Die vorliegende Arbeit beschäftigt sich mit rohstofflichen und verfahrenstechnischen Einflussfaktoren bei der Biomassepyrolyse. Ausgehend von der Entwicklung einer kleintechnischen Festbettpyrolyseapparatur, erfolgten experimentelle Untersuchungen an 26 biogenen Einsatzstoffen unter verschiedenen Prozessbedingungen. Die Apparatur erlaubt eine vollständige Bilanzierung und Gewinnung aller Produkte, zudem können Einflüsse durch sekundäre Reaktionen in der Gasphase minimiert werden. Die Einsatzstoffe, welche u. a. auch Zellstoff, Xylan und Alkali-Lignin einschließen, wurden hinsichtlich brennstofftechnischer und physikalischer Eigenschaften sowie der Stoffgruppenzusammensetzung charakterisiert. Sie repräsentieren eine große Bandbreite möglicher Zusammensetzungen. Bei den Prozessparametern wurde die Pyrolysetemperatur im Bereich von 200 bis 750 °C, die Aufheizrate zwischen 5 und 100 K/min, die Feststoffverweilzeit von 0 bis 30 min sowie die Partikelgröße (0 bis 5 mm) variiert. Aus den Untersuchungen zum Einfluss der Prozessparameter für die verschiedenen Einsatzstoffe wurden unter Anwendung einer geeigneten Bilanzierungsmethodik geschlossene Masse- und Elementbilanzen für jeden Versuchspunkt aufgestellt. Unter den Prozessvariablen konnte die Temperatur erwartungsgemäß als wichtigste Einflussgröße identifiziert werden. Der zweistufige Zersetzungsverlauf der Biomassen ermöglicht die mathematische Beschreibung der temperaturabhängigen Ausbeuten mittels der zweistufigen Boltzmann-Funktion für den gesamten Temperaturbereich mit hohen Bestimmtheitsmaßen. Die rohstofflichen Einflussgrößen wurden unter Anwendung der Rangkorrelationsmethode nach Spearman und der Produkt-Moment-Korrelation nach Pearson mit den definierten Zielgrößen (Ausbeuten, Produktzusammensetzung, Kokseigenschaften, Heizwerte, Energieeinbindung) bei verschiedenen Pyrolysetemperaturen korreliert. Neben der Stoffgruppenzusammensetzung konnten bei den rohstofflichen Einflussfaktoren die Gehalte an Alkalien sowie der Gesamtgehalt an potentiell katalytisch aktiven Bestandteilen (Na, K, Mg, Ca, Fe) als Haupteinflussgrößen identifiziert werden. Korrelationen ergeben sich auch für brennstofftechnische Eigenschaften, wobei neben dem Flüchtigen- und dem Aschegehalt, das O/C-Verhältnis signifikant ist. Die gefundenen statistischen Zusammenhänge können weitestgehend mechanistisch begründet werden. Zur Quantifizierung der ermittelten Zusammenhänge für die Zielgrößen wurden multiple Regressionsmodelle erstellt und anhand von Bestimmtheitsmaß, Informationskriterium und mittleren Modellfehlern bewertet. Somit konnten 42 Regressionsgleichungen für die Produktausbeuten bei verschiedenen Pyrolysetemperaturen entwickelt werden, die auf den Gehalten verschiedener Stoffgruppen und dem Gesamtgehalt an katalytisch aktiven Elementen basieren. Weitere 56 Regressionsgleichungen stehen für die Berechnung von Teer/Öl-Elementarzusammensetzung, Kokszusammensetzung, Teer/Öl-Heizwert sowie Energieeinbindung im Koks bei verschiedenen Pyrolysetemperaturen zur Verfügung. Die Prognoseeignung der Gleichungen wurde anhand eines weiteren Datensatzes für Apfeltrester überprüft. Für die Koks-, die Gas- und die Kondensatausbeute sowie die genannten Produkteigenschaften ergab sich eine gute Vorhersagequalität, die jedoch stark von der verwendeten Gleichung abhängt. Die Validierung mit Literaturdaten konnte aufgrund fehlender Datensätze, die sowohl die notwendigen Rohstoffparameter als auch Produktausbeuten und -eigenschaften enthalten, nur anhand der Koksausbeute erfolgen. Für verschiedene Biomassen und biogene Reststoffe führte dies zu einer guten Anpassung. Die mathematische Beschreibung der Ausbeuten und bestimmter Produkteigenschaften über Regressionsgleichungen auf Grundlage von Rohstoffparametern stellt einen vielversprechenden Ansatz für die Vorhersage der maximalen Ausbeuten bei bestimmten Bedingungen dar. Dies ermöglicht eine Abschätzung zur Einsatzeignung von Biomassen bzw. biogenen Reststoffen für verschiedene Anwendungszwecke. Bisher existiert kein derartiges Modell zur Vorhersage der definierten Zielgrößen. Grundsätzlich wäre die Entwicklung einfacher Gleichungen mit wenigen, einfach bestimmbaren und standardisierten Parametern erstrebenswert. Die Ergebnisse haben jedoch gezeigt, dass Ein-Variablen-Modelle die Trends zwischen den Biomassen aufgrund der komplexen Zusammenhänge zwischen Pyrolyseverhalten und Rohstoffparametern häufig nicht richtig wiedergeben können. Für robuste Modelle sind somit mindestens zwei unabhängige Modellparameter mit idealerweise gegensätzlichem Einfluss notwendig.:Abkürzungs- und Symbolverzeichnis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . x Abbildungsverzeichnis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xvii Tabellenverzeichnis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xxiii 1 Einleitung und Zielstellung . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 2 Kenntnisstand . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 2.1 Zusammensetzung und Struktur von Lignocellulosen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 2.1.1 Allgemeine chemische Zusammensetzung . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2.1.2 Struktureller Aufbau . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 2.1.3 Vorkommen und Einbindungsformen von anorganischen Bestandteilen . . . . . . . . . . . . . . . . . . . 14 2.2 Möglichkeiten zur Untersuchung der Pyrolyse von Biomassen . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 2.2.1 Untersuchungsmethoden . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 2.2.2 Verwendete Reaktoren zur Untersuchung der Biomassepyrolyse . . . . . . . . . . . . . . . . . . . . . . . . 18 2.3 Reaktionsabläufe bei der Biomassepyrolyse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 2.4 Einflussfaktoren auf Pyrolyseproduktverteilung und -eigenschaften . . . . . . . . . . . . . . . . . . . . . . . 25 2.4.1 Einfluss rohstofflicher Parameter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 2.4.2 Einfluss verfahrenstechnischer Parameter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 2.5 Beschreibung und Vorhersage des Pyrolyseverhaltens von Biomasse . . . . . . . . . . . . . . . . . . . . . 39 2.5.1 Empirische Modelle basierend auf statistischen Methoden . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 2.5.2 Kinetische Modelle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 2.5.3 Modelle auf Basis der Stoffgruppenzusammensetzung . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 2.5.4 Netzwerkpyrolysemodelle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 2.6 Schlussfolgerungen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 3 Untersuchungsmethodik . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 3.1 Einsatzmaterialien und deren Charakterisierung . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 3.1.1 Biomassen und Vorbehandlung . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 3.1.2 Charakterisierungsmethoden . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 3.2 Entwicklung einer apparativen Einrichtung zur Bilanzierung des Biomassepyrolyseprozesses . . . 55 3.2.1 Anforderungen und Zielstellung . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 3.2.2 Konzeption, Dimensionierung und Optimierung . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 3.2.3 Endgültige Konfiguration der Laborpyrolyseanlage (LPA) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64 3.3 Durchführung der Bilanzversuche an der LPA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .66 3.3.1 Parametervariationen bei der Festbettpyrolyse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 3.3.2 Versuchsvorbereitung und -durchführung . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 3.3.3 Produktrückgewinnung und -aufarbeitung . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 3.4 Methodik bei der Bilanzierung des Pyrolyseprozesses im Festbettreaktor . . . . . . . . . . . . . . . . . . 69 3.4.1 Bilanzgleichungen und -annahmen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 3.4.2 Fehlerabschätzung . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72 4 Ergebnisse zur Charakterisierung der Einsatzmaterialien . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74 4.1 Brennstofftechnische Parameter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74 4.2 Chemisch-strukturelle Parameter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79 4.3 Physikalische Parameter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .86 5 Einfluss verfahrenstechnischer und rohstofflicher Parameter . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 5.1 Bilanzfehler und Wiederholbarkeit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 5.1.1 Vergleich der Bilanzierungsvarianten und Bilanzfehler . