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Die Rolle oxidativer Pilzenzyme für die Totholzzersetzung und die Zersetzungsdynamik von Fagus sylvatica, Picea abies und Pinus sylvestrisArnstadt, Tobias 05 May 2017 (has links)
In Waldökosystemen ist Totholz von zentraler Bedeutung, indem es zahlreichen Organismen einen Lebensraum bietet oder als Substrat dient, Bestandteil des Kohlenstoff- und Nährstoffkreislaufs ist sowie als ein wichtiges strukturelles Element fungiert. Für seine Zersetzung ist die Überwindung der Ligninbarriere von besonderer Bedeutung. Dazu sind lediglich saprobionte Pilze aus den Phyla der Basidiomycota und Ascomycota in der Lage, die verschiedene Strategien – die Fäuletypen – entwickelt haben, um Lignin abzubauen oder zu modifizieren und somit Zugang zu den vom Lignin inkrustierten Polysachariden (Zellulose und Hemizellulosen) zu erhalten. Eine besondere Rolle spielen dabei Weißfäulepilze, die mit ihren extrazellulären oxidativen Enzymen, wie Laccasen und verschiedenen Peroxidasen, Lignin komplett bis zum Kohlendioxid (CO2) mineralisieren. Trotz der Bedeutung des Ligninabbaus für die Totholzzersetzung sind extrazelluläre oxidative Enzyme im natürlichen Totholz kaum erforscht.
Ziel dieser Arbeit war es, die Rolle der oxidativen Enzyme für die Totholzzersetzung unter Realbedingungen zu verifizieren, ihre räumlichen und zeitlichen Muster zu beschreiben und ihre Abhängigkeiten von verschiedenen Totholzvariablen sowie der pilzlichen Artengemeinschaft in und auf Totholz zu ermitteln. Weiter wurde die Veränderung der Totholzvariablen über den Zersetzungsprozess für unterschiedliche Baumarten vergleichend beschrieben und der Einfluss der Waldbewirtschaftung auf den Prozess untersucht.
Dazu wurden 197 natürliche Totholzstämme (coarse woody debris, CWD) von Fagus sylvatica (Rotbuche), Picea abies (Gemeine Fichte) und Pinus sylvestris (Gemeine Kiefer) in unterschiedlich stark bewirtschafteten Wäldern in Deutschland untersucht. Insgesamt wurden 735 Proben genommen und darin die Aktivität von Laccase (Lacc), Genereller Peroxidase (GenP) und Mangan-Peroxidase (MnP) gemessen. Weiterhin wurden Variablen wie Dichte, Wassergehalt, pH-Wert, wasserlösliche Ligninfragmente, die Gehalte an Lignin und Extraktiven sowie an Nährstoffen und Metallen (N, Al, Ca, Cu, K, Mg, Mn und Zn) ermittelt. Die pilzliche Artengemeinschaft wurde anhand genetischer Fingerprints (F-ARISA) und mittels Fruchtkörperkartierung erfasst.
In 79 % der untersuchten Totholzproben wurden oxidative Enzymaktivitäten festgestellt. Sie waren hoch variabel über den Zersetzungsverlauf sowie in Bezug auf die Probenahmepositionen innerhalb der einzelnen Stämme. Generell waren die Aktivitäten im F.-sylvatica-Totholz höher als im Koniferentotholz. Lineare und logistische Modelle zeigten, dass die pilzliche Artengemeinschaft, gefollgt von den wasserlöslichen Ligninfragmenten, die wichtigste Einflussgröße hinsichtlich der oxidativen Enzyme war. Ein saurer pH-Wert unterstützte die Funktion von Lacc und MnP; Mangan, Eisen und Kupfer waren in ausreichenden Konzentrationen vorhanden, um die Funktion und Bildung der Enzyme zu gewährleisten. Die holzabbauenden Pilze erwiesen sich als optimal an das niedrige Stickstoffangebot im Totholz angepasst, sodass ein erhöhter Stickstoffeintrag über zwei Jahre die oxidativen Enzymaktivitäten nicht weiter beeinflusste.
Der pH-Wert sowie die Gehalte an Lignin, Extraktiven und Nährstoffen waren im Vergleich der drei Baumarten signifikant verschieden, obwohl die zeitlichen Veränderungen der Variablen über den Zersetzungsprozess vergleichbar waren. Die Anzahl operativer taxonomischer Einheiten (OTUs ~ molekulare Artenzahl) nahm im Verlauf der Holzzersetzung zu, während die Zahl fruktifizierender Arten für mittlere Zersetzungsgrade am höchsten war. Beide Artenzahlen nahmen zusammen mit dem Stammvolumen zu. Die Weißfäulepilze dominierten über den gesamten Zersetzungsprozess die fruchtkörperbasierte Artenzahl aller drei Baumarten, was mit dem Vorhandensein oxidativer Enzymaktivitäten einhergeht. Generell nahmen der massebezogene Gehalt des Lignins, der Extraktive und der Nährstoffe über die Zersetzung zu, während der volumenbezogene Gehalt abnahm. Der pH-Wert im Holz aller drei Baumarten sank kontinuierlich im Verlauf der Zersetzung. Eine Erhöhung der Waldbewirtschaftungsintensität hatte einen negativen Effekt auf das Stammvolumen und darüber vermittelt auf die Zahl fruktifizierender Pilzarten, jedoch kaum auf andere untersuchte Totholzvariablen.
