Questo studio è supportato da un programma NSF (ricerca esperienze per gli studenti universitari), alla Washington University di St. Louis.

1. Alghe Coltivazione e scale-up <ol><li> Preparare il terreno di coltura con acqua deionizzata contenente 0,55 g / L -1 urea, 0,1185 g / L -1 KH 2 PO 4, 0,102 g / L -1 MgSO 4 · 7H 2 O, 0,015 g / L -1 FeSO 4 · 7H 2 O e 22,5 microelementi microlitri (18,5 g / L -1 H 3 BO 3, 21.0 g / L -1 CuSO 4 · 5H 2 O, 73,2 g / L -1 MnCl 2 · 4H 2 O, 13,7 g / L -1 CoSO 4 · 7H 2 O, 59,5 g / L -1 ZnSO 4 · 5H 2 O, 3,8 g / L -1 (NH 4) 6 Mo 7 O 24 · 4H 2 O, 0,31 g / L -1 NH 4 VO 3 ). Regolare il pH medio di 7-8. Sterilizzare mezzo di coltura con 0,22 micron filtro a siringa. </li><li> Seminare Chlorella sp. da una singola colonia su una piastra di agar fresco in una scossa flask contenente 50 mL di terreno con un&#39;ansa da inoculo sterile. Cultura alghe sotto 150 rpm e 30 ° C per sei giorni (condizioni di luce continua, flusso di fotoni = 40-50 mmol m -2 s -1). Controllo densità cellulare da uno spettrofotometro (OD 730). </li><li> Trasferire 50 mL coltura algale (fase di crescita medio-log, OD 730&gt; 1) in un pallone di vetro 2-L (con ~ 1 L mezzo di coltura sterilizzato). Pompa aria filtrata (o CO 2) nella coltura durante l&#39;incubazione (per 5 giorni). </li><li> Trasferire 1 L algale cultura in una damigiana di vetro 20-L contenente 15 L mezzo non sterilizzato cultura (in questa fase, il rischio di contaminazione microbica è piccola), poi algacoltura sotto stesse condizioni come indicato al punto 1.3. </li><li> Mettere 15 L di coltura fresco algale (OD 730 = 2) e 85 L mezzo non sterilizzato in una photobioreactor lastra piana (dotato di diodi emettitori di luce, regolatore del calcolatore, miscela di gas, analizzatori per cellulare densità ottica, pH, ossigeno discioltogen, temperatura e sciolto CO 2). Pompare la miscela aria / gas di scarico nel bioreattore. </li><li> Accuratamente lavare a secco fotobioreattore utilizzando etanolo al 70% dopo la raccolta della biomassa (OD 730&gt; 20). </li></ol> 2. Laboratorio Dimostrazione della Flue Gas Treatment Utilizzo Piccoli Fotobioreattori <ol><li> Seminare colture algali in bottiglie di vetro (200 ml / min a medio / bottiglia, OD iniziale 730 ~ 0,3). </li><li> Bruciare gas naturale e pompare il gas di combustione (~ 250 cm 3 min -1) attraverso un imbuto, un tubo del refrigerante, e una bottiglia di lavaggio 0,5 L (contenente acqua / calcare slurry). </li><li> I controllori di flusso di massa controllano il flusso del gas effluente in coltura algale (Figura 1). Impulsi di gas di combustione includono due modalità: gas-on di scarico e fumi-off (pompare aria invece). </li></ol> 3. Modello di Sviluppo Kinetic Il modello cinetico assume: (1) le colture sono sistema omogeneos. (2) concentrazione di CO 2 e l&#39;intensità della luce nelle culture sono i fattori limitanti per la crescita delle alghe. (3) CO 2 pressione parziale e il suo equilibrio fase liquida con H 2 CO 3, HCO 3 - e CO 3 2 - è semplificata con la legge di Henry). Le equazioni del modello sono: <img alt="Equazioni 1 e 2" fo:content-width="4in" src="/files/ftp_upload/50718/50718eq1and2.jpg" width="500px" /> X è la biomassa (kg · m -3). S è la disciolto CO 2 (mol · m -3). P è la pressione parziale di CO 2 nella fase gassosa (Pa). p i è la pressione parziale esimo composto tossico nel gas (come NO x e SO x). P max.i è la pressione parziale del gas tossico avere inibizione globale sulla crescita della biomassa. η i è il coefficiente empirico. K s è la costante di Michaelis-Mentendi CO 2 (mol · m -3). K I è la costante di inibizione di CO 2 (mol · m -3). K è la costante di Michaelis-Menten dell&#39;intensità luminosa (mol · m -2 · sec -1). H è la costante di Henry per la CO 2 (Pa · m 3 · mol -1). La K è la velocità di trasferimento di massa di CO 2 (ore -1). I è la media intensità della luce, mol · m -2 · sec -1, che può