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 5.1.2 Wiederholbarkeit der Ergebnisse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 5.2 Einfluss verfahrenstechnischer Parameter auf Produktverteilung und -zusammensetzung . . . . 94 5.2.1 Einfluss radialer Temperaturgradienten in der Biomasseschüttung . . . . . . . . . . . . . . . . . . . . . 94 5.2.2 Pyrolysetemperatur . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96 5.2.3 Empirische Gleichungen für die Temperaturabhängigkeit der Produktausbeuten . . . . . . . . . 103 5.2.4 Aufheizgeschwindigkeit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106 5.2.5 Feststoffverweilzeit bei Pyrolyseendtemperatur . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110 5.3 Einfluss rohstofflicher Parameter auf Produktverteilung und -zusammensetzung . . . . . . . . . . . 111 5.3.1 Partikelgröße . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111 5.3.2 Pyrolyse von Zellstoff, Xylan und Alkali-Lignin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113 5.4 Kombinierte Betrachtungen zum Temperatur- und Rohstoffeinfluss . . . . . . . . . . . . . . . . . . . . . 120 6 Mathematische Zusammenhänge zwischen Rohstoffeigenschaften und Pyrolyseverhalten . . . . 133 6.1 Korrelation mit Rohstoffeigenschaften . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133 6.1.1 Produktausbeuten . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134 6.1.2 Produkteigenschaften . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140 6.1.3 Schlussfolgerungen zur Korrelation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154 6.2 Regressionsanalyse und Multiple Regression zur Beschreibung des Pyrolyseverhaltens . . . . . 155 6.2.1 Modellvergleich am Beispiel der Koksausbeute bei 500 °C . . . . . . . . . . . . . . . . . . . . . . . . . . 155 6.2.2 Gleichungen zur Berechnung der Produktausbeuten . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160 6.2.3 Gleichungen zur Berechnung der Produkteigenschaften . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170 6.2.4 Schlussfolgerungen zur Regression . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173 7 Vorhersagemöglichkeiten für das Pyrolyseverhalten . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174 7.1 Validierung der Modellgleichungen mit internem Datensatz . . . . . . . . . . . . . . . . . . . . . . . . . . . 174 7.2 Validierung mit Literaturdaten zur Festbettpyrolyse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179 8 Zusammenfassung und Ausblick . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .181 Literatur . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .187 Anhang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .208 A Weiterführende Informationen zu Kapitel 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .208 B Weiterführende Informationen zur Untersuchungsmethodik . . . . . . . . . . . . . . . . . . . . . . . . . . . . .211 C Ergebnisse zur Einsatzstoffcharakterisierung . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 239 D Ergebnisse zum Einfluss verfahrenstechnischer und rohstofflicher Parameter . . . . . . . . . . . . . . . 272 E Ergebnisse zur Korrelation des Pyrolyseverhaltens . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .314 F Ergebnisse zur Regression . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .348 G Ergebnisse zur Vorhersage des Pyrolyseverhaltens. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .361 / The intention of this work was an intensive study of the influence of feedstock properties and process variables on biomass pyrolysis. Due to a lack in consistent data sets, including various feedstock parameters as well as product yields, compositions, and further properties, a laboratory fixed bed reactor was developed to overcome this problem. The pyrolysis reactor was used for experiments with 26 biogenous feedstock under variable process conditions. The reactor is suitable to assure nearly closed mass balances and a complete product recovery. Furthermore, it allows the minimization of secondary reactions. The used feedstock, which include cellulose, xylan, and lignin amongst others, represent a broad range of possible compositions and were intensively characterized by determination of fuel and physical properties as well as biopolymer composition. The varied process parameters are: temperature between 200 and 700 °C, heating rate in the range of 5 to 100 K/min, solid residence time from 0 to 30 min, and particle size up to 5 mm. Closed mass and element balances were done for every set of parameters. As expected, amongst process variables the temperature was identified as the main factor influencing biomass pyrolysis. The temperature depending products yields could be fitted well by the double boltzmann approach due to the two-stage pyrolytic decomposition of biomass. Correlation of feedstock properties with different target parameters, including yields, product composition, heating values, remaining energy content in char, and char properties, was done by Spearman´s rank correlation and Pearson´s correlation for different temperatures. Biopolymer composition as well as alkaline content and total content of potential catalytic elements (Na, K, Ca, Mg, Fe) were identified as main factors influencing biomass pyrolysis product yields and compositions. Further correlations arise with fuel properties like volatile matter and ash content besides O/C atomic ratio. The obtained correlations can be mainly related to pyrolysis mechanisms. The received relationships were quantified by means of multiple regression models. Model evaluation was done by coefficient of determination, information criteria and mean squared errors. 42 regression models, based on different biopolymer contents and the total content of catalytic elements, were provided for the mathematical description of product yields for different process temperatures. Another 56 equations are suitable for the calculation of product properties like tar/oil and char composition, tar/oil heating value, and remaining energy content in the char at different temperatures. The predictability of the regression models was proved using another data set for apple pomace. The yields of char, gas, and condensate as well as the aforementioned product properties can be predicted very well, although, the predictability varies with the applied equation. Validation of the models by literature data was only possible for the char yield, because of the mentioned lack in suitable and complete data sets. Application of regression model to fixed bed char yields for different biomass and biogenous residues from literature resulted in a good predictability. Mathematical description of pyrolysis product yields and properties by means of regression models based on feedstock parameters is a promising approach to predict maximum yields at defined conditions and, therefore, to make an estimation of suitability of the biomass to different applications. Up to now such models do not exist. In general, the development of simple equations based on a few standardized parameters which are easy to determine is worthwhile. Hence, the results showed that the overall trend between different biomass feeds was often not predicted correctly using one-parameter models. This is due to the complex relationships between pyrolysis behavior and feedstock properties. Consequently, at least two parameter models, where the variables show the opposite trends, were most appropriate.:Abkürzungs- und Symbolverzeichnis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . x Abbildungsverzeichnis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xvii Tabellenverzeichnis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xxiii 1 Einleitung und Zielstellung . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 2 Kenntnisstand . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 2.1 Zusammensetzung und Struktur von Lignocellulosen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 2.1.1 Allgemeine chemische Zusammensetzung . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2.1.2 Struktureller Aufbau . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 2.1.3 Vorkommen und Einbindungsformen von anorganischen Bestandteilen . . . . . . . . . . . . . . . . . . . 14 2.2 Möglichkeiten zur Untersuchung der Pyrolyse von Biomassen . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 2.2.1 Untersuchungsmethoden . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 2.2.2 Verwendete Reaktoren zur Untersuchung der Biomassepyrolyse . . . . . . . . . . . . . . . . . . . . . . . . 18 2.3 Reaktionsabläufe bei der Biomassepyrolyse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 2.4 Einflussfaktoren auf Pyrolyseproduktverteilung und -eigenschaften . . . . . . . . . . . . . . . . . . . . . . . 