refer to the manufacturer&#39;s protocol.</li>
		<li>Use 1 mL of sample in the commercial method kit to determine nitrate concentration. Refer to the manufacturer&#39;s protocol.</li>
		<li>Use 10 mL of sample in the commercial method kit to determine nitrite concentration. Refer to the manufacturer&#39;s protocol.</li>
	</ol>
	</li>
	<li>Monitor environmental conditions (air temperature, solar radiation, wind speed) using a commercial weather station as well as tank/pond conditions (water temperature, pH, dissolved oxygen) using commercial probes and data logger. Refer to the manufacturer&#39;s protocol.</li>
</ol>
4. Statistical Analysis of Results
<ol>
	<li>Determine if the data collected is statistically normal. Determine normality of the data set using a Q-Q plot12.</li>
	<li>Determine correlations among parameters using Pearson&#39;s r or Spearman&#39;s p for normal and non-normal data, respectively13. Correlation parameters should include at least the following parameters: initial ammonia concentration, initial total nitrogen concentration, initial biomass density, ammonia removal rate, total nitrogen removal rate, biomass growth rate, and all environmental conditions.</li>
</ol>

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The authors have nothing to disclose.

System performance:
Over the course of an 8-week study, the productivity of the small- and large-scale vessels in a system were compared. In this study nitrogen and ammonia removal rates and biomass growth rates were used as measures of productivity of the treatment system. The system was operated as a semi-batch reactor, where each week was operated under discrete conditions. Representative results account for the first 8 weeks of system operation, however a full study would extend for much longer periods to account for seasonal variability in environmental conditions.
The methodology described above calls for mixing the paired system (small- and large-scale vessels) together every 7 days. Therefore the difference in productivity between the two scales over this time period depends solely on the different conditions in the two sized vessels. For example, if the light exposure in one of the reactors is significantly less than in the other, the biomass growth rates will be significantly different. Dead zones due to incomplete mixing, poor mass transfer, variable CO2 or pH, along with any other discrepant conditions between the two scales could cause differences in the productivity of the vessels within the paired systems.
On the other hand, if the productivity values of the small- and large-scale vessels in each system are equal, then it is likely that the small-scale vessel creates similar growth conditions as the large-scale vessel or any differences between the two different scaled reactors affect productivity negligibly. In this situation, the values from the small-scale system would likely be representative predictors of productivity in a full-scale system.
The treatment capacity of this system was evaluated based on its ability to remove nitrogen. Statistical correlations among all factors revealed a strong, positive correlation (&#961;=0.90) between the starting ammonia concentration and the ammonia removal rate. This same positive correlation was seen in a previous study conducted in the aquaria tanks 14. This positive trend between the ammonia removal rate and the starting ammonia concentration can be seen in Figure 3, which includes data collected from all RWPs and ATs. The nitrogen removal rates from the two vessel types can be compared to identify scale-specific trends once more data has been collected.
Variable reactor parameters:
Key reactor variables include the surface area to volume ratio and residence time. Reactors were operated in a semi-batch manner, with a complete mix of small and large vessels and 1/3 total reactor system volume replacement every 7 days. While the mixing period in this study was one week, as stated in section 2.3, this time could be modified depending on the growth and nutrient consumption rates of the photosynthetic cultures, as well as the ultimate application of the full-scale system. The surface area to volume ratio, which can be modified by changing the volume, will influence the mass transfer rate of gases as well as light exposure for photosynthetic organisms.
The volumes from the raceway pond and aquarium tank of each system were mixed at the beginning of each week to ensure that the starting conditions, specifically the inoculum culture, in both scales were equal. The length of time between mixing the two vessels can be modified based on the application. Since most alga are relatively slow-growing microorganisms, one week is recommended as the shortest amount of time that should be used. A longer period of time between mixing may reveal some variation in the productivity caused by small differences in environmental conditions between the two scales. Too much time between mixing the scales would allow for the microbial communities to diverge significantly, at which time the comparison between scales would no longer be accurate of the reactor conditions. Even when extending the length of time between mixing the two scales it is important to complete several repetitions in order to verify that any difference (or lack of differences) in productivities is significant.
The surface area to volume ratio can be modified by adjusting the working volume. This ratio impacts the mass transfer of gasses in and out of the vessel, as well as the amount of light the algae is exposed to. Depending on the type of vessel, the surface area to volume ratio (SA:V) and the light exposed surface area to volume ratio (LE-SA:V) may be different. In this study the walls of the aquaria tanks are transparent, allowing light in on all sides and through the top, whereas gas transfer will only occur through the water surface, meaning the SA:V and the LE-SA:V are unequal. However, the raceway ponds used in this study have opaque walls, so the SA:V and LE-SA:V are equal.
When focusing on scale up, the light exposed surface area to volume (LE-SA:V) ratio is important 1,7. A dense algae culture will result in minimal light penetration beyond the first few centimeters of water. Continuous mixing of a dense culture and a high LE-SA:V ratio will increase overall light exposure and should result in higher production yields. Continuous mixing will also aide in the mass transfer of gasses. To verify that the small-scale vessel accurately predicts large-scale productivity a full comparative study would need to be done.
Reactor constraints:
When setting up and operating this system for the first time there are a few things that may cause difficulties. First, it is very important to have at least 0.1 g/L of algae biomass in any vessel when scaling up. If the density is too low, it is highly likely that the inoculated algae will die off rapidly 10. Secondly, this system can handle high concentrations of ammonia, however the input ammonia concentration has to be increased slowly over many weeks 14,16,17. In this study the input ammonia concentration was raised at a very conservative rate, an approximate increase of 10 mgN/L every 3 weeks. Lastly, while monitoring all dissolved nitrogen species it is important that the nitrite concentrations are kept low. Nitrite can be toxic to algae and other organisms at high concentrations 18. If nitrite concentrations increase above 150 mg N/L, then additional volume should be removed and replaced with water to dilute the toxic nitrite concentrations.
Potential applications:
This methodology can be applied to verify the accuracy of input data used to simulate full-scale production processes in life cycle assessments (LCAs) and techno-economic analyses (TEAs) of full-scale production systems. Frequently, biomass growth and nutrient consumption rates from small-scale studies overestimate the abilities of a scaled-up system. Despite this, the vast majority of LCAs and TEAs use input values from small-scale studies to predict full-scale production values for their estimation of full-scale technologies 19,20,21,22,23. Before using the results from small-scale studies in this way, it should be verified that these results are a good representation of what can be expected from a full-scale system. Currently, there is no standardized methodology for collecting data for predictive studies of large-scale systems. The methodology presented here could be applied as a verification study.
In this study, nitrogen removal and biomass growth were used as the metrics for determining the effectiveness of treatment. This system could be easily adapted for other applications, including other waste streams (domestic or agricultural wastewater), monitored for other parameters (BOD, heavy metal, pathogen removal), observations on changes in microbial community, or altered from a semi-batch reactor to a continuously mixed reactor system. In any of these applications the protocol described here can be used to evaluate lab-scale and larger-scale systems.