essere calcolato come segue (Eq. (3)) 9. <img alt="Equazione 3" fo:content-width="4in" src="/files/ftp_upload/50718/50718eq3.jpg" width="500px" /> La definizione di parametri del modello è in Tabella 1. Le condizioni iniziali presuppongono che biomassa e CO 2 disciolto concentrazioni sono 100 mg / L e 13 mmol / L, rispettivamente. Il coefficiente di trasferimento di massa volumetrica può essere stimata correlazione empiricazione di bioreattore parametri 10: <img alt="Equazione 4" fo:content-width="4in" src="/files/ftp_upload/50718/50718eq4.jpg" width="500px" /> P g / V è il consumo di energia del sistema areato nel bioreattore (W / m 3). u gs è la velocità superficiale del flusso di gas attraverso il bioreattore (m / sec). α, β, e γ sono costanti legati alle condizioni di miscelazione. <ol><li> Costruire un file di Simulink per la simulazione del modello (le schermate sono indicate nel materiale di supporto I). <ol><li> Scegliete File / Nuovo / Modello sull&#39;interfaccia MATLAB per creare un modello Simulink, e aperto &quot;Biblioteca Browser&quot; (schermata 1). </li><li> Scegli blocco &#39;sottosistema&#39; nel browser libreria per creare le sottosistemi per l&#39;equazione 1 e 2. Trascinare un blocco sottosistema il file del modello Simulink, cambiare il suo nome in &#39;equazione 1&#39;, e quindi ripetere la stessa procedura per Equazione 2. </li><li&gt; Crea blocchi e parametri appropriati a ciascun sottosistema (screen shot 3). Fare doppio clic blocco del &#39;equazione 1&#39;, scegliere i blocchi appropriati dal browser biblioteca e collegarli con le frecce che indicano la sequenza di calcolo, fare doppio clic sui blocchi per impostare i parametri, e ripetere la procedura per l&#39;altro sottosistema. Nota: 1) La sequenza deve iniziare con blocchi di ingresso e concludere con blocchi di uscita, 2) I blocchi operatore di addizione, sottrazione, moltiplicazione, divisione e integrazione può essere tutti trovati nel browser biblioteca, e suggeriamo agli utenti di esplorare i file di aiuto di la Simulink per capire come usarli, 3) Il solutore di ottimizzazione può essere impostato tramite i parametri percorso di simulazione / configurazione sulla barra degli strumenti. </li><li> Collegare i due sottosistemi per rappresentare le equazioni del modello (1 e 2). Collegare l&#39;uscita di un sottosistema all&#39;ingresso di un altro sottosistema dalla freccia se necessario. Ad esempio, la concentrazione di CO 2 disciolta è l&#39;Oscita nella equazione 2 sottosistema, e anche l&#39;ingresso della Equazione 1 sottosistema. </li><li> Utilizzare &#39;Pulse Generator&#39; isolato come gli ingressi per &#39;Equazione 2&#39; di simulare le CO 2 impulsi on-off; utilizzare blocco &#39;Constant&#39; come valore di input luce superficie. Fare doppio clic i blocchi di modificare i parametri come il periodo di tempo e l&#39;ampiezza. </li><li> Scegli blocco &#39;Mux&#39; nel browser biblioteca. Collegare tutte le uscite a &#39;Mux&#39; e poi collegarlo al &#39;To Workspace&#39; blocco che memorizza i risultati simulati. </li><li> Definire il &#39;tempo di arresto di simulazione&#39; nella barra degli strumenti superiore, fare clic sul pulsante &quot; <img src="/files/ftp_upload/50718/playarrow.jpg" alt="Arrow" width="10px" fo:content-width="0.1in" fo:src="/files/ftp_upload/50718/playarrow.jpg" /> &quot;Per avviare la simulazione, ed i risultati verranno visualizzati nel workspace di MATLAB (schermata 4). </li></ol></li><li> Applicare approccio di ottimizzazione dinamica al profilo di CO 2 ottimali condizioni. </li&gt; </ol> Per trovare le variazioni di afflusso di entrata CO 2 profilo (P opt) che massimizzano la produzione di biomassa 11, funzione MATLAB &#39;fmincon&#39; e CVP (controllo vettoriale di parametrizzazione) 12 sono utilizzati. Figura 2 illustra l&#39;algoritmo di ottimizzazione (vedi codici di programmazione MATLAB nel supporto Materiale II).