Aufgrund des häufigen Vorkommens von Weißfäulepilzen, der gleichzeitigen Präsenz oxidativer Enzymaktivitäten und des substanziellen Ligninabbaus kann auf eine fundamentale Bedeutung von Laccasen und Peroxidasen für die Zersetzung des Totholzes geschlossen werden. Nicht zuletzt die charakteristische Molekularmassenverteilung der wasserlöslichen Ligninfragmente deutete darauf hin, dass die Mn-oxidierenden Peroxidasen (MnPs) die dominierenden oxidativen Enzyme des Ligninabbaus sind. Das hoch variable Muster der oxidativen Enzymaktivitäten ist jedoch das Resultat eines komplexen Zusammenspiels der Holzeigenschaften und der pilzlichen Artengemeinschaft. Die dabei bestehenden funktionellen Abhängigkeiten müssen weiter im Detail in zukünftigen Studien analysiert und aufgeklärt werden.:Zusammenfassung I
Abstract III
Inhaltsverzeichnis V
Abkürzungsverzeichnis VIII
1 Einleitung 1
1.1 Totholz als Bestandteil von Waldökosystemen 1
1.1.1 Vorkommen von Totholz 1
1.1.2 Klassifizierung von Totholz 1
1.1.3 Entstehung von Totholz 2
1.1.4 Totholz und Biodiversität 3
1.1.5 Totholz in Stoffkreisläufen 8
1.1.6 Totholz als wichtiges Strukturelement 9
1.2 Holzaufbau 10
1.2.1 Grundsätzlicher Aufbau von Holz 10
1.2.2 Der Lignozellulose-Komplex 14
1.3 Saprobionte Pilze als Spezialisten zur Überwindung der Ligninbarriere 18
1.3.1 Weißfäulepilze 18
1.3.2 Braunfäulepilze 20
1.3.3 Moderfäulepilze 22
1.4 Enzymatischer Ligninabbau 23
1.4.1 Laccase 23
1.4.2 Peroxidasen 26
1.5 Totholz - Stand der Forschung 33
1.5.1 Totholzabbau in Europa 33
1.5.2 Totholz und Waldbewirtschaftung 34
1.5.3 Abbauprozesse 34
1.5.4 Oxidative Enzyme im Totholz 36
2 Zielstellung der Arbeit 39
3 Methoden 43
3.1 Untersuchung von natürlichem Totholz auf den VIP-Flächen 43
3.1.1 Untersuchungsgebiet 43
3.1.2 Probenahme 47
3.1.3 Aufbereitung der Proben für die enzymatischen Messungen 49
3.1.4 Aktivitäten oxidativer Enzyme 50
3.1.5 Physikochemische Variablen der Totholzproben 52
3.1.6 Artenzusammensetzung der Pilze auf und im Totholz 54
3.1.7 Statistik 56
3.2 Erfassung der kleinräumigen Verteilung von Oxidoreduktasen in einem Totholzfragment 63
3.2.1 Probenahme 63
3.2.2 Untersuchung der Proben 65
3.2.3 Statistische Auswertung 66
3.3 Stickstoffexperiment 66
3.3.1 Experimentaufbau 66
3.3.2 Probenahme 68
3.3.3 Aufbereitung der Proben für die enzymatischen Messungen 69
3.3.4 Enzymatische Untersuchungen 69
3.3.5 Untersuchung mit markiertem Stickstoff 74
3.3.6 Statistische Analyse 74
3.4 Optimierung der organischen Extraktion in Vorbereitung der Ligninbestimmung 75
3.4.1 Methodisches Vorgehen 76
3.4.2 Ergebnisse zur Methodenentwicklung 78
3.4.3 Bewertung der Methodenentwicklung 80
4 Ergebnisse 83
4.1 Natürliches Totholz auf den VIP-Flächen 83
4.1.1 Totholzvariablen und Ihre Unterschiede zwischen den Baumarten 83
4.1.2 Einfluss der Waldbewirtschaftung auf die Variablen des Totholzabbaus 91
4.1.3 Veränderungen des Totholzes während der Zersetzung 92
4.1.4 Abhängigkeit der oxidativen Enzymaktivitäten von den physikochemischen Eigenschaften und den Pilzarten (OTUs) 99
4.1.5 Kleinräumige Verteilungsmuster der oxidativen Enzymaktivitäten in den Totholzstämmen 105
4.2 Kleinräumige Muster der oxidativen Enzymaktivitäten in einem einzelnen Totholzfragment 106
4.3 Stickstoffexperiment 111
5 Diskussion 115
5.1 Unterschiede im Zersetzungsprozess zwischen den Baumarten 115
5.2 Oxidative Enzymaktivitäten im Totholz 119
5.2.1 Bedeutung von Lacc, GenP und MnP für die Ligninmodifikation 119
5.2.2 Variabilität der Lacc-, GenP- und MnP-Aktivitäten 121
5.2.3 Kleinräumige Muster der Lacc-, GenP und MnP-Aktivitäten 122
5.2.4 Dynamik der oxidativen Enzymaktivitäten im Verlauf des Zersetzungsprozesses 123
5.2.5 Zusammenhänge zwischen den oxidativen Enzymaktivitäten und den Totholzvariablen 125
5.3 Veränderung des Totholzes über den Zersetzungsprozess 135
5.3.1 Die Artengemeinschaft 136
5.3.2 Die Holzbestandteile und der pH-Wert 138
5.3.3 Die Nährstoffe 139
5.4 Einfluss der Waldbewirtschaftung auf Variablen des Totholzabbaus 141
6 Ausblick 145
7 Thesen 151
8 Literaturverzeichnis 153
Anhang 169
A Charakteristik der Untersuchungsflächen 169
B NMDS-Ordination der pilzlichen Artengemeinschaft 172
C Daten der Totholzstämme 175
D Daten zu den Proben 177
E Daten zur Modellierung der Enzymaktivitäten und der Wahrscheinlichkeit, diese zu detektieren 178
F Daten zur Untersuchung des einzelnen F.-sylvatica-Totholzfragments 189
G Detailabbildungen zur Zersetzungsdynamik 192
H Semivariogrammdaten oxidativer Enzyme im Totholz der VIP-Flächen 195