Translation of bench-scale data to larger scale applications is a key step in the commercialization of bioprocesses. Production efficiencies in small-scale reactor systems, particularly those focusing on the use of microorganisms, have been shown to consistently over predict efficiencies occurring in commercial-scale systems 1,2,3,4. Challenges also exist in scaling up photosynthetic cultivation of algae and cyanobacteria from the laboratory scale to larger systems for the purpose of manufacturing high-value products, such as cosmetics and pharmaceuticals, for production of biofuels, and for the treatment of wastewater. The demand for large-scale algal biomass production is growing with the emerging industry for algae in biofuel, pharmaceuticals/nutraceuticals, and livestock feed 5. The methodology described in this manuscript aims to evaluate the influence of increasing scale of a photosynthetic reactor system on biomass growth rate and nutrient removal. The system presented here uses algae to remediate landfill leachate wastewater but can be adapted for a variety of applications.
Production efficiencies of large scale systems are often predicted using smaller scale experiments; however, several factors must be considered to determine the accuracy of these predictions, as scale has been shown to affect the performance of bioprocesses. For example, Junker (2004) presented results from a comparison of eight different-sized fermentation reactors, ranging from 30 L to 19,000 L, which showed that actual productivity at pilot- or commercial-scales was almost always lower than the values predicted using small-scale studies 4. Inequalities in vessel dimension, mixing power, agitation type, nutrient quality, and gas transfer were predicted to be the major causes for the decreased productivity 4. Similarly, it has been shown in algae growth reactors that biomass growth and biomass related products are nearly always reduced when scale is increased 6.
Biological, physical, and chemical factors change with the size of a reactor, with many of these factors influencing microbial activity at small scales differently than at larger scales 2,7. Since most full-scale systems for algae, such as raceway ponds, exist outdoors, one biological factor to consider is that microbial species and bacteriophages can be introduced from the surrounding environment, which may alter the microbial species present and thus the microbial function of the system. The activity of the microbial community will also be sensitive to environmental factors, such as light and temperature. Mass transfers of gasses and fluid motion are examples of physical factors that are influenced in the scale up of microbial processes. Achieving ideal mixing in small reactors is easy; however, with increasing scale, it becomes a challenge to engineer ideal-mixing conditions. At larger scales, reactors are more likely to have dead zones, non-ideal mixing, and reduced efficiencies in mass transfer 2. Since algae are photosynthetic organisms, commercial growth must account for changes in light exposure due to changes in water depth and surface area when increasing volume. High biomass density and/or low mass transfer rates can cause decreased CO2 concentrations and increased O2 concentrations, both of which may result in inhibition of biomass growth 8. Chemical factors in an algae growth system are driven by pH dynamics of the aquatic environment 2, which is consequently affected by changes in pH buffering compounds such as dissolved CO2 and carbonate species. These factors are compounded by complex interactions among the biological, physical, and chemical factors, often in unpredictable ways 9.
This study presents a paired reactor system designed to regulate and compare growth conditions in vessels of two different scales. The experimental protocol focuses on quantifying leachate treatment and algae growth; however, it could be adapted to monitor other metrics such as changes in the microbial community over time or the CO2 sequestration potential of algae. The protocol presented here is designed to evaluate the effect of scale on algal growth and nitrogen removal in a leachate treatment system.