<ol>
	<li>Granite, E. J., O'Brien, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Review+of+novel+methods+for+carbon+dioxide+separation+from+flue+and+fuel+gases.">Review of novel methods for carbon dioxide separation from flue and fuel gases.</a> Fuel Process. Technol. 86, 1423-1434 (2005).</li><li>Chisti, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Biodiesel+from+microalgae.">Biodiesel from microalgae.</a> Biotechnol. Adv. 25, 294-306 (2007).</li><li>Li, Y., Horsman, M., Wu, N., Lan, C. Q., Dubois-Calero, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Biofuels+from+microalgae.">Biofuels from microalgae.</a> Biotechnol. Prog. 24, 815-820 (2008).</li><li>Schenk, P., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Second+generation+biofuels:+high-efficiency+microalgae+for+biodiesel+production.">Second generation biofuels: high-efficiency microalgae for biodiesel production.</a> BioEnergy Research. 1, 20-43 (2008).</li><li>Kumar, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Enhanced+CO2+fixation+and+biofuel+production+via+microalgae:+recent+developments+and+future+directions.">Enhanced CO2 fixation and biofuel production via microalgae: recent developments and future directions.</a> Trends Biotechnol. 28, 371-380 (2010).</li><li>Kumar, K., Dasgupta, C. N., Nayak, B., Lindblad, P., Das, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Development+of+suitable+photobioreactors+for+CO2+sequestration+addressing+global+warming+using+green+algae+and+cyanobacteria.">Development of suitable photobioreactors for CO2 sequestration addressing global warming using green algae and cyanobacteria.</a> Bioresour. Technol. 102, 4945-4953 (2011).</li><li>Lee, J. -. N., Lee, J. -. S., Shin, C. -. S., Park, S. -. C., Kim, S. -. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Methods+to+enhance+tolerances+of+Chlorella+KR-1+to+toxic+compounds+in+flue+gas.">Methods to enhance tolerances of Chlorella KR-1 to toxic compounds in flue gas.</a> Appl. Biochem. Biotechnol. 84-86, 329-342 (2000).</li><li>Zeiler, K. G., Heacox, D. A., Toon, S. T., Kadam, K. L., Brown, L. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+use+of+microalgae+for+assimilation+and+utilization+of+carbon+dioxide+from+fossil+fuel-fired+power+plant+flue+gas.">The use of microalgae for assimilation and utilization of carbon dioxide from fossil fuel-fired power plant flue gas.</a> Energy Conversion and Management. 36 (95), 707-712 (1995).</li><li>Mart&#237;nez, M. E., Camacho, F., Jim&#233;nez, J. M., Esp&#237;nola, J. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Influence+of+light+intensity+on+the+kinetic+and+yield+parameters+of+Chlorella+pyrenoidosa+mixotrophic+growth.">Influence of light intensity on the kinetic and yield parameters of Chlorella pyrenoidosa mixotrophic growth.</a> Process Biochem. 32 (96), 93-98 (1997).</li><li>Van't Riet, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Review+of+measuring+methods+and+results+in+nonviscous+gas-liquid+mass+transfer+in+stirred+vessels.">Review of measuring methods and results in nonviscous gas-liquid mass transfer in stirred vessels.</a> Ind. Eng. Chem. Process. 18, 357-364 (1979).</li><li>Methekar, R., Ramadesigan, V., Braatz, R. D., Subramanian, V. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Optimum+charging+profile+for+lithium-ion+batteries+to+maximize+energy+storage+and+utilization.">Optimum charging profile for lithium-ion batteries to maximize energy storage and utilization.</a> ECS Trans. 25, 139-146 (2010).</li><li>Kameswaran, S., Biegler, L. T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Simultaneous+dynamic+optimization+strategies:+Recent+advances+and+challenges.">Simultaneous dynamic optimization strategies: Recent advances and challenges.</a> Comput. Chem. Eng. 30, 1560-1575 .</li><li>He, L., Subramanian, V. R., Tang, Y. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Experimental+analysis+and+model-based+optimization+of+microalgae+growth+in+photo-bioreactors+using+flue+gas.">Experimental analysis and model-based optimization of microalgae growth in photo-bioreactors using flue gas.</a> Biomass Bioenergy. 41, 131-138 (2012).</li><li>Novak, J. T., Brune, D. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Inorganic+carbon+limited+growth+kinetics+of+some+freshwater+algae.">Inorganic carbon limited growth kinetics of some freshwater algae.</a> Water Res. 19 (85), 215-225 (1985).</li><li>Landry, M. R., Haas, L. W., Fagerness, V. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Dynamics+of+microbial+plankton+communities+experiments+in+Kaneohe+Bay,+Hawaii.">Dynamics of microbial plankton communities experiments in Kaneohe Bay, Hawaii.</a> Mar. Ecol. 16, 127-133 (1984).</li><li>Silva, H. J., Pirt, S. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Carbon+dioxide+inhibition+of+photosynthetic+growth+of+Chlorella.">Carbon dioxide inhibition of photosynthetic growth of Chlorella.</a> J. Gen. Microbiol. 130, 2833-2838 (1984).</li><li>Powell, E. E., Mapiour, M. L., Evitts, R. W., Hill, G. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Growth+kinetics+of+Chlorella+vulgaris+and+its+use+as+a+cathodic+half+cell.">Growth kinetics of Chlorella vulgaris and its use as a cathodic half cell.</a> Bioresour. Technol. 100, 269-274 (2009).</li><li>Sawyer, C. N., McCarty, P. L., Parkin, G. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Chemistry for environmental engineering and science. , 144 (2003).</li><li>Doucha, J., Straka, F., L&#237;vansk&#253;, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Utilization+of+flue+gas+for+cultivation+of+microalgae+Chlorella+sp.+in+an+outdoor+open+thin-layer+photobioreactor.">Utilization of flue gas for cultivation of microalgae Chlorella sp. in an outdoor open thin-layer photobioreactor.</a> J. Appl. Phycol. 17, 403-412 (2005).</li><li>Thimijan, R. W., Heins, R. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Photometric,+radiometric,+and+quantum+light+units+of+measure:+a+review+of+procedures+for+interconversion.">Photometric, radiometric, and quantum light units of measure: a review of procedures for interconversion.</a> Hortscience. 18, 818-822 (1983).</li></ol>