25 2.4.1 Einfluss rohstofflicher Parameter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 2.4.2 Einfluss verfahrenstechnischer Parameter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 2.5 Beschreibung und Vorhersage des Pyrolyseverhaltens von Biomasse . . . . . . . . . . . . . . . . . . . . . 39 2.5.1 Empirische Modelle basierend auf statistischen Methoden . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 2.5.2 Kinetische Modelle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 2.5.3 Modelle auf Basis der Stoffgruppenzusammensetzung . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 2.5.4 Netzwerkpyrolysemodelle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 2.6 Schlussfolgerungen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 3 Untersuchungsmethodik . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 3.1 Einsatzmaterialien und deren Charakterisierung . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 3.1.1 Biomassen und Vorbehandlung . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 3.1.2 Charakterisierungsmethoden . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 3.2 Entwicklung einer apparativen Einrichtung zur Bilanzierung des Biomassepyrolyseprozesses . . . 55 3.2.1 Anforderungen und Zielstellung . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 3.2.2 Konzeption, Dimensionierung und Optimierung . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 3.2.3 Endgültige Konfiguration der Laborpyrolyseanlage (LPA) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64 3.3 Durchführung der Bilanzversuche an der LPA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .66 3.3.1 Parametervariationen bei der Festbettpyrolyse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 3.3.2 Versuchsvorbereitung und -durchführung . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 3.3.3 Produktrückgewinnung und -aufarbeitung . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 3.4 Methodik bei der Bilanzierung des Pyrolyseprozesses im Festbettreaktor . . . . . . . . . . . . . . . . . . 69 3.4.1 Bilanzgleichungen und -annahmen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 3.4.2 Fehlerabschätzung . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72 4 Ergebnisse zur Charakterisierung der Einsatzmaterialien . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74 4.1 Brennstofftechnische Parameter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74 4.2 Chemisch-strukturelle Parameter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79 4.3 Physikalische Parameter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .86 5 Einfluss verfahrenstechnischer und rohstofflicher Parameter . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 5.1 Bilanzfehler und Wiederholbarkeit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 5.1.1 Vergleich der Bilanzierungsvarianten und Bilanzfehler . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 5.1.2 Wiederholbarkeit der Ergebnisse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 5.2 Einfluss verfahrenstechnischer Parameter auf Produktverteilung und -zusammensetzung . . . . 94 5.2.1 Einfluss radialer Temperaturgradienten in der Biomasseschüttung . . . . . . . . . . . . . . . . . . . . . 94 5.2.2 Pyrolysetemperatur . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96 5.2.3 Empirische Gleichungen für die Temperaturabhängigkeit der Produktausbeuten . . . . . . . . . 103 5.2.4 Aufheizgeschwindigkeit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106 5.2.5 Feststoffverweilzeit bei Pyrolyseendtemperatur . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110 5.3 Einfluss rohstofflicher Parameter auf Produktverteilung und -zusammensetzung . . . . . . . . . . . 111 5.3.1 Partikelgröße . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111 5.3.2 Pyrolyse von Zellstoff, Xylan und Alkali-Lignin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113 5.4 Kombinierte Betrachtungen zum Temperatur- und Rohstoffeinfluss . . . . . . . . . . . . . . . . . . . . . 120 6 Mathematische Zusammenhänge zwischen Rohstoffeigenschaften und Pyrolyseverhalten . . . . 133 6.1 Korrelation mit Rohstoffeigenschaften . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133 6.1.1 Produktausbeuten . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134 6.1.2 Produkteigenschaften . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140 6.1.3 Schlussfolgerungen zur Korrelation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154 6.2 Regressionsanalyse und Multiple Regression zur Beschreibung des Pyrolyseverhaltens . . . . . 155 6.2.1 Modellvergleich am Beispiel der Koksausbeute bei 500 °C . . . . . . . . . . . . . . . . . . . . . . . . . . 155 6.2.2 Gleichungen zur Berechnung der Produktausbeuten . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160 6.2.3 Gleichungen zur Berechnung der Produkteigenschaften . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170 6.2.4 Schlussfolgerungen zur Regression . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173 7 Vorhersagemöglichkeiten für das Pyrolyseverhalten . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174 7.1 Validierung der Modellgleichungen mit internem Datensatz . . . . . . . . . . . . . . . . . . . . . . . . . . . 174 7.2 Validierung mit Literaturdaten zur Festbettpyrolyse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179 8 Zusammenfassung und Ausblick . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .181 Literatur . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .187 Anhang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .208 A Weiterführende Informationen zu Kapitel 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .208 B Weiterführende Informationen zur Untersuchungsmethodik . . . . . . . . . . . . . . . . . . . . . . . . . . . . .211 C Ergebnisse zur Einsatzstoffcharakterisierung . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 239 D Ergebnisse zum Einfluss verfahrenstechnischer und rohstofflicher Parameter . . . . . . . . . . . . . . . 272 E Ergebnisse zur Korrelation des Pyrolyseverhaltens . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .314 F Ergebnisse zur Regression . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .348 G Ergebnisse zur Vorhersage des Pyrolyseverhaltens. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .361

Le développement de biofilms est étudié sur de longues périodes (de deux à sept mois) dans des réacteurs à disque tournant (RBC) et à lit fixe alimentés par des eaux résiduaires domestiques ou des substrats synthétiques en continu à l’échelle du laboratoire. Deux réacteurs ont été spécialement conçus pour des expériences. Les biofilms ont été soumis à des stress physiques (forces hydrodynamiques) ou chimiques (antibiotique). L’activité biologique des réacteurs a été suivie au cours du temps (dégradation de la pollution carbonée et azotée). Les phénomènes de détachement et de redéveloppement des biofilms ont été caractérisés sur des surfaces lisses ou structurées par des techniques d’analyse d’images non destructives. La quantité globale de biomasse présente est évaluée par l’opacité du biofilm et cette méthode d’évaluation a été validée par comparaison avec des méthodes classiques destructives (coloration au Cristal Violet, matières sèches). La macrostructure du biofilm, liées aux phénomènes de croissance, détachement et recroissance, a été évaluée à l’aide de deux méthodes de caractérisation de la texture visuelle : la méthode de cooccurrence de niveaux de gris (SGLDM) et la longueur des segments (GLRLM). Le travail montre l’efficacité de l’analyse d’images comme une méthode rapide et peu onéreuse dans l’étude des biofilms sur le long terme. / The development of biofilm has been studied over long periods of time (two to seven months) in laboratory-scale rotating biological contactors and fixed bed reactors continuously fed with municipal wastewater or synthetic growth media. Two reactors have been specifically designed for this purpose. The biofilms have been subject to hydrodynamic and chemical (antibiotics) stresses. The overall biological activity of the reactors have been monitored, in terms of carbon and nitrogen removal. The phenomena of sloughing and re-growth have been characterized on smooth and rough surfaces using image analysis non-destructive techniques. The amount of biomass present on the substratum has been evaluated by the biofilm opacity and this monitoring method has been validated by comparison with destructive methods such as crystal violet staining and dry weight. The biofilm macrostructure, related to growth, sloughing and re-growth phenomena, has been evaluated through visual texture characterization of the scanning gray level co-occurrence matrix (SGLDM) and the gray level run length method (GLRLM). The results shows the efficiency of image analysis as a rapid and cheap method to monitor biofilm development on the long term.