<table><tbody><tr><td>Aquarium Tank</td><td></td><td></td><td>Any 100+ L aquarium tank with optically clear glass can be used</td></tr><tr><td>RW 3.5</td><td>MicroBio Engineering</td><td></td><td>Raceway Pond</td></tr><tr><td>Eurostar 100 digital</td><td>IKA</td><td>4238101</td><td>Overhead mixers</td></tr><tr><td>Leachate</td><td>Sandtown Landfill</td><td></td><td></td></tr><tr><td>Sampling Bottles</td><td>Nalgene</td><td></td><td>Plastic or glass, lab grade, 125-200&amp;nbsp;mL</td></tr><tr><td>Transfer Pumps</td><td></td><td></td><td>Garden type pump with drinking water quality hoses will be suitable</td></tr><tr><td>AmVer Salicylate Test &#039;N Tube</td><td>Hach</td><td>2606945</td><td>High Range Ammonia Tests</td></tr><tr><td>NitraVer X Nitrogen - Nitrate Reagent Set&amp;nbsp;</td><td>Hach</td><td>2605345</td><td>High Range Nitrate Tests</td></tr><tr><td>NitriVer 2 Nitrite Reagent Powder Pillows</td><td>Hach</td><td>2107569</td><td>High Range Nitrite Tests</td></tr><tr><td>Hach DR2400 Spectrophotmeter</td><td>Hach</td><td></td><td>The DR2400 was discontinued, but any DR series Hach spectrophotometer can be used in this application.&amp;nbsp;</td></tr><tr><td>EMD Microbiological Analysis Membrane Filters</td><td>Millipore</td><td>HAWG047S6</td><td>0.45 &amp;micro;m filters</td></tr></tbody></table>

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.