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In questo studio, abbiamo dimostrato il protocollo sperimentale per il salto di colture algali in fotobioreattori. Abbiamo anche esaminare diversi metodi per gli ingressi dei gas di scarico per promuovere la crescita delle alghe. Utilizzando un trasferimento di massa e il modello bio-reazione, dimostriamo che il coefficiente di CO 2 di trasferimento di massa K La (determinata dal bioreattore mescolando condizioni e CO 2 velocità superficiale) influenza fortemente la crescita delle alghe....

<table border="0" cellpadding="0" cellspacing="0" width="636">
	<tbody>
		<tr height="21"> 
			<td height="21" style="height:21px;width:212px;">Spectrophotometer</td>
			<td style="width:212px;">Thermal Scientific, Texas USA</td>
			<td style="width:212px;"> </td>
		</tr>
		<tr height="39">
			<td height="39" style="height:39px;width:212px;">CO2 gas analyzer</td>
			<td style="width:212px;">LI-COR, Biosciences, Nebraska USA</td>
			<td style="width:212px;"> </td>
		</tr>
		<tr height="39">
			<td height="39" style="height:39px;width:212px;">Mass flow controllers</td>
			<td style="width:212px;">OMEGA Engineering INC, Connecticut USA</td>
			<td style="width:212px;">FMA5416</td>
		</tr>
		<tr height="58">
			<td height="58" style="height:58px;width:212px;">Data acquisition card</td>
			<td style="width:212px;">Measurement Computing Corporation, Massachusetts USA</td>
			<td style="width:212px;">USB-1208FS</td>
		</tr>
		<tr height="39">
			<td height="39" style="height:39px;width:212px;">Filters</td>
			<td style="width:212px;">Aerocolloid LLC, Minnesota USA</td>
			<td style="width:212px;"> </td>
		</tr>
		<tr height="39">
			<td height="39" style="height:39px;width:212px;">MATLAB/Simulink</td>
			<td style="width:212px;">Mathworks, Massachusetts USA</td>
			<td style="width:212px;">R2010a</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:212px;">Glass bottles</td>
			<td style="width:212px;">Fisher USA</td>
			<td style="width:212px;"> </td>
		</tr>
	</tbody>
</table>

optimize flue gas settings to promote microalgae growth in photobioreactors via computer simulations