Le couplage oxydant du méthane (OCM) est une réaction complexe de catalyse hétérogène, permettant la conversion directe du méthane en éthylène, pour un coût énergétique moindre par rapport aux procédés industriels indirects actuels. L’OCM nécessite une température supérieure à 700°C, à pression atmosphérique. Il y a donc compétition avec l’oxydation totale. Dans les nombreuses études rapportées dans la littérature, la limite de 25 % de rendement en C2 (éthane + éthylène) n’a pas été franchie. Les mécanismes proposés ne sont pas applicables à tous les catalyseurs actifs ou valables pour un large domaine de conditions opératoires. Une nouvelle manière d’aborder cette réaction est de prendre en compte la plus large diversité possible des paramètres intervenant dans ce procédé, de la formulation aux réacteurs en vue d'optimiser les performances. La présente étude a permis d’extraire des descripteurs pertinents du processus de l’OCM à partir de données expérimentales et d’établir certaines corrélations entre descripteurs et performances. Des catalyseurs LaSrCaO ont été sélectionnés après tests à haut débit en réacteur parallèle à lit fixe et un modèle micro-cinétique de l’OCM dans ce réacteur a été validé grâce aux données obtenues. D’autres expériences ont été menées avec succès en réacteur à membrane dense pour améliorer la productivité en éthylène. Le rôle joué par la composition de surface des catalyseurs a été identifié et une analyse critique de la méthode générale mise en œuvre conclut ce travail / The oxidative coupling of methane (OCM) is a complex heterogeneous catalytic reaction allowing the direct conversion of methane to ethylene, at a lower energetic cost than the current industrial processes. OCM requires a temperature higher than 700°C at atmospheric pressure. Hence, there is competition with total oxidation. In the numerous studies reported in literature, the limit of 25% C2 (ethane + ethylene) yield could not be overtaken. Proposed mechanisms are not relevant for all active materials or on all operating condition ranges. A new way to approach the reaction would be to take into account the wider possible panel of parameters involved in this process, from formulation to reactors targeting at process optimisation. The present study permitted to extract relevant descriptors of OCM process from experimental data and establish relationships between descriptors and performances. LaSrCaO catalysts were selected and tested in a parallel fixed-bed reactor and the data obtained were used to validate a micro-kinetic model in this reactor. Experiments were also performed successfully in a dense membrane reactor to improve ethylene productivity. The role played catalyst surface composition was also identified and a critical analysis of the global method implemented concludes this work

Esta pesquisa objetivou enriquecer biomassa capaz de realizar a oxidação anaeróbia do amônio (anammox) utilizando inóculo proveniente de reator nitrificante-desnitrificante, com a finalidade de estabelecer biofilme nitrificante-anammox em reator de leito fixo. O enriquecimento foi realizado em reator operado em bateladas sequenciais (RBS), com volume útil de 5 L e tempo de ciclo, inicialmente, de 56 h, e depois, sem tempo predeterminado (estratégias I e II). Após 89 dias de operação, 27,2 mg de \'N\'-\'N0 IND.2\'POT.-\'/L e 32,1 mg de \'N\'-\'NH IND.4\'POT.+\'/L foram consumidos concomitantemente. A estratégia III consistiu de batelada alimentada com ciclos de sete dias com afluente contendo 210 mg de cada composto nitrogenado. Na última estratégia (IV) a operação foi com ciclos de 24 h. Nessa etapa, a carga nitrogenada aplicada (CNA) foi aumentada de 155 g de \'N\' (\'N\'-\'N0 IND.2\'POT.-\' \'N\'-\'NH IND.4\'POT.+\')/\'M POT.3\' dia para 1.405,7 g de \'N\'/\'M POT.3\' dia com eficiências de conversão de nitrogênio de 91,7% e 98,0%, respectivamente. Essa biomassa foi inoculada em reator de leito fixo ascendente (RLF) visando estabelecimento da biomassa anammox em meio suporte (PEBD). Sob tais condições foi obtido eficiência de conversão de nitrogênio de 97,6% e carga nitrogenada removida média de 598,5 \'+ OU -\' 22,5 g \'N\'/\'M POT.3\' dia. Após estabelecimento de biomassa anammox, foi adicionado lodo ativado da indústria Volkswagen (São Carlos-SP) para formação de biofilme nitrificante-anammox. Nessa fase, a remoção de nitrogênio foi de 19,2% para CNA de 112,2 g \'N\'/\'M POT.3\' dia. A atividade anammox específica máxima foi 33,5 mg \'N\'-\'NH IND.4\'POT.+\'/g SSV h com a biomassa submetida à 50 rpm. Paralelamente ao processo de enriquecimento, foi verificada a influência de micronutrientes em condições nitrificantes em três quimiostatos, nas seguintes condições: Q1 alimentado com meio contendo solução de micronutrientes completa, Q2 alimentado sem solução de micronutrientes e Q3 alimentado com solução de micronutrientes sem o elemento Boro (quimiostato experimental). Nas três condições a estabilidade foi atingida com 11 dias de operação com conversão média de nitrogênio amoniacal de 99 \'+ OU -\' 1,5%, 94,6\'+ OU -\' 6,3% e 93,3\'+ OU -\' 7,3%, para Q1, Q2 e Q3, respectivamente, para 79 mg \'N\'-\'NH IND.4\'POT.+\'/L afluente. Após 450 dias de operação do RBS foi constatado semelhança do clones com Brocadia anammoxidans, Planctomycetes, Proteobacteria, Chlorobi, Nitrospira, filo Chloroflexi e ao filo candidato OP 11. A composição microbiana encontrada no RLF com 139 dias de operação (final da fase anammox) foi de 48% dos clones relacionados à B. anammoxidans, 4% relacionados à Planctomycetes não cultivados, 12% relacionados à Proteobacteria, 8% relacionados à Chlorobi, 24% relacionados à Nitrospira, 4% relacionados ao filo Chloroflexi. Pode-se concluir que a biomassa aderida em PEBD selecionou positivamente microrganismos anammox e Nitrospira e negativamente aos filamentos relacionados ao filo Chloroflexi. / This research aimed to enhance biomass capable of performing anaerobic ammonia oxidation (anammox) using inoculum from nitrifying-denitrifying reactor, with the goal of establishing nitrifying-anammox biofilm in fixed bed reactor. The enrichment was performed in sequencing batch reactor (SBR), with a volume of 5 L and cycle time, initially, 56 h, and then, without pre-set time (strategies I and II). After 89 operation days, 27.2 mg \'N\'-\'N0 IND.2\'POT.-\'/L and 32.1 mg \'N\'-\'NH IND.4\'POT.+\'/L were consumed concomitantly. The strategy consisted of fed batch III with seven days cycles with influent containing 210 mg of each nitrogen compound. The last strategy (IV) was with 24 h/cycle. At this strategy, the nitrogen applied load (NAL) was increased from 155 \'N\' (\'N\'-\'N0 IND.2\'POT.-\' + \'N\'-\'NH IND.4\'POT.+\')/\'M POT.3\' to 1405.7 g \'N\'/\'M POT.3\' day with conversion efficiencies of 91.7% nitrogen and 98.0%, respectively. This biomass was inoculated into fixed bed reactor up (FBR) in order to establish the anammox biomass in support medium (LDPE). Under such conditions was obtained nitrogen conversion efficiency of 97.6% and nitrogen load removed an average of 598.5 \'+ OU -\' 22.5 g \'N\'/\'M POT.3\' day. After establishment of anammox biomass it was added activated sludge - Volkswagen industry (São Carlos-SP) - for nitrifying-anammox biofilm. At that stage the removaI of nitrogen was 19.2% to 112.2 g CNA \'N\'/\'M POT.3\' day. Simultaneously to enrichment process, was verified the influence of micronutrients in nitrifying conditions in three chemostats, as follows: Q1 fed with medium containing micronutrients solution complete feeds without Q2 and Q3 micronutrients solution fed micronutrients solution without the element Boron (chemostat experiment). In the three conditions stability was achieved with 11 days of operation with average conversion of ammonia nitrogen of 99 \'+ OU -\' 1.5%, 94.6 \'+ OU -\' 6.3% and 93.3 \'+ OU -\' 7.3% for Q1, Q2 and Q3 respectively for 79 mg \'N\'-\'NH IND.4\'POT.+\'/L. After 450 days of operation of the RBS was found similarity of clones with Brocadia anammoxidans, Planctomycetes, Proteobacteria, Chlorobi, Nitrospira, Chloroflexi phyla and candidate phylum OP 11. The microbial composition found in the FBR with 139 days of operation (end of anammox phase) was 48% of clones related to B. anammoxidans, 4% related to uncultured Planctomycetes, Proteobacteria related to 12%, 8% related to Chlorobi, 24% related to Nitrospira, 4% related to the phylum Chloroflexi. It can be concluded that biomass adhered to LDPE selected anammox microorganisms and Nitrospira positively, and negatively to the filaments related to the Chloroflexi phylum.