The aim of this study is to compare the biomass growth and nutrient removal capabilities of algal cultures grown in small- and large-scale reactors. This study uses two paired systems, referred to as System 1 and System 2, to duplicate its findings. These representative results are from an 8-week period, February through April, 2016. The first raceway pond was inoculated with algae originally sourced from an outdoor pond in Philadelphia, PA 14. This culture was grown to a high density in an aquarium tank. This inoculation resulted in a biomass density of 0.12 g/L in the RWP. After 2.5 weeks, the second raceway pond and aquarium tank were inoculated, resulting in starting biomass densities of approximately 0.18 g/L. After a few weeks, all ATs and RWPs were mixed together for a uniform biomass density and microbial population among all vessels; regular operation and monitoring began as described in the above protocol.
Starting and ending parameters were measured on a weekly basis as described in the Sample Analysis section 15. Initial conditions for biomass, ammonia and total nitrogen concentrations in all vessels ranged from 0.2-1.0 g/L, 3.1-14 mg NH3-N/L, and 8.1-20.1 mg N/L, respectively. The mean and standard deviation of the removal and growth rates recorded from each vessel are presented in Table 1. These conditions yielded biomass growth rates, and ammonia and total nitrogen removal rates ranging from -0.04-0.07 g/L/day, 0.39-1.61 mg N/L/day, and 0.26-1.47 mg N/L/day, respectively from all four vessels. Weekly nitrogen removal rates and biomass growth rates from System 1 and System 2 can be seen in Figure 2.
<img alt="Figure 2" src="/files/ftp_upload/55256/55256fig2.jpg" /> 
Figure 2. Summary of productivity over the representative study period. Ammonia removal rates (A), total nitrogen removal rates (B), and biomass growth rates (C) are presented in the top, middle and bottom panels, respectively. Results from system 1 are presented on the left, and system 2 on the right. Results from aquaria tanks and raceway ponds are represented on all graphs by X, and &#916;, respectively. <a href="http://cloudflare.jove.com/files/ftp_upload/55256/55256fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Statistical correlations were used to compare parameters and identify possible trends. Input parameters were: initial ammonia concentration, initial nitrate concentration, initial nitrite concentration, initial total nitrogen concentration, starting biomass concentration, ammonia removal rate, nitrate removal rate, nitrite removal rate, total nitrogen removal rate, biomass growth rate, water temperature, pH. The data collected was not statistically normal so Spearman&#39;s rho, the nonparametric correlation, was used. The strongest significant correlation was between the initial ammonia concentration and ammonia removal rate (&#961;=0.90). The trend between initial ammonia concentration and the ammonia removal rate can be seen in Figure 3.
<img alt="Figure 3" src="/files/ftp_upload/55256/55256fig3.jpg" /> 
Figure 3: Ammonia remova fo:keep-together.within-page=&#34;1&#34;l rate as a function of starting ammonia concentration. Data from all vessels over the representative 8 weeks are presented. Trend line R2 = 0.76. <a href="http://cloudflare.jove.com/files/ftp_upload/55256/55256fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<table fo:keep-together.within-page="1">
	<tbody>
		<tr>
			<td></td>
			<td>Ammonia Removal Rate (mgN/L)</td>
			<td>Total Nitrogen Removal Rate (mgN/L)</td>
			<td>Biomass Growth Rate (g biomass/L)</td>
		</tr>
		<tr>
			<td>RWP 1</td>
			<td>0.95 &#177; 0.36</td>
			<td>0.79 &#177; 0.38</td>
			<td>0.013 &#177; 0.029</td>
		</tr>
		<tr>
			<td>RWP 2</td>
			<td>1.08 &#177; 0.30</td>
			<td>1.01 &#177; 0.21</td>
			<td>0.034 &#177; 0.036</td>
		</tr>
		<tr>
			<td>Aquarium Tank 1</td>
			<td>0.87 &#177; 0.23</td>
			<td>0.803 &#177; 0.30</td>
			<td>0.005 &#177; 0.028</td>
		</tr>
		<tr>
			<td>Aquarium Tank 2</td>
			<td>0.88 &#177; 0.33</td>
			<td>0.94 &#177;0.22</td>
			<td>0.015 &#177; 0.019</td>
		</tr>
	</tbody>
</table>
Table 1. Mean &#177; standard deviation of productivity rates in individual vessels.

Watch this Scientific Journal Video about Comparison of Scale in a Photosynthetic Reactor System for Algal Remediation of Wastewater at JoVE.com

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

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, ...

comparison-scale-photosynthetic-reactor-system-for-algal-remediation

Nanyang Technological University

Research

JoVE Journal

Environment

9.0K Views.  Drexel University.  Een experimentele methode wordt voorgesteld om de prestaties van kleine (100 L) en grote (1000 L) vergelijken schaal reactoren ontworpen voor algen sanering van de stortplaats afvalwater. Systeemkenmerken, zoals specifiek oppervlak tot volumeverhouding, retentietijd biomassa dichtheid en afvalwater voer concentraties kan worden aangepast op basis van toepassing. 