Gas di combustione delle centrali elettriche in grado di promuovere la coltivazione delle alghe e ridurre le emissioni di gas serra 1. Le microalghe non solo di catturare l&#39;energia solare più efficiente di piante 3, ma anche sintetizzare biocarburanti avanzati 2-4. In generale, CO 2 atmosferica non è una fonte sufficiente per sostenere la massima crescita delle alghe 5. D&#39;altra parte, le alte concentrazioni di CO 2 nel gas di scarico industriali hanno effetti negativi sulla fisiologia delle alghe. Di conseguenza, entrambe le condizioni di coltivazione (come nutrienti e luce) e il controllo del flusso del gas effluente nei fotobioreattori sono importanti per sviluppare un efficiente &quot;fumi per le alghe&quot; sistema. I ricercatori hanno proposto diverse configurazioni fotobioreattori 4,6 e strategie di coltivazione 7,8 con il gas di scarico. Qui vi presentiamo un protocollo che illustra come utilizzare i modelli per prevedere la crescita di microalghe in risposta al camino impostazioni del gas. Noi Perfsia sperimentali illustrazioni e le simulazioni del modello ORM per determinare le condizioni favorevoli per la crescita delle alghe con gas di scarico. Sviluppiamo un modello basato-Monod accoppiata con trasferimento di massa e le equazioni di intensità della luce per simulare la crescita di microalghe in un omogeneo foto-bioreattore. Il modello di simulazione a confronto algali consumi di gas di crescita e di scarico sotto diverse impostazioni dei fumi. Il modello illustra: 1) come la crescita delle alghe è influenzata da diversi coefficienti di trasferimento di massa volumetriche di CO 2, 2) come possiamo trovare ottimale concentrazione di CO 2 per la crescita delle alghe attraverso l&#39;approccio di ottimizzazione dinamica (DOA), 3) come possiamo progettare un rettangolare on-off impulsi fumi per promuovere la crescita della biomassa algale e di ridurre l&#39;utilizzo di gas di scarico. Sul lato sperimentale, presentiamo un protocollo per la coltivazione Chlorella sotto fumi (generata dalla combustione del gas naturale). I risultati sperimentali convalidano qualitativamente le previsioni del modello che i gas di scarico ad alta frequenza puLSES possono migliorare significativamente la coltivazione delle alghe.

La nostra precedente analisi sperimentali indicano che l&#39;esposizione dei fumi continua influenza negativamente la crescita Clorella, riducendo il tempo di CO 2, l&#39;esposizione è in grado di alleviare questa inibizione 13. Per comprendere meglio il flusso dei fumi e rapporto crescita delle alghe, sviluppiamo un modello empirico per simulare la crescita della biomassa in presenza di fumi. Partiamo dal presupposto che il gas di scarico contiene il 15% di CO 2 (nota: Il tipi...

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

Gas di combustione delle centrali elettriche è una conveniente fonte di CO 2 per la crescita delle alghe. Abbiamo costruito &quot;dei fumi delle alghe coltivazione&quot; prototipo dei sistemi e descritto come scalare il processo di coltivazione algale. Abbiamo dimostrato l&#39;utilizzo di un modello bio-reazione di trasferimento di massa per simulare e progettare il funzionamento ottimale del gas di combustione per la crescita di Chlorella sp. in alghe foto-bioreattori.

Ottimizzare le impostazioni dei gas di scarico per promuovere la crescita di microalghe in fotobioreattori tramite simulazioni al computer

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

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14.2K Views.  Washington University in St. Louis, St. Louis.  Gas di combustione delle centrali elettriche è una conveniente fonte di CO 2 per la crescita delle alghe. Abbiamo costruito "dei fumi delle alghe coltivazione" prototipo dei sistemi e descritto come scalare il processo di coltivazione algale. Abbiamo dimostrato l'utilizzo di un modello bio-reazione di trasferimento di massa per simulare e progettare il funzionamento ottimale del gas di combustione per la crescita di Chlorella sp. in alg...