A presente pesquisa teve por objetivo avaliar a produção biológica de hidrogênio em longo prazo, e os impactos da separação das principais etapas da digestão anaeróbia, acidogênese e metanogênese, sobre a eficiência do tratamento em reatores de leito fixo estruturado e sobre o desempenho da filtração em biorreatores com membrana. O efluente utilizado foi à base de sacarose e a temperatura foi mantida em 30ºC. Na primeira etapa experimental, avaliou-se a produção de H2 em três configurações de reatores: leito fixo estruturado (FB), UASB granular (UG) e UASB floculento (UF-1). Na segunda etapa experimental, um reator UASB acidogênico (UF-2) foi combinado a um reator metanogênico de leito fixo estruturado (RM). Um reator de estágio único de leito fixo estruturado (RU) foi operado em paralelo. Na última etapa experimental, foram avaliados dois biorreatores anaeróbios conjugados com módulos externos de membranas tubulares, nomeadamente 1-AnMBR, que foi alimentado com efluente bruto, e 2-AnMBR, que foi alimentado com efluente acidificado. Na primeira etapa, sob um TDH de 3,3 h (COV = 33 gDQO.L-1d-1), os reatores FB, UG e UF-1 apresentaram produção de H2 contínua, porém instável, com rendimentos de aprox. 1,5, 0,8 e 1,2 molH2.mol-1sacaroseconsumida, respectivamente. O reator UF-1 apresentou uma estabilidade relativamente melhor e, por isso, esta configuração foi utilizada nos experimentos seguintes. No reator UF-2, aumentou-se o TDH para 4,6 h (COV = 25 gDQO.L-1d-1), o que significativamente promoveu a melhoria do desempenho. Nenhum alcalinizante foi adicionado e o pH do efluente permaneceu em torno de apenas 2,7. Contudo, uma produção de H2 contínua, estável e por longa duração foi atingida, de 175 mLH2.L-1h-1 (= 4,2 LH2.L-1d-1), com rendimento de 3,4 molH2.mol-1sacaroseconsumida, concomitante com a produção de ácido acético e etanol. Nos reatores metanogênicos, o TDH aplicado foi gradativamente reduzido (53-18 h no RM e 56-23 h no RU). Após os sistemas atingirem estabilidade, os valores de DQO permaneceram inferiores no efluente do RM, sobretudo pela redução da concentração de SSV, equivalente a 92 mg.L-1, enquanto que no RU essa concentração foi de 244 mg.L-1. No final da operação, o rendimento energético do sistema de dois estágios foi de 20,69 kJ.g-1DQOadicionada, sendo 90% proveniente do CH4 e 10% do H2. Este rendimento foi 34% maior do que o obtido no reator de estágio único, que foi de 15,48 kJ.g-1DQOadicionada. Por fim, avaliando-se o desempenho da filtração nos biorreatores com membrana, verificou-se que a permeabilidade operacional foi, na maior parte do tempo, superior no 2-AnMBR. A pré-acidificação do efluente levou à redução de cerca de 56-59% na concentração de sólidos voláteis suspensos e totais no 2-AnMBR e à modificação no perfil do tamanho das partículas. No 1-AnMBR, porém, não havia partículas de pequenas dimensões, tais quais encontradas no reator acidogênico, indicando reduzido crescimento suspenso de bactérias acidogênicas. Embora os valores de fluxo crítico tenham sido muito semelhantes para ambos os AnMBR, testes de resistência específica da torta indicaram maior resistência do lodo do 1-AnMBR (1,02 x 1018 m-1), comparado ao lodo do 2-AnMBR (1,03 x 1012 m-1) e ao lodo acidogênico (7,44 x 1011 m-1). Portanto, essa pesquisa demonstrou, por meio da aplicação do tratamento anaeróbio em dois estágios, a viabilidade da produção contínua de hidrogênio em pH extremamente ácido e com mínimos requerimentos operacionais, a redução da concentração de sólidos suspensos no efluente de reatores de leito fixo estruturado, o potencial de aumento da recuperação de bioenergia e de redução da incrustação em membranas de ultrafiltração. / This study assessed long-term hydrogen production and the impacts of separating the main stages of anaerobic digestion (acidogenesis and methanogenesis) on treatment efficiency in structured fixed-bed reactors and on filtration performance in anaerobic membrane bioreactors. Sucrose based wastewater was used and the temperature was maintained at 30°C. In the first experimental phase, H2 production was evaluated in three different acidogenic reactors: structured fixed-bed (FB), granular UASB (UG) and flocculated UASB (UF-1). In the second experimental phase, an acidogenic UASB reactor (UF-2) was combined with a structured fixedbed methanogenic reactor (RM). A single-stage structured fixed-bed reactor (RU) was operated in parallel. In the last experimental phase, two sidestream anaerobic membrane bioreactors were evaluated: 1-AnMBR, which was fed with raw effluent; and, 2-AnMBR, which was fed with biologically acidified effluent. During the first operational phase, under an HRT of 3.3 h (OLR = 33 gCOD.L-1d-1), the FB, UG and UF-1 reactors showed continuous but unstable H2 production, with yields of approximately 1.5, 0.8 and 1.2 molH2.mol-1sucroseconsumed, respectively. The UF-1 reactor showed relatively better stability; therefore, this configuration was used in the next experiments. In the UF-2 reactor, the HRT was increased to 4.6 h (OLR = 25 gCOD.L-1d-1), which significantly improved the overall performance. No alkalizing agent was added, and effluent pH values remained around only 2.7. However, continuous, stable and long-term H2 production was achieved of 175 mLH2.L-1h-1 (= 4.2 LH2.L-1h-1), with yields of 3.4 molH2.mol-1sucroseconsumed, concomitant with acetic acid and ethanol production. In the methanogenic reactors, the HRT was gradually reduced and, when the systems reached stability, COD values remained lower in the RM effluent. This was mainly due to the reduction of VSS concentrations, equivalent to 92 mg.L-1, while in the RU this value was 244 mg.L-1. At the end of the operation, the energy yield of the two-stage system was 20.69 kJ.g-1CODadded with 90% coming from CH4 and 10% from H2. This yield was 34% greater than that obtained in the single-stage system, which was 15.48 kJ.g-1CODadded. Finally, regarding the filtration performance in the membrane bioreactors, the operational permeability was higher in the 2- AnMBR most of the time. The pre-acidification of the effluent led to the 56-59% reduction in the volatile total and suspended solid concentrations, and to modification in the particle size profile in the 2-AnMBR. Nevertheless, in the 1-AnMBR, there were no small particles such as were found in the sludge of the acidogenic reactor, indicating less suspended growth of acidogenic biomass. Although the critical flux values were very similar for both AnMBRs, a higher specific cake resistance was verified in the 1-AnMBR sludge (1.02 x 1018 m-1), as compared to the 2-AnMBR sludge (1.03 x 1012 m-1) and to the acidogenic sludge (7.44 x 1011m-1</sup). Therefore, this study demonstrated, through the application of two-stage anaerobic treatment, the viability of continuous hydrogen production in extreme acid pH and with minimum operating requirements, the reduction of solid concentrations in the effluent of structured fixed bed reactors, as well as the potential for increased bioenergy recovery and for fouling reduction of ultrafiltration membranes.