I Km-Werte von Mangan-Peroxidasen (MnP) für Mangan(II)-Ionen (Mn2+) aus der Literatur 196
J Zuordnung der Fäuletypen zu den Pilzarten 198
K Publikationen 208
L Danksagung 251
M Rechtliche Erklärung 253 / In forest ecosystems, deadwood is an important component that provides habitat and substrate for numerous organisms, contributes to the carbon and nutrient cycle as well as serves as a structural element. Overcoming the lignin barrier is a key process in deadwood degradation. Only specialized saprotrophic fungi of the phyla Basidiomycota and Ascomycota developed different strategies – the rot types – to degrade lignin or to modify it in way, which allows them to get access to the polysaccharides (cellulose and hemicelluloses) that are incrusted within the lignocellulosic complex. In this context, basidiomycetous white rot fungi secreting oxidative enzymes (especially laccases and peroxidases) are of particular importance, since they are the only organisms that are able to substantially mineralize lignin to carbon dioxide (CO2). Although lignin degradation is such an important process for deadwood degradation, oxidative enzyme activities have been only poorly studied under natural conditions in deadwood.
The aim of this work was to verify the importance of oxidative enzymes for deadwood degradation in the field, to describe their temporal and spatial patterns of occurrence and to identify dependencies from deadwood variables as well as from the fungal community within and on deadwood. Furthermore, the changes of different deadwood variables were studied over the whole period of degradation and compared among three tree species. Last but not least, the influence of forest management intensity on the process of deadwood degradation was evaluated.
Therefor, 197 logs of naturally occurring deadwood (coarse woody debris, CWD) of Fagus sylvatica (European beech), Picea abies (Norway spruce) and Pinus sylvestris (Scots pine) were monitored and sampled in forests with different management regimes across three regions in Germany. A total of 735 samples were taken from the logs and analyzed regarding activities of laccase (Lacc), general peroxidase (GenP) and manganese peroxidase (MnP). Wood density, water content, content of lignin and extractives as well as of nutrients and metals (N, Al, Ca, Cu, K, Mg, Mn und Zn) were determined in the samples, too. The fungal community was assessed based on sporocarps (fruiting bodies) and molecular fingerprints (F-ARISA).
Oxidative enzyme activities were present in 79 % of all samples. The activities were found to be highly variable both regarding the time course of degradation and their distribution within the logs. Activities were generally higher in wood samples of F. sylvatica than in samples of conifers. Linear and logistic models revealed that the fungal community structure was the most important determinant for oxidative enzyme activities in the samples, followed by the amount of water-soluble lignin fragments. Moreover, the prevalent acidic pH determined in deadwood was suitable to facilitate the function of laccase and peroxidases. Concentrations of metals (manganese, copper, iron) were sufficient to ensure synthesis and functioning of the enzymes. Deadwood-dwelling fungi turned out to be well adapted to low nitrogen concentrations and thus, an elevated nitrogen deposition over a period of two years did not affect the oxidative enzyme activities.
The pH as well as the content of lignin, extractives and nutrients significantly differed among the tree species; however, their trend over the course of degradation was rather similar. Molecular species richness (determined by F-ARISA as OTUs) increased over the whole course of degradation, while the number of fruiting species was highest in the intermediate stage of degradation. Both types of species richness increased with increasing volume of the CWD logs. Over the entire degradation period, white rot fungi – based on the identification of sporocarps – were the most abundant group of wood rot fungi in and on all three tree species. This corresponds well with the overall presence of oxidative enzyme activities. During degradation, the mass-related content of lignin, extractives and nutrients frequently increased, although the volume-related content decreased. The pH of all three tree species decreased in deadwood over the whole period of degradation. Higher forest management intensity had a negative effect on the log volume of deadwood and in consequence on fungal species richness (fruiting bodies), but hardly to other analyzed variables.