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

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.

Analisi di acido grasso contenuto e la composizione in microalghe

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

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Measurement of Greenhouse Gas Flux from Agricultural Soils Using Static Chambers

Measurement of greenhouse gas (GHG) fluxes between the soil and the atmosphere, in both managed and unmanaged ecosystems, is critical to understanding the biogeochemical drivers of climate change and to the development and evaluation of GHG mitigation strategies based on modulation of landscape management practices. The static chamber-based method described here is based on trapping gases emitted from the soil surface within a chamber and collecting samples from the chamber headspace at regular intervals for analysis by gas chromatography. Change in gas concentration over time is used to calculate flux. This method can be utilized to measure landscape-based flux of carbon dioxide, nitrous oxide, and methane, and to estimate differences between treatments or explore system dynamics over seasons or years. Infrastructure requirements are modest, but a comprehensive experimental design is essential. This method is easily deployed in the field, conforms to established guidelines, and produces data suitable to large-scale GHG emissions studies.

This article showcases the static chamber-based method for measurement of greenhouse gas flux from soil systems. With relatively modest infrastructure investments, measurements may be obtained from multiple treatments/locations and over timeframes ranging from hours to years.

Misura del flusso di gas serra da terreni agricoli Uso statici Chambers

Measurement of greenhouse gas (GHG) fluxes between the soil and the atmosphere, in both managed and unmanaged ecosystems, is critical to understanding the ...

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.

Quantificazione dei metalli pesanti e altri contaminanti inorganici sulla produttività delle microalghe

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

Laboratory Simulation of an Iron(II)-rich Precambrian Marine Upwelling System to Explore the Growth of Photosynthetic Bacteria

A conventional concept for the deposition of some Precambrian Banded Iron Formations (BIF) proceeds on the assumption that ferrous iron [Fe(II)] upwelling from hydrothermal sources in the Precambrian ocean was oxidized by molecular oxygen [O2] produced by cyanobacteria. The oldest BIFs, deposited prior to the Great Oxidation Event (GOE) at about 2.4 billion years (Gy) ago, could have formed by direct oxidation of Fe(II) by anoxygenic photoferrotrophs under anoxic conditions. As a method for testing the geochemical and mineralogical patterns that develop under different biological scenarios, we designed a 40 cm long vertical flow-through column to simulate an anoxic Fe(II)-rich marine upwelling system representative of an ancient ocean on a lab scale. The cylinder was packed with a porous glass bead matrix to stabilize the geochemical gradients, and liquid samples for iron quantification could be taken throughout the water column. Dissolved oxygen was detected non-invasively via optodes from the outside. Results from biotic experiments that involved upwelling fluxes of Fe(II) from the bottom, a distinct light gradient from top, and cyanobacteria present in the water column, show clear evidence for the formation of Fe(III) mineral precipitates and development of a chemocline between Fe(II) and O2. This column allows us to test hypotheses for the formation of the BIFs by culturing cyanobacteria (and in the future photoferrotrophs) under simulated marine Precambrian conditions. Furthermore we hypothesize that our column concept allows for the simulation of various chemical and physical environments &#8212; including shallow marine or lacustrine sediments.

Laboratory Simulation of an IronII-rich Precambrian Marine Upwelling System to Explore the Growth of Photosynthetic Bacteria

We simulated a Precambrian ferruginous marine upwelling system in a lab-scale vertical flow-through column. The goal was to understand how geochemical profiles of O2 and Fe(II) evolve as cyanobacteria produce O2. The results show the establishment of a chemocline due to Fe(II) oxidation by photosynthetically produced O2.

Simulazione Laboratorio di ferro (II) ricchi di Precambriano Marine Upwelling sistema per esplorare la crescita di batteri fotosintetici

A conventional concept for the deposition of some Precambrian Banded Iron Formations (BIF) proceeds on the assumption that ferrous iron [Fe(II)] upwelling ...