Un frein majeur au développement des énergies renouvelables à finalité électrogène réside dans l’inadéquation entre les moments de forte disponibilité des ressources, et les moments de forte demande de la part des consommateurs. Un élément de solution éventuel consisterait à utiliser l’énergie électrique excédentaire, en périodes de surproduction, pour produire du méthane de synthèse (power-to-gas). Cette approche présente l’avantage d’autoriser un lissage à l’échelle des saisons, car le méthane peut être stocké, transporté et utilisé facilement avec les systèmes existants. La réaction de méthanation CO_2+4.H_2⇄CH_4+2.H_2 O, étape clé de la chaine de power-to-gas, peut être réalisée dans un réacteur catalytique à lit fixe refroidi par la paroi. La conception d’un tel réacteur présente des difficultés d’ordre théorique et technologique. Du fait de la forte exothermicité de la réaction, cette dernière tend à être instable (emballement vs. extinction). De plus, la puissance électrique excédentaire varie au cours du temps : le régime de fonctionnement du réacteur (débit de mélange réactif à convertir) doit pouvoir varier en conséquence. L’exigence de fonctionnement dynamique, pour une réaction instable, fait apparaitre des difficultés spécifiques auxquelles ne sont pas confrontés les réacteurs fonctionnant en régime permanent (risque d’emballement transitoire). Dans ce contexte, un projet impliquant le Laboratorie de Thermique, Energétique et Procédés et la start-up industrielle ENOSIS a été mis en place pour contribuer au développement d’un réacteur performant et sûr. Ce projet bénéficie du financement de la région Nouvelle-Aquitaine.Dans la présente thèse, un critère théorique est introduit pour quantifier la marge de sécurité dont bénéficie un réacteur vis-à-vis des instabilités transitoires. Un logiciel est développé pour simuler, au premier ordre, le fonctionnement dynamique d’un réacteur. Cela permet d’illustrer l’optimisation d’un réacteur, en prenant en compte la contrainte de stabilité transitoire. Il est montré que l’utilisation d’un catalyseur dont la dilution est étagée, stratégie connue pour améliorer la sécurité et la performance des réacteurs en fonctionnement permanent, peut se réveler contre-productive en regard de critères transitoires de performance et/ou de sécurité. Une caractéristique clé du fonctionnement intermittent réside dans le temps de démarrage (ou de redémarrage à chaud) de la réaction, lors de l’injection soudaine de réactifs. Aussi, un examen de la durée de (re)démarrage d’un réacteur en fonction de sa température juste avant injection est mené. La relation entre température et vitesse de (re)démarrage se révèle approximativement affine. Dans un second temps, un modèle plus précis est développé et le logiciel correspondant est écrit, afin de distinguer le comportement thermique des grains catalytiques proprement-dits du comportement de grains inertes. Ces derniers, outre leur rôle de diluant, peuvent également présenter des propriétés thermiques dont l’exploitation autoriserait possiblement une stabilisation des transitoires critiques. Aussi, quelques simulations sont lancées sur des configurations de réacteur non-conventionnelles (grains inertes pouvant être chauffés par induction, grains à changement de phase). Les résultats obtenus permettent de mieux appréhender certaines difficultés qui seront à résoudre pour permettre l’utilisation éventuelle de ces technologies disruptives. En complément du travail théorique et numérique, une micro-campagne expérimentale a été menée au sein du Combustion and Catalysis Laboratory de New-York (mise en place d’un dispositif, collecte de premières données en vue d’une validation).En parallèle de ces différents axes de recherche, une solution technologique brevetable (non détaillée dans le présent manuscrit) a également été trouvée. / The development of renewable energy for electricity generation is significantly hindered by the discrepancy between the moments when high amounts of energy are available and the moments when consumers demand most power supply. A prospective solution consists in using electric power surplus to produce synthetic methane, during extra production periods (power-to-gas). This solution would enable to smoothen the electric balance from a season to another, since methane can be easily stored, transported and used in existing devices. The methanation reaction CO_2+4.H_2⇄CH_4+2.H_2 O is a key step in power-to-gas. It can be completed in a fixed-bed wall-cooled reactor. Designing such a reactor leads to theoretical and technological difficulties. Because the reaction is highly exothermic, it tends to be unstable (runaway vs. blow-out). Moreover, power surplus varies over time: the reactor must therefore enable dynamic operation (reactants flow rate variations). Dynamic completion of an unstable reaction leads to specific issues which do not exist for steady-state operating reactors (risk of a transient runaway). In this context, a project involving the Laboratoire de Thermique, Energétique et Procédés and the start-up company ENOSIS has been set up (with the financial support of French region Nouvelle-Aquitaine), to obtain a contribution to the development of a safe and efficient reactor. In the present work, a theoretical criterion is introduced to quantify the safety margin of a reactor towards transient instabilities. A software is developed to perform a simplified simulation of a reactor’s dynamic operation. This simulation tool is used to illustrate the process of optimizing a reactor, taking into account the transient stability constraint. It is shown that using a staggered catalyst dilution – a well known strategy to improve safety and efficiency for steady state operating reactors – can be counter-productive when it comes to transient safety/efficiency criteria. A key characteristic of intermittent operation lies in the start-up time (or warm restart-up time) of the reaction, when reactants are injected sharply. Therefore, we examined the (re)start-up time of a reactor as a function of its temperature just before injection begins. The temperature-(re)start time relation turns out to be nearly linear.Secondly, a more accurate model is developed and the corresponding software is encoded, with the aim of distinguishing the catalytic pellets from the inert pellets, in terms of thermal behavior. Not only do inert pellets play a diluting role, but they can also have specific thermal properties to stabilize critical transient sequences. A few simulations are thus performed on non-conventional reactor configurations (inert grains can be heated by induction, or undergo a phase change). The results provide a better understanding of some difficulties that should be solved before such disruptive technologies could eventually be operational.As a complement to the theoretical and numerical work, a micro experimental campaign is performed in the Combustion and Catalysis Laboratory of New-York (setting-up an experimental device, collecting data for future validation of the simulator).Alongside these lines of research, a patentable technological solution has also been found (not detailed in this manuscript).

Made available in DSpace on 2017-07-10T19:25:20Z (GMT). No. of bitstreams: 1 Cristiane.pdf: 2244710 bytes, checksum: 7f1fb544f09e13f94b271e1202243132 (MD5) Previous issue date: 2012-02-13 / In this study, it was evaluated the operational conditions, the organic matter, nitrogen and phosphorus removal efficiency and the hydrodynamic behavior of a continuously up-flow combined anaerobic-aerobic fixed bed reactor (RAALF), operated in bench-scale, filled with expanded clay and polyurethane foam cubic arrays as means of biomass immobilization support, in the treatment of raw effluent from a cattle slaughterhouse. Three different operational conditions were tested: Step I, characterized by the operation of RAALF in anaerobic condition; Step II, in combined condition (anaerobic-aerobic), and Step III, in combined condition with recirculation. In each operational step three different hydraulic retention times (14, 11 and 8 h) were tested. The hydrodynamics assays were determined using stimulus-response type pulse, with Eosina Y as a tracer to obtain the curves of residence time distribution (RTD). The results from the RAALF in the Step I, under anaerobic condition, indicated that operational conditions ensured the process of anaerobic digestion, with keeping of the pH and the RAALF s buffering, promoting a biochemical balance between acidogenic/acetogenic and methanogenic archaea. In this operational step, the HRT of 11 h showed better result, with removal efficiency of raw COD, filtered COD, TS, TSS and N-amon of 59, 60, 56, 76 and 16%, respectively. In Step II, the HRT of 14 h showed better results in terms of organic matter and solids removal