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

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 ...

Physical, Chemical and Biological Characterization of Six Biochars Produced for the Remediation of Contaminated Sites

The physical and chemical properties of biochar vary based on feedstock sources and production conditions, making it possible to engineer biochars with specific functions (e.g. carbon sequestration, soil quality improvements, or contaminant sorption). In 2013, the International Biochar Initiative (IBI) made publically available their Standardized Product Definition and Product Testing Guidelines (Version 1.1) which set standards for physical and chemical characteristics for biochar. Six biochars made from three different feedstocks and at two temperatures were analyzed for characteristics related to their use as a soil amendment. The protocol describes analyses of the feedstocks and biochars and includes: cation exchange capacity (CEC), specific surface area (SSA), organic carbon (OC) and moisture percentage, pH, particle size distribution, and proximate and ultimate analysis. Also described in the protocol are the analyses of the feedstocks and biochars for contaminants including polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), metals and mercury as well as nutrients (phosphorous, nitrite and nitrate and ammonium as nitrogen). The protocol also includes the biological testing procedures, earthworm avoidance and germination assays. Based on the quality assurance / quality control (QA/QC) results of blanks, duplicates, standards and reference materials, all methods were determined adequate for use with biochar and feedstock materials. All biochars and feedstocks were well within the criterion set by the IBI and there were little differences among biochars, except in the case of the biochar produced from construction waste materials. This biochar (referred to as Old biochar) was determined to have elevated levels of arsenic, chromium, copper, and lead, and failed the earthworm avoidance and germination assays. Based on these results, Old biochar would not be appropriate for use as a soil amendment for carbon sequestration, substrate quality improvements or remediation.

Biochar is a carbon-rich material used as a soil amendment with the ability to sustainably sequester carbon, improve substrate quality and sorb contaminants. This protocol describes the 17 analytical methods used for the characterization of biochar, which is required prior to large scale implementation of these amendments in the environment.

The physical and chemical properties of biochar vary based on feedstock sources and production conditions, making it possible to engineer biochars with ...

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 ...

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 ...

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.

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 ...

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 ...

A Novel Bioreactor for High Density Cultivation of Diverse Microbial Communities

A novel reactor design, coined a high density bioreactor (HDBR), is presented for the cultivation and study of high density microbial communities. Past studies have evaluated the performance of the reactor for the removal of COD1 and nitrogen species2-4 by heterotrophic and chemoautotrophic bacteria, respectively. The HDBR design eliminates the requirement for external flocculation/sedimentation processes while still yielding effluent containing low suspended solids. In this study, the HDBR is applied as a photobioreactor (PBR) in order to characterize the nitrogen removal characteristics of an algae-based photosynthetic microbial community. As previously reported for this HDBR design, a stable biomass zone was established with a clear delineation between the biologically active portion of the reactor and the recycling reactor fluid, which resulted in a low suspended solid effluent. The algal community in the HDBR was observed to remove 18.4% of total nitrogen species in the influent. Varying NH4+ and NO3- concentrations in the feed did not have an effect on NH4+ removal (n=44, p=0.993 and n=44, p=0.610 respectively) while NH4+ feed concentration was found to be negatively related with NO3- removal (n=44, p=0.000) and NO3- feed concentration was found to be positively correlated with NO3- removal (n=44, p=0.000). Consistent removal of NH4+, combined with the accumulation of oxidized nitrogen species at high NH4+ fluxes indicates the presence of ammonia- and nitrite-oxidizing bacteria within the microbial community.

A novel reactor design, coined a high density bioreactor (HDBR), is presented for the cultivation and study of high density microbial communities. Here, the HDBR is successfully applied in a photobioreactor (PBR) configuration for the study of nitrogen metabolism by a mixed high density algal community.

A novel reactor design, coined a high density bioreactor (HDBR), is presented for the cultivation and study of high density microbial communities. Past ...

Bioengineering

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 ...

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, ...

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

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