A Gusseted Thermogradient Table to Control Soil Temperatures for Evaluating Plant Growth and Monitoring Soil Processes

Thermogradient tables were first developed in the 1950s primarily to test seed germination over a range of temperatures simultaneously without using a series of incubators. A temperature gradient is passively established across the surface of the table between the heated and cooled ends and is lost quickly at distances above the surface. Since temperature is only controlled on the table surface, experiments are restricted to shallow containers, such as Petri dishes, placed on the table. Welding continuous aluminum vertical strips or gussets perpendicular to the surface of a table enables temperature control in depth via convective heat flow. Soil in the channels between gussets was maintained across a gradient of temperatures allowing a greater diversity of experimentation. The gusseted design was evaluated by germinating oat, lettuce, tomato, and melon seeds. Soil temperatures were monitored using individual, battery-powered dataloggers positioned across the table. LED lights installed in the lids or along the sides of the gradient table create a controlled temperature chamber where seedlings can be grown over a range of temperatures. The gusseted design enabled accurate determination of optimum temperatures for fastest germination rate and the highest percentage germination for each species. Germination information from gradient table experiments can help predict seed germination and seedling growth under the adverse soil conditions often encountered during field crop production. Temperature effects on seed germination, seedling growth, and soil ecology can be tested under controlled conditions in a laboratory using a gusseted thermogradient table.

Traditional thermogradient tables create a range of temperatures across the surface. Welding gussets perpendicular to the surface of a thermogradient table will control temperature in depth increasing possible research applications.

Una tabella soffietto Thermogradient di controllo della temperatura del suolo per la valutazione di crescita delle piante e monitoraggio processi del suolo

Thermogradient tables were first developed in the 1950s primarily to test seed germination over a range of temperatures simultaneously without using a ...

Procedures of Laboratory Fumigation for Pest Control with Nitric Oxide Gas

Nitric oxide (NO) is a newly discovered fumigant for postharvest pest control. This paper provides detailed protocols for conducting NO fumigation on fresh products and procedures for residue analysis and product quality evaluation. An airtight fumigation chamber containing fresh fruit and vegetables is first flushed with nitrogen (N2) to establish an ultralow oxygen (ULO) environment followed by injection of NO. The fumigation chamber is then kept at a low temperature of 2 - 5 &#176;C for a specified time period necessary to kill a target pest to complete a fumigation treatment. At the end of a fumigation treatment, the fumigation chamber is flushed with N2 to dilute NO prior to opening the chamber to ambient air to prevent the reaction between NO and O2, which produces NO2 and may damage delicate fresh products. At different times after NO fumigation, NO2 in headspace and nitrate and nitrite in liquid samples were measured as residues. Product quality was evaluated after 2 weeks of post-treatment cold storage to determine effects of NO fumigation on product quality. Keeping&#160;O2 from reacting with NO is critical to NO fumigation and is an important part of the protocols. Measuring NO levels is challenging and a practical solution is provided. Possible protocol modifications are also suggested for measuring NO levels in the fumigation chambers as well as residues. NO fumigation has the potential to be a practical alternative to methyl bromide fumigation for postharvest pest control on fresh and stored products. This publication is intended to assist other researchers in conducting NO fumigation research for postharvest pest control and accelerating the development of NO fumigation for practical applications.

This paper describes nitric oxide (NO) fumigation protocols for postharvest pest control. Fumigation chambers are flushed with nitrogen (N2) to establish ultralow oxygen conditions before NO is injected. At the end, chambers are flushed with N2 to dilute NO before exposing products to ambient air to prevent exposure to NO2.

Procedure di fumigazione di laboratorio per il controllo dei parassiti con Gas di ossido di azoto

Nitric oxide (NO) is a newly discovered fumigant for postharvest pest control. This paper provides detailed protocols for conducting NO fumigation on ...

Lab-Scale Model to Evaluate Odor and Gas Concentrations Emitted by Deep Bedded Pack Manure

A lab-scaled simulated bedded pack model was developed to study air quality and nutrient composition of deep-bedded packs used in cattle mono-slope facilities. This protocol has been used to effectively evaluate many different bedding materials, environmental variables (temperature, humidity), and potential mitigation treatments that can improve air quality in commercial deep-bedded mono-slope facilities. The model is dynamic and allows researchers to easily collect many chemical and physical measurements from the bedded pack. Weekly measurements, collected over the course of six to seven weeks, allows sufficient time to see changes in air quality measurements over time as the bedded pack matures. The data collected from the simulated bedded packs is within the range of concentrations previously measured in commercial deep-bedded mono-slope facilities. Past studies have demonstrated that 8 - 10 experimental units per treatment are sufficient to detect statistical differences among the simulated bedded packs. The bedded packs are easy to maintain, requiring less than 10 minutes of labor per bedded packs per week to add urine, feces, and bedding. Sample collection using the gas sampling system requires 20 - 30 minutes per bedded pack, depending on the measurements that are being collected. The use of lab-scaled bedded packs allows the researcher to control variables such as temperature, humidity, and bedding source that are difficult or impossible to control in a research or commercial facility. While not a perfect simulation of &#34;real-world&#34; conditions, the simulated bedded packs serve as a good model for researchers to use to examine treatment differences among bedded packs. Several lab-scale studies can be conducted to eliminate possible treatments before trying them in a research or commercial-sized facility.

A protocol has been developed to measure gases, odors, and nutrient composition in lab-scaled bedded manure packs, which can be used to study ways to improve air quality in commercial cattle facilities using deep-bedded manure packs.

Modello di scala di laboratorio per valutare odore e le concentrazioni di Gas emesse dal profondo Bedded Pack letame

A lab-scaled simulated bedded pack model was developed to study air quality and nutrient composition of deep-bedded packs used in cattle mono-slope ...

Experimental Study of the Relationship Between Particle Size and Methane Sorption Capacity in Shale

The amount of adsorbed shale gas is a key parameter used in shale gas resource evaluation and target area selection, and it is also an important standard for evaluating the mining value of shale gas. Currently, studies on the correlation between particle size and methane adsorption are controversial. In this study, an isothermal adsorption apparatus, the gravimetric sorption analyzer, is used to test the adsorption capacity of different particle sizes in shale to determine the relationship between the particle size and the adsorption capacity of shale. Thegravimetric method requires fewer parameters and produces better results in terms of accuracy and consistency than methods like the volumetric method. Gravimetric measurements are performed in four steps: a blank measurement, preprocessing, a buoyancy measurement, and adsorption and desorption measurements. Gravimetric measurement is presently considered to be a more scientific and accurate method of measuring the amount of adsorption; however, it is time-consuming and requires a strict measuring technique. A Magnetic Suspension Balance (MSB) is the key to verify the accuracy and consistency of this method. Our results show that adsorption capacity and particle size are correlated, but not a linear correlation, and the adsorptions in particles sieved into 40 - 60 and 60 - 80 meshes tend to be larger. We propose that the maximum adsorption corresponding to the particle size is approximately 250 &#181;m (60 mesh) in the shale gas fracturing.

We use an isothermal adsorption apparatus, the gravimetric sorption analyzer, to test the adsorption capacity of different particle sizes of shale, in order to find out the relationship between particle size and the adsorption capacity of shale.

Studio sperimentale della relazione tra la dimensione delle particelle e la capacità di adsorbimento di metano in scisto

The amount of adsorbed shale gas is a key parameter used in shale gas resource evaluation and target area selection, and it is also an important standard ...

An Optimized Rhizobox Protocol to Visualize Root Growth and Responsiveness to Localized Nutrients

Roots are notoriously difficult to study. Soil is both a visual and mechanical barrier, making it difficult to track roots in situ without destructive harvest or expensive equipment. We present a customizable and affordable rhizobox method that allows the non-destructive visualization of root growth over time and is particularly well-suited to studying root plasticity in response to localized resource patches. The method was validated by assessing maize genotypic variation in plasticity responses to patches containing 15N-labeled legume residue. Methods are described to obtain representative developmental measurements over time, measure root length density in resource-containing and control patches, calculate root growth rates, and determine 15N recovery by plant roots and shoots. Advantages, caveats, and potential future applications of the method are also discussed. Although care must be taken to ensure that experimental conditions do not bias root growth data, the rhizobox protocol presented here yields reliable results if carried out with sufficient attention to detail.

Visualizing and measuring root growth in situ is extremely challenging. We present a customizable rhizobox method to track root development and proliferation over time in response to nutrient enrichment. This method is used to analyze maize genotypic differences in root plasticity in response to an organic nitrogen source.

Un protocollo di Rhizobox ottimizzato per visualizzare la crescita delle radici e tempi di risposta alle sostanze nutrienti localizzate

Roots are notoriously difficult to study. Soil is both a visual and mechanical barrier, making it difficult to track roots in situ without destructive ...

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.

Coltivazione di microalghe verdi in bolla colonna fotobioreattori e un saggio di lipidi neutri

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