efficiency, with 58, 66, 66 and 84% for raw COD, filtered COD, TS and TSS, respectively. The overall efficiency of nitrogen removal achieved in this study was 0, 17 and 7% at Step I; 37, 22 and 22% in Step II for the HRT 14, 11 and 8 h, respectively, and 50 and 29% for the HDT of 11 and 8 h in Step III. Therefore, there was an evolution in the overall nitrogen removal efficiency in Steps II and III when compared to Step I, due to the partial nitrification and denitrification. Denitrification has been compromised by factors such as liquid temperature, pH, and DQO/N-NO3- ratio. The efficiency of phosphorus removal was 0, 0 and 15% in Step I and 46, 0 and 0% in Step II for HRT 14, 11 and 8 h, respectively, and 10 and 0 % removal HRT to 11 and 8 h, respectively, in Step III. The ANOVA and Tukey tests indicated that the operational stages I, II and III were statistically different for all physical-chemical parameters evaluated, except for phosphorus, for which it can be stated that the efficiency of organic matter and nitrogen removal was affected by the operating condition. The hydrodynamic study conducted at RAALF indicated behavior tending to a complete mixing and deviations from ideality were found, such as dead zones, recirculation and long tail effect. The dispersion degrees were probably influenced by insertion of the aerobic phase, which improved the liquid mixture inside the reactor. The RAALF presented similar kinetic behavior in the operational steps I, II and III, represented by the first order model, with increase of k and vr parameters along the height of the anaerobic phase and decrease of the kinetic constant and degradation rate in the aerobic phase / Neste trabalho foram avaliadas as condições operacionais, a eficiência de remoção de matéria orgânica, nitrogênio e fósforo e o comportamento hidrodinâmico de um reator anaeróbio aeróbio de leito fixo (RAALF) e fluxo ascendente, vertical, operado de modo contínuo, em escala de bancada, preenchido com argila expandida e matrizes cúbicas de espuma de poliuretano como meio suporte para imobilização da biomassa, no tratamento de efluente bruto proveniente de um matadouro bovino. Foram testadas três condições operacionais distintas, sendo a Etapa I caracterizada pela operação do RAALF em condição anaeróbia, a Etapa II em condição combinada (anaeróbia-aeróbia) e a Etapa III em condição combinada com recirculação. Em cada etapa operacional foram testados três tempos de detenção hidráulicos diferentes (14, 11 e 8 h). O comportamento hidrodinâmico foi avaliado utilizando ensaios de estímulo-resposta, tipo pulso, com o uso de Eosina Y como traçador para obtenção das curvas de distribuição do tempo de residência (DTR). Os resultados da avaliação do RAALF na Etapa I, sob condição anaeróbia, indicaram que as condições operacionais garantiram o processo de digestão anaeróbia, com a manutenção do pH e tamponamento do sistema, promovendo um equilíbrio bioquímico entre microrganismos acidogênicos/acetogênicos e arqueas metanogênicas. Nesta etapa operacional, o TDH de 11 h apresentou melhores rendimentos, com eficiência de remoção de DQO bruta, DQO filtrada, ST, SST e N-amon de 59, 60, 56, 76 e 16%, respectivamente. Na Etapa II, o TDH de 14 horas apresentou melhores resultados em termos de eficiência de remoção de matéria orgânica e sólidos, com valores de 58, 66, 66 e 84% para DQO bruta, DQO filtrada, ST e SST, respectivamente. A eficiência global de remoção de nitrogênio alcançada neste estudo foi de 0, 17 e 7% na Etapa I, 37, 22 e 22% na Etapa II, para o TDH de 14, 11 e 8 h, respectivamente, e de 50 e 29% para o TDH de 11 e 8 h na Etapa III; portanto, verifica-se evolução da eficiência global na remoção de nitrogênio das Etapas II e III se comparada à Etapa I, decorrente do processo de nitrificação e desnitrificação parcial. A desnitrificação foi comprometida por fatores como temperatura do líquido, pH e relação DQO/N-NO3-. As eficiências de remoção de fósforo total foram de 0, 0 e 15% na Etapa I e de 46, 0 e 0% na Etapa II para os TDHs de 14, 11 e 8 h, respectivamente, e de 10 e 0% de remoção para o THD de 11 e 8 h, respectivamente, na Etapa III. O teste ANOVA e o teste Tukey indicaram que as etapas operacionais I, II e III foram estatisticamente diferentes entre si, para todos os parâmetros físico-químicos avaliados, com exceção do fósforo, podendo-se afirmar que a eficiência de remoção de matéria orgânica e nitrogenada foi afetada pela condição operacional. O estudo hidrodinâmico realizado no RAALF indicou comportamento tendendo ao de mistura completa e foram constatados desvios de idealidade, como zonas mortas, recirculações e efeito de cauda longa. Os graus de dispersão foram possivelmente influenciados pela inserção da fase aeróbia, que promoveu uma melhor mistura do líquido no interior do reator. O RAALF apresentou comportamento cinético similar nas etapas operacionais I, II e III, representado pelo modelo de primeira ordem, com aumento dos parâmetros k e vr ao longo da altura da fase anaeróbia, e diminuição da constante cinética e da velocidade de degradação na fase aeróbia

Made available in DSpace on 2017-05-12T14:48:43Z (GMT). No. of bitstreams: 1 Cristiane.pdf: 2244710 bytes, checksum: 7f1fb544f09e13f94b271e1202243132 (MD5) Previous issue date: 2012-02-13 / In this study, it was evaluated the operational conditions, the organic matter, nitrogen and phosphorus removal efficiency and the hydrodynamic behavior of a continuously up-flow combined anaerobic-aerobic fixed bed reactor (RAALF), operated in bench-scale, filled with expanded clay and polyurethane foam cubic arrays as means of biomass immobilization support, in the treatment of raw effluent from a cattle slaughterhouse. Three different operational conditions were tested: Step I, characterized by the operation of RAALF in anaerobic condition; Step II, in combined condition (anaerobic-aerobic), and Step III, in combined condition with recirculation. In each operational step three different hydraulic retention times (14, 11 and 8 h) were tested. The hydrodynamics assays were determined using stimulus-response type pulse, with Eosina Y as a tracer to obtain the curves of residence time distribution (RTD). The results from the RAALF in the Step I, under anaerobic condition, indicated that operational conditions ensured the process of anaerobic digestion, with keeping of the pH and the RAALF s buffering, promoting a biochemical balance between acidogenic/acetogenic and methanogenic archaea. In this operational step, the HRT of 11 h showed better result, with removal efficiency of raw COD, filtered COD, TS, TSS and N-amon of 59, 60, 56, 76 and 16%, respectively. In Step II, the HRT of 14 h showed better results in terms of organic matter and solids removal efficiency, with 58, 66, 66 and 84% for raw COD, filtered COD, TS and TSS, respectively. The overall efficiency of nitrogen removal achieved in this study was 0, 17 and 7% at Step I; 37, 22 and 22% in Step II for the HRT 14, 11 and 8 h, respectively, and 50 and 29% for the HDT of 11 and 8 h in Step III. Therefore, there was an evolution in the overall nitrogen removal efficiency in Steps II and III when compared to Step I, due to the partial nitrification and denitrification. Denitrification has been compromised by factors such as liquid temperature, pH, and DQO/N-NO3- ratio. The efficiency of phosphorus removal was 0, 0 and 15% in Step I and 46, 0 and 0% in Step II for HRT 14, 11 and 8 h, respectively, and 10 and 0 % removal HRT to 11 and 8 h, respectively, in Step III. The ANOVA and Tukey tests indicated that the operational stages I, II and III were statistically different for all physical-chemical parameters evaluated, except for phosphorus, for which it can be stated that the efficiency of organic matter and nitrogen removal was affected by the operating condition. The hydrodynamic study conducted at RAALF indicated behavior tending to a complete mixing and deviations from ideality were found, such as dead zones, recirculation and long tail effect. The dispersion degrees were probably influenced by insertion of the aerobic phase, which improved the liquid mixture inside the reactor. The RAALF presented similar kinetic behavior in the operational steps I, II and III, represented by the first order model, with increase of k and vr parameters along the height of the anaerobic phase and decrease of the kinetic constant and degradation rate in the aerobic phase / Neste trabalho foram avaliadas as condições operacionais, a eficiência de remoção de matéria orgânica, nitrogênio e fósforo e o comportamento hidrodinâmico de um reator anaeróbio aeróbio de leito fixo (RAALF) e fluxo ascendente, vertical, operado de modo contínuo, em escala de bancada, preenchido com argila expandida e matrizes cúbicas de espuma de poliuretano como meio suporte para imobilização da biomassa, no