Based on the widespread occurrence of white rot fungi, the concomitant presence of oxidative enzyme activities as well as the substantial loss of lignin, it can be concluded that laccases and peroxidases are highly relevant for deadwood decomposition. Not least, the detected characteristic molecular size distribution of water-soluble lignin fragments points to a key role of Mn oxidizing peroxidases (MnPs) in enzymatic lignin degradation. The variable patterns of oxidative enzymes observed in wood samples is therefore the result of a complex array of wood variables and the fungal community structure, which will have to be resolved in more detail in future studies.:Zusammenfassung I
Abstract III
Inhaltsverzeichnis V
Abkürzungsverzeichnis VIII
1 Einleitung 1
1.1 Totholz als Bestandteil von Waldökosystemen 1
1.1.1 Vorkommen von Totholz 1
1.1.2 Klassifizierung von Totholz 1
1.1.3 Entstehung von Totholz 2
1.1.4 Totholz und Biodiversität 3
1.1.5 Totholz in Stoffkreisläufen 8
1.1.6 Totholz als wichtiges Strukturelement 9
1.2 Holzaufbau 10
1.2.1 Grundsätzlicher Aufbau von Holz 10
1.2.2 Der Lignozellulose-Komplex 14
1.3 Saprobionte Pilze als Spezialisten zur Überwindung der Ligninbarriere 18
1.3.1 Weißfäulepilze 18
1.3.2 Braunfäulepilze 20
1.3.3 Moderfäulepilze 22
1.4 Enzymatischer Ligninabbau 23
1.4.1 Laccase 23
1.4.2 Peroxidasen 26
1.5 Totholz - Stand der Forschung 33
1.5.1 Totholzabbau in Europa 33
1.5.2 Totholz und Waldbewirtschaftung 34
1.5.3 Abbauprozesse 34
1.5.4 Oxidative Enzyme im Totholz 36
2 Zielstellung der Arbeit 39
3 Methoden 43
3.1 Untersuchung von natürlichem Totholz auf den VIP-Flächen 43
3.1.1 Untersuchungsgebiet 43
3.1.2 Probenahme 47
3.1.3 Aufbereitung der Proben für die enzymatischen Messungen 49
3.1.4 Aktivitäten oxidativer Enzyme 50
3.1.5 Physikochemische Variablen der Totholzproben 52
3.1.6 Artenzusammensetzung der Pilze auf und im Totholz 54
3.1.7 Statistik 56
3.2 Erfassung der kleinräumigen Verteilung von Oxidoreduktasen in einem Totholzfragment 63
3.2.1 Probenahme 63
3.2.2 Untersuchung der Proben 65
3.2.3 Statistische Auswertung 66
3.3 Stickstoffexperiment 66
3.3.1 Experimentaufbau 66
3.3.2 Probenahme 68
3.3.3 Aufbereitung der Proben für die enzymatischen Messungen 69
3.3.4 Enzymatische Untersuchungen 69
3.3.5 Untersuchung mit markiertem Stickstoff 74
3.3.6 Statistische Analyse 74
3.4 Optimierung der organischen Extraktion in Vorbereitung der Ligninbestimmung 75
3.4.1 Methodisches Vorgehen 76
3.4.2 Ergebnisse zur Methodenentwicklung 78
3.4.3 Bewertung der Methodenentwicklung 80
4 Ergebnisse 83
4.1 Natürliches Totholz auf den VIP-Flächen 83
4.1.1 Totholzvariablen und Ihre Unterschiede zwischen den Baumarten 83
4.1.2 Einfluss der Waldbewirtschaftung auf die Variablen des Totholzabbaus 91
4.1.3 Veränderungen des Totholzes während der Zersetzung 92
4.1.4 Abhängigkeit der oxidativen Enzymaktivitäten von den physikochemischen Eigenschaften und den Pilzarten (OTUs) 99
4.1.5 Kleinräumige Verteilungsmuster der oxidativen Enzymaktivitäten in den Totholzstämmen 105
4.2 Kleinräumige Muster der oxidativen Enzymaktivitäten in einem einzelnen Totholzfragment 106
4.3 Stickstoffexperiment 111
5 Diskussion 115
5.1 Unterschiede im Zersetzungsprozess zwischen den Baumarten 115
5.2 Oxidative Enzymaktivitäten im Totholz 119
5.2.1 Bedeutung von Lacc, GenP und MnP für die Ligninmodifikation 119
5.2.2 Variabilität der Lacc-, GenP- und MnP-Aktivitäten 121
5.2.3 Kleinräumige Muster der Lacc-, GenP und MnP-Aktivitäten 122
5.2.4 Dynamik der oxidativen Enzymaktivitäten im Verlauf des Zersetzungsprozesses 123
5.2.5 Zusammenhänge zwischen den oxidativen Enzymaktivitäten und den Totholzvariablen 125
5.3 Veränderung des Totholzes über den Zersetzungsprozess 135
5.3.1 Die Artengemeinschaft 136
5.3.2 Die Holzbestandteile und der pH-Wert 138
5.3.3 Die Nährstoffe 139
5.4 Einfluss der Waldbewirtschaftung auf Variablen des Totholzabbaus 141
6 Ausblick 145
7 Thesen 151
8 Literaturverzeichnis 153
Anhang 169
A Charakteristik der Untersuchungsflächen 169
B NMDS-Ordination der pilzlichen Artengemeinschaft 172
C Daten der Totholzstämme 175
D Daten zu den Proben 177
E Daten zur Modellierung der Enzymaktivitäten und der Wahrscheinlichkeit, diese zu detektieren 178
F Daten zur Untersuchung des einzelnen F.-sylvatica-Totholzfragments 189
G Detailabbildungen zur Zersetzungsdynamik 192
H Semivariogrammdaten oxidativer Enzyme im Totholz der VIP-Flächen 195
I Km-Werte von Mangan-Peroxidasen (MnP) für Mangan(II)-Ionen (Mn2+) aus der Literatur 196
J Zuordnung der Fäuletypen zu den Pilzarten 198
K Publikationen 208
L Danksagung 251
M Rechtliche Erklärung 253
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Investigation of trace components in autothermal gas reforming processesMuritala, Ibrahim Kolawole 07 April 2017 (has links)
Trace component analysis in gasification processes are important part of elemental component balances in order to understand the fate of these participating compounds in the feedstock. Residual traces in the raw synthesis gas after quench could bring about the poisoning of catalysts and corrosion effects on plant facilities. The objective of this work is to investigate the effects of quenching operation on the trace components during test campaigns of the autothermal non-catalytic reforming of natural gas (Gas-POX) mode in the HP POX (high pressure partial oxidation) test plant. In order to achieve this, Aspen Plus simulation model of the quench chamber of the HP POX test plant was developed to re-calculate the quench chamber input amount of different trace compounds from their output amount measured during test points of the Gas-POX campaigns.
Variation in quench water temperatures from 130 °C to 220 °C and pH value of quench water as well as the resulting variation in Henry´s and Dissociation constant of the traces (CO2, H2S, NH3 and HCN) changed the distribution of traces calculated in the quench water. The formation of traces of organic acid (formic acid and acetic acid) and traces of BTEX, PAHs and soot in the quench water effluent were discussed. The discrepancies between equilibrium constant and reaction quotient (non-equilibrium or real) for the formation of NH3 and HCN at the exit of the gasifier were discussed. The assessment of the results in this work should lead to the improvement in the understanding of trace components and concepts that could be employed to influence their formation and reduction.:List of Figures vii
List of Tables xii
List of Abbreviations and Symbols xiii
1 Introduction 1
1.1 Background 1
1.2 Objective of the Work 4
1.3 Overview of the Work 5
2 Process and test conditions 6
2.1 HP POX test plant 6
2.2 Test campaign procedure 8
2.2.1 Gas-POX operating parameter range 8
2.2.2 Gas-POX experiments 9
2.2.3 Net reactions of partial oxidation 9
2.3 Gaseous feedstock characterization 11
2.3.1 Natural gas feedstock composition 11
2.4 Analytical methods for gaseous products 12
2.4.1 Hot gas sampling 12
2.4.2 Raw synthesis gas analysis after quench 13
2.5 Aqueous phase product analysis 14
2.5.1 Molecularly dissolved trace compounds and their ions trace analysis 14
2.5.2 Other trace analysis 15
2.6 Limit of accuracy in measurement systems 15
2.7 Summary 17
3 Simulation and methods 18
3.1 Test points calculation of the HP POX test campaign 18
3.1.1 Aspen Plus model for HP POX quench water system 19
3.2 Gas-POX 201 VP1 quench water system model simulation by Aspen Plus 23
3.2.1 Measured and calculated input parameters 23
3.2.2 Calculated sensitivity studies of species and their distribution for test point (VP1) 24
3.3 Used calculation tools related to the work 25
3.3.1 VBA in Excel 25
3.3.2 Python as interface between Aspen Plus and Microsoft Excel 26
3.3.3 Aspen Simulation Workbook 27
3.4 Summary 29
4 Trace components in quench water system 30
4.1 Physico-chemical parameters of quench water 31
4.1.1 Quench water pH adjustment 32
4.1.2 Henry constant 34
4.1.3 Dissociation constant 35
4.1.4 Organic acids in quench water 38
4.2 Carbon dioxide (CO2) 39
4.2.1 Results of sensitivity study: quench water temperature variation effects on CO2 41
4.2.2 Results of sensitivity study: quench water pH variation influence on CO2 42
4.3 Nitrogen compounds 43
4.3.1 Ammonia (NH3) 44
4.3.2 Results of sensitivity study: quench water temperature variation effects on NH3 46
4.3.3 Results of sensitivity study: quench water pH variation influence on NH3 47
4.3.4 Hydrogen Cyanide (HCN) 48
4.3.5 Results of sensitivity study: quench water temperature variation effects on HCN 50
4.3.6 Results of sensitivity study: quench water pH variation influence on HCN 50
4.4 Sulphur compounds: H2S 51
4.4.1 Results of sensitivity study: quench water temperature variation effects on H2S 53
4.4.2 Results of sensitivity study: quench water pH variation influence on H2S 54
4.5 Summary 55
5 Organic acids trace studies in quench water 57
5.1 Organic acids interaction with ammonia compounds in the quench water 57
5.2 Formic acid 62
5.2.1 Trace of formic acid in quench water 64
5.3 Acetic acid 67
5.3.1 Trace of acetic acid in quench water 69
5.4 Summary 72
6 Temperature approach studies for NH3 and HCN formation in gasifier 74
6.1 Nitrogen compounds: NH3 and HCN 74
6.2 Ammonia (NH3) formation in the gasifer 77
6.3 Hydrogen cyanide (HCN) formation in the gasifier 79
6.4 Discrepancies between back-calculated reaction quotients and equilibrium constants of the NH3 formation 81
6.4.1 Case 1: calculated equilibrium distribution between N2, NH3 and HCN 81
6.4.2 Case 2: calculated equilibrium distribution between NH3 and HCN 83
6.5 Summary 84
7 Traces of BTEX, PAHs and soot in quench water 86
7.1 Quench water behaviour 87
7.2 BTEX compounds 88
7.2.1 BTEX in quench water effluent 90
7.3 PAH compounds 93
7.3.1 PAHs in quench water effluent 95
7.4 Soot formation 99
7.4.1 Soots in quench water effluent 101
7.5 Summary 102
8 Summary and outlook 103
Bibliography 106
9 Appendix 135
List of Figures
Figure 2.1: HP POX test plant main facility components and material flow courtesy of [Lurgi GmbH, 2008] 6
Figure 2.2: Simplified scheme of HP POX plant (including quench system) [Lurgi GmbH, 2008] 7
Figure 2.3: Overview of reactions of methane 10
Figure 3.1: Simplified scheme for HP POX quench water system 18
Figure 3.2: Aspen Plus flow diagrams of simulated HP POX quench water system 19
Figure 3.3: Integration of information and functions in VBA via Microsoft Excel to Aspen Plus model 25
Figure 3.4: Integration of information and functions in Python via Microsoft Excel to Aspen Plus model 26
Figure 3.5: ASW enables Excel users to rapidly run scenarios using the underlying rigorous models to analyze plant data, monitor performance, and make better decisions. 27
Figure 4.1: Vapour-liquid equilibria system of CO2, H2S, NH3, HCN and organic acids in the quench water and extended mechanisms according to [Kamps et al., 2001], [Alvaro et al., 2000], [Kuranov et al., 1996], [Xia et al., 1999] and [Edwards et al., 1978]. 30
Figure 4.2: HP POX quench water system with pH regulator for sensitivity studies 34
Figure 4.3: Henry´s constant for CO2, H2S, NH3 and HCN derived from [Edwards et al., 1978] for CO2, [Alvaro et al., 2000] for NH3, [Kamps et al., 2001] for H2S, and [Rumpf et al., 1992] for HCN 35
Figure 4.4: Dissociation constants for CO2, H2S, NH3, HCN and H2O derived from [Alvaro et al., 2000], [Kamps et al., 2001], and [Edwards et al., 1978] 37
Figure 4.5: The flow of CO2 in the quench water cycle (test point VP1). 40
Figure 4.6: Calculated quench water temperature variation and effects on CO2 distribution 42
Figure 4.7: Calculated influence of pH regulation and effects on CO2 distribution 43
Figure 4.8: The flow of NH3 in the quench water cycle (test point VP1). 46
Figure 4.9: Calculated quench water temperature variation and effects on NH3 distribution 47
Figure 4.10: Calculated influence of pH regulation and effects on NH3 distribution 48
Figure 4.11: The flow of HCN in the quench water cycle (test point VP1). 49
Figure 4.12: Calculated quench water temperature variation and effects on HCN distribution 50
Figure 4.13: Calculated influence of pH regulation and effects on HCN distribution 51
Figure 4.14: The flow of H2S in the quench water cycle (test point VP1) 53
Figure 4.15: Calculated quench water temperature variation and effects on H2S distribution 54
Figure 4.16: Calculated influence of pH regulation and effects on H2S distribution 55
Figure 5.1: Aspen Plus back-calculated (real) formic acid concentration, quench water temperature and the calculated equilibrium formic acid concentration against back-calculated (real) ammonia concentration for the 47 test points (using amongst others sampled HCOO- and NH4+ values according to Table 2.6). 59
Figure 5.2: Aspen plus back-calculated (real) formic acid concentration, back-calculated (real) ammonia concentration and the calculated equilibrium formic acid concentration against quench water temperature for the 47 test points (using amongst others sampled HCOO- and NH4+ values according to Table 2.6). 60
Figure 5.3: Aspen plus back-calculated (real) acetic acid concentration, quench water temperature and the calculated equilibrium acetic acid concentration against back-calculated (real) ammonia concentration for the 47 test points. 61
Figure 5.4: Aspen plus back-calculated (real) acetic acid concentration, back-calculated (real) ammonia concentration and the calculated equilibrium acetic acid concentration against quench water temperature for the 47 test points. 62
Figure 5.5: Concentration of formic acid (Aspen plus calculated m_eq and back-calculted m_real) formation in the quench and quench water temperature for the 47 test points. 64
Figure 5.6: Concentration of formic acid (Aspen plus calculated m_eq and back-calculted m_real) in the quench against quench water temperature for the 47 test points (as in Fig.5.2). 65
Figure 5.7: Comparison between formic acid equilibrium constant (Keq), reaction quotient (Kreal) and the quench water temperature for the 47 test points. 66
Figure 5.8: Comparison between formic acid equilibrium constant (Keq) and reaction quotient (Kreal) against quench water temperatures for the 47 test points. 67
Figure 5.9: Concentration of acetic acid (Aspen plus calculated m_eq and back-calculted m_real) in the quench and quench water temperature for the 47 test points. 69
Figure 5.10: Concentration of acetic acid (Aspen plus calculated m_eq and back-calculted m_real) in the quench against quench water temperature for the 47 test points (as in Fig.5.4). 70
Figure 5.11: Comparison between acetic acid equilibrium constant (Keq), reaction quotient (Kreal) and the quench water temperature for the 47 test points. 71
Figure 5.12: Comparison between acetic acid equilibrium constant (Keq) and reaction quotient (Kreal) against quench water temperatures for the 47 test points. 72
Figure 6.1: Mole fraction of gas compoents in the hot gas outlet out of gasifier against hot gas temperature for the 47 test points 76
Figure 6.2: Calculated reaction quotient (Q) and equlibrium constant (Keq) for NH3 against hot gas temperature for the 47 test points (see Fig. 9.10 in Appendix) 77
Figure 6.3: NH3 temperature approach against hot gas temperature for the 47 test points (see Fig. 9.11 in Appendix) 78
Figure 6.4: Calculated reaction quotient (Q) and equlibrium constant (Keq) for HCN against hot gas temperature for the 47 test points (see Fig. 9.13 in Appendix) 79
Figure 6.5: HCN temperature approach against hot gas temperature for the 47 test points (see Fig. 9.14 in Appendix) 80
Figure 6.6: Comparison between calculated real and equilibrium hot gas N2, NH3 and HCN mol fractions against their respective hot gas temperature (case 1). 82
Figure 6.7: Relations between back-calculated real and equilibrium hot gas N2, NH3 and HCN mol fractions (for chemical equilibrium according to equations (6.1) and (6.4)) against their respective hot gas temperature (see Case 1, Section 6.4.1, and Fig. 6.6) 82
Figure 6.8: Comparison between calculated real and equilibrium hot gas HCN mol fraction against their respective hot gas temperature (case 2). 83
Figure 6.9: Relations between back-calculated real and equilibrium hot gas HCN mol fractions, and change in NH3 mol fractions (for chemical equilibrium according to equation (6.4)), against their respective hot gas temperature (see. Case 2, Section 6.4.2 and Fig. 6.7) 84
Figure 6.10 Comparison between NH3 and HCN formation (mole fraction) calculated equilibrium constant (Keq) and calculated reaction quotient (Q), N2 consumption and hot gas temperatures for the 47 test points (case 1 and case 2). 85
Figure 7.1: HP POX test plant quench water system 88
Figure 7.2: Traces of BTEX measured in the Gas-POX 203 – 207 quench water effluent sample. 91
Figure 7.3: Individual component of BTEX measured in the Gas-POX 203 – 207 quench water effluent sample. 92
Figure 7.4: (a) Alkyl radical decomposition and (b) C1 and C2 hydrocarbons oxidation mechanism [Warnatz et al., 2000] 93
Figure 7.5: Recombination of C3H3 to form benzene 94
Figure 7.6: The Diels - Alder reaction for the formation of PAHs 95
Figure 7.7: Amount of PAHs that were detected in Gas-POX 203 – 207 test points quench water effluent samples. 97
Figure 7.8: Distribution of PAH compounds in Gas-POX 203 – 207 quench water effluent samples. 98
Figure 7.9: Some steps in soot formation [McEnally et al., 2006]. 99
Figure 7.10: Illustration of soot formation path in homogenous mixture [Bockhorn et al., 1994] 100
Figure 9.1: Aspen flow sheet set up for HP POX quench system GasPOX 201 VP1 (simplified and extension of Fig. 3.2, organic acids not taken into account). Tabulated values are given in Table 9.11. 135
Figure 9.2: Comparison between the Henry´s constant profiles: Aspen Plus (markers) and Literatures (solid lines) ([Edwards et al., 1978] for CO2, [Alvaro et al., 2000] for NH3, [Kamps et al., 2001] for H2S, and [Rumpf et al., 1992] for HCN as it can be seen in Fig. 4.3) 137
Figure 9.3: Henry´s constant profiles derived from literatures ([Edwards et al., 1978] for CO2, [Alvaro Pérez-Salado et al., 2000] for NH3, [Kamps et al., 2001] for H2S, and [Rumpf et al., 1992] for HCN as it can be seen in Fig. 4.3) 137
Figure 9.4: Comparison between the dissociation constant profiles: Aspen Plus (markers) and Literatures (solid or dashed lines) [Alvaro et al., 2000], [Kamps et al., 2001], and [Edwards et al., 1978] as in Fig.4.4. 138
Figure 9.5: Dissociation constant profiles derived from literatures [Kamps et al., 2001], and [Edwards et al., 1978] as in Fig.4.4. 138
Figure 9.6: Calculated pH values, temperature range and species 139
Figure 9.7: Aspen Plus flow sheet setup for organic acid compounds calculations (GasPOX 201 VP1, see also Table 9.12) 142
Figure 9.8: Aspen Plus flow sheet setup for nitrogen compounds calculations (GasPOX 201 VP1, see also Table 9.12, organic acids are taken into account in the aqueous streams of the quench system) 145
Figure 9.9: Yield of ammonia in gasifier (calculated real) and hot gas temperature against the 47 test points 146
Figure 9.10: Kreal or reaction quotient for ammonia formation in the gasifier against the 47 test points. 146
Figure 9.11: Temperature approach studies for ammonia and the 47 test points 147
Figure 9.12: Yield of HCN from the gasifier (calculated real and equilibrium) and hot gas temperature and the 47 test points 147
Figure 9.13: Comparison between equilibrium constant and reaction quotient for HCN and 47 test points 148
Figure 9.14: Temperature approach studies for HCN and the 47 test points 148
Figure 9.15: Comparison among equilibrium constants of reactions against temperature, T [°C] 149
Figure 9.16: Comparison among equilibrium constants of reactions against temperature, 1/T [1/K] 150
List of Tables
Table 2.1: Outline of Gas-POX mode operating parameter range 8
Table 2.2: Outline of test runs operating mode and parameters of chosen test campaigns 9
Table 2.3: Natural gas feedstock compositions 12
Table 2.4: Product synthesis gas analysis method (hot gas before quench) [Brüggemann, 2010] 12
Table 2.5: Analysis methods for raw synthesis gas [Brüggemann, 2010] 13
Table 2.6: Analysis methods for aqueous phase products [Brüggemann, 2010] 14
Table 2.7: Relative accuracy for the measured value for temperature, pressure and flow of each feed and product stream [Meyer, 2007] and [Brüggemann, 2010] 17
Table 3.1: Description of blocks used in Aspen Plus simulation. 20
Table 3.2: HP POX test plant quench water cycle parameters Gas-POX 201 VP1* 23
Table 3.3: pH regulator parameters 24
Table 4.1: Organic acids distribution in streams for VP1 based on calculation from Aspen Plus. 38
Table 4.2: The distribution of CO2 and its ions in all the streams 40
Table 4.3: The distribution of NH3 and its ions in all the streams 45
Table 4.4: The distribution of HCN and its ions in all the streams 49
Table 4.5: The distribution of H2S and its ions in all the streams 52
Table 7.1: Relative sooting tendency [Tesner et al., 2010] 101
Table 9.1: Natural gas feed analysis method [Brüggemann, 2010] 135
Table 9.2: pH scale with examples of solution [NALCO 2008] 136
Table 9.3: Gas-POX test campaigns and with designated serial numbers 140
Table 9.4: Summary of correlation coefficient (r) from Figures in Chapter 5 144
Table 9.5: Comparison among reactions temperatures and heat of reactions 149
Table 9.6: Content of BTEX compounds in Gas-POX quench water samples 151
Table 9.7: BTEX in quench water effluent samples results 152
Table 9.8: Content of PAH compounds in Gas-POX quench water samples 157
Table 9.9: PAHs in quench water effluent samples results 160
Table 9.10: Soot in quench water effluent samples results 169
Table 9.11: Aspen Plus flow sheet setup stream details (GasPOX 201 VP1, according to Fig.3.2 and Fig.9.1, organic acids not taken into account) 170
Table 9.12: Aspen Plus flow sheet setup for organic acid and nitrogen compounds calculations for GasPOX 201 VP1 (according to Figures 9.7 and 9.8, organic acids are taken into account) 174
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Development aid - a perspective on the World Bank performance: Calculating the social return on investment for the least developed countriesSchäfer, Dominik 02 March 2016 (has links)
This doctoral thesis focuses on the evaluation of the World Bank (WB) performance in delivering development aid to the Least Developed Countries (LDCs). For this purpose, an extensive research was performed to analyze a set of 790 Implementation Completion and Results reports for key economic and financial indicators. Results of this research provide various insights for the appraisal and the results stage of project delivery of the LDCs in different continents. In the final part of the economic and financial analysis the minimum Social Return on Investment (SROI) of the LDCs including all project costs was calculated. This SROI ratio outcome of 1 and 1.06 in the weighted and 1.3 and 1.72 in the unweighted case indicate that projects delivered by the WB have a positive effect on the poor countries. In the second part of this research project the data set of the ICR reports was qualitatively researched for negative ratings according to 3 core assessment categories for the overall project performance: Sustainability, bank performance and borrower performance. As a result the most critical categories respectively risks were outlined. In conclusion, the research analyses and findings support the general demand to provide even more development assistance to poor countries.:Table of Tables and Figures
List of Equations
List of Abbreviations
1 Introduction
1.1 Introduction to the Topic
1.2 Assessing Poverty Problems and Achieving Economic Growth
1.3 Millennium Development Goals
1.4 Development Aid
2 Research Approach
2.1 Objective
2.2 Structure
2.3 Least Developed Countries
2.4 World Bank
2.5 Data Access and Relevance
2.5.1 Data Basis
2.5.2 Implementation Completion and Results Reports
2.5.3 Project Types
2.6 Term “Performance”
2.7 Study and Research Questions
2.8 Challenges of this Doctoral Thesis
2.9 Contribution of this Thesis
3 Economic and Financial Analysis
3.1 SROI Concept
3.1.1 SROI Definition
3.1.2 SROI Process and Impact Map
3.1.3 Cost-Benefit-Analysis
3.1.4 SROI Calculation
3.2 SROI of World Bank Projects
3.2.1 Purpose of the Cost-Benefit-Analysis
3.2.2 Indicators of the SROI Calculation
3.2.2.1 Net Present Value
3.2.2.2 Capital and Recurring Costs
3.2.2.3 Project Dates and Duration
3.2.2.4 NPV-horizon
3.2.2.5 Discount Rate
3.2.3 Types of NPV-Cost-Ratios
3.2.3.1 Pro-Rata-Capital-Costs Ratio
3.2.3.2 Total-Capital-Costs Ratio
3.2.3.3 Pro-Rata-Capital plus Recurring-Costs Ratio
3.2.3.4 Total-Capital plus Recurring-Costs Ratio
3.2.4 Calculation of the proper SROI Ratio
3.2.5 Portfolio Analysis
3.2.6 Sensitivity Analysis
3.3 Additional Economic and Financial Indicators
3.3.1 Economic Rate of Return
3.3.2 Benefit-Cost-Ratio
3.3.3 Net Benefit
3.3.4 Financial Net Present Value
3.3.5 Financial Rate of Return
4 Results of the Economic and Financial Analysis
4.1 Analysis Approach and Setup
4.2 NPV Outcomes at the Appraisal Stage
4.2.1 Appraisal NPVs of the LDCs
4.2.2 Appraisal NPV Continent Comparison
4.3 NPV Outcomes of the Result Stage
4.3.1 Result NPVs of the LDCs
4.3.2 Result NPV Continent Comparison
4.4 Appraisal vs. Result NPVs
4.4.1 Results of the LDCs
4.4.2 Continent Comparison
4.5 Economic Rate of Return Result Values
4.5.1 Results of the LDCs
4.5.2 Continent Comparison
4.6 Additional Economic and Financial Indicator Result Values
4.6.1 Benefit-Cost-Ratio and Net Benefit
4.6.2 Financial Net Present Value and Financial Rate of Return
4.7 Overall Project Performance
4.7.1 Definition
4.7.2 Overall Project Performance Ratings
4.7.3 Outcome Calculation for Non-Financial Indicator Projects
4.7.4 Verification of Outcomes and Conclusion
4.8 NPV-Cost-Ratios and SROI Calculation
4.8.1 NPV-Cost-Ratios of the ICR Reports
4.8.1.1 Overall Results
4.8.1.2 Continent Comparison
4.8.2 Standardized NPV-Cost-Ratios
4.8.2.1 Overall Results
4.8.2.2 Continent Comparison
4.8.