tratamento de efluente bruto proveniente de um matadouro bovino. Foram testadas três condições operacionais distintas, sendo a Etapa I caracterizada pela operação do RAALF em condição anaeróbia, a Etapa II em condição combinada (anaeróbia-aeróbia) e a Etapa III em condição combinada com recirculação. Em cada etapa operacional foram testados três tempos de detenção hidráulicos diferentes (14, 11 e 8 h). O comportamento hidrodinâmico foi avaliado utilizando ensaios de estímulo-resposta, tipo pulso, com o uso de Eosina Y como traçador para obtenção das curvas de distribuição do tempo de residência (DTR). Os resultados da avaliação do RAALF na Etapa I, sob condição anaeróbia, indicaram que as condições operacionais garantiram o processo de digestão anaeróbia, com a manutenção do pH e tamponamento do sistema, promovendo um equilíbrio bioquímico entre microrganismos acidogênicos/acetogênicos e arqueas metanogênicas. Nesta etapa operacional, o TDH de 11 h apresentou melhores rendimentos, com eficiência de remoção de DQO bruta, DQO filtrada, ST, SST e N-amon de 59, 60, 56, 76 e 16%, respectivamente. Na Etapa II, o TDH de 14 horas apresentou melhores resultados em termos de eficiência de remoção de matéria orgânica e sólidos, com valores de 58, 66, 66 e 84% para DQO bruta, DQO filtrada, ST e SST, respectivamente. A eficiência global de remoção de nitrogênio alcançada neste estudo foi de 0, 17 e 7% na Etapa I, 37, 22 e 22% na Etapa II, para o TDH de 14, 11 e 8 h, respectivamente, e de 50 e 29% para o TDH de 11 e 8 h na Etapa III; portanto, verifica-se evolução da eficiência global na remoção de nitrogênio das Etapas II e III se comparada à Etapa I, decorrente do processo de nitrificação e desnitrificação parcial. A desnitrificação foi comprometida por fatores como temperatura do líquido, pH e relação DQO/N-NO3-. As eficiências de remoção de fósforo total foram de 0, 0 e 15% na Etapa I e de 46, 0 e 0% na Etapa II para os TDHs de 14, 11 e 8 h, respectivamente, e de 10 e 0% de remoção para o THD de 11 e 8 h, respectivamente, na Etapa III. O teste ANOVA e o teste Tukey indicaram que as etapas operacionais I, II e III foram estatisticamente diferentes entre si, para todos os parâmetros físico-químicos avaliados, com exceção do fósforo, podendo-se afirmar que a eficiência de remoção de matéria orgânica e nitrogenada foi afetada pela condição operacional. O estudo hidrodinâmico realizado no RAALF indicou comportamento tendendo ao de mistura completa e foram constatados desvios de idealidade, como zonas mortas, recirculações e efeito de cauda longa. Os graus de dispersão foram possivelmente influenciados pela inserção da fase aeróbia, que promoveu uma melhor mistura do líquido no interior do reator. O RAALF apresentou comportamento cinético similar nas etapas operacionais I, II e III, representado pelo modelo de primeira ordem, com aumento dos parâmetros k e vr ao longo da altura da fase anaeróbia, e diminuição da constante cinética e da velocidade de degradação na fase aeróbia

Ce travail est consacré à la modélisation, simulation et optimisation des réacteurs catalytiques gaz/solide à lit fixe multitubulaire pour la production de l'acroléine à partir du propylène ou du glycérol. La première partie du travail traite de l'oxydation catalytique du propylène en acroléine. Différents modèles cinétiques et du réacteur ont été développés. Les paramètres inconnus mis en jeu sont identifiés à partir des mesures expérimentales. Un ensemble de variables opératoires qui maximisent les rendements des produits clés ont ensuite été déterminés en utilisant le modèle validé. La seconde partie du travail concerne la production d'acroléine à partir du glycérol. Elle comprend une étape de déshydratation du glycérol et une étape de régénération du catalyseur. Un modèle hétérogène bidimensionnel a été développé. Pour la régénération du catalyseur, un modèle cinétique qui permet d'identifier la concentration et les compositions initiales du coke et de prédire le processus de sa combustion a été développé et identifié à l'aide de mesures expérimentales. L'optimisation de l'étape de régénération du catalyseur a ensuite été effectuée. Pour l'étape de déshydratation, un modèle cinétique qui permet de simuler simultanément la déshydratation du glycérol, la formation du coke et la variation de l'activité du catalyseur a été développé et identifié à l'aide de mesures expérimentales. / In this work, modeling, simulation and optimization of multitubular gas/solid fixed bed catalytic reactors for acrolein production from propylene or from glycerol are investigated. The first part of the work deals with the catalytic oxidation of propylene to acrolein. Different kinetic and reactor models are developed and the unknown parameters involved are identified from experimental measurements. A set of operating variables that maximize the yield of key products then determined using the validated reactor model. The second part of the work is devoted to the production of acrolein from glycerol. This part consists of two steps: a glycerol dehydration step and a catalyst regeneration step. A two-dimensional heterogeneous model is developed. In the catalyst regeneration step, a kinetic model enabling the identification of the concentration and initial compositions of the coke and the prediction of its combustion process is developed and identified using experimental measurements. The optimization of the operating conditions of the regeneration step is then carried out. In the dehydration step, a kinetic model that allows the simultaneous simulation of glycerol dehydration, coke formation and catalyst activity variation is developed and identified by means of experimental measurements.

Made available in DSpace on 2016-06-02T19:56:42Z (GMT). No. of bitstreams: 1 3506.pdf: 2271432 bytes, checksum: fc1d05123fb3be32395a9e84b2da5ad8 (MD5) Previous issue date: 2011-02-25 / Universidade Federal de Sao Carlos / This work investigated numerical methods in the solution of mathematical models of fixed-bed reactors. For the reactors modeling and simulation, two numerical methods were used: sequencing method (SM) and finite volume method (FVM). There were also proposed two mathematical models: the pseudo-homogeneous model and the dimensionless one, which is based on the Peclet (Pe) and Biot (Bi) numbers. A horizontal-flow anaerobic immobilized sludge (HAIS) reactor developed in bench scale and after a scale-up, reducing the COD in the wastewater treatment was simulated by sequencing method, varying the numbers of mesh; a tubular fixed-bed reactor with biomass immobilized for the startup period of lactic acid fermentation, also simulated by sequencing method and compared with experimental data; and was also evaluated the precision of sequencing and finite volume methods over the reactor s profile, varying the Peclet e Biot numbers. The models development was based on studies about hydrodynamics and biochemistry kinetics. Both methods described satisfactorily the behavior of the reactors in the performed simulations, but in high values of Peclet, the finite volume method generated inadequacies such as oscillatory responses and over the limit. This paper is an elucidation to sequencing method, which besides its huge range and simplicity, still is not so studied neither known, because it s a recent method. / Este trabalho investigou metodos numericos na solucao de modelos matematicos para reatores de leito fixo. Para a modelagem e simulacao dos reatores, foram utilizados dois metodos numericos: metodo da sequencia (SM) e metodo dos volumes finitos (FVM). Foram propostos dois modelos matematicos: o pseudo-homogeneo e o adimensional, sendo este ultimo baseado nos numeros de Peclet (Pe) e Biot (Bi). Um reator anaerobio horizontal de leito fixo (RAHLF) desenvolvido inicialmente em escala de bancada e posterior aumento de escala na reducao da DQO de aguas residuarias foi simulado pelo metodo da sequencia, variando-se o numero de malhas; um reator tubular de leito fixo com biomassa anaerobia imobilizada no periodo da partida da fermentacao de acido latico, tambem simulado pelo metodo da sequencia e comparado com dados experimentais; e avaliou-se a precisao dos metodos da sequencia e dos volumes finitos sobre o perfil da concentracao de um reator, variando-se os valores de Peclet e Biot. O desenvolvimento dos modelos foi baseado em estudos sobre caracteristicas hidrodinamicas do sistema e de cinetica bioquimica. Ambos os metodos descreveram satisfatoriamente o comportamento dos reatores nas simulacoes realizadas, porem em valores elevados de Peclet, o metodo dos volumes finitos gerou inadequacoes como respostas oscilatorias e superiores ao limite. Este trabalho foi uma elucidacao ao metodo da sequencia, que apesar da sua grande abrangencia e simplicidade, por ser um metodo recente, ainda e pouco estudado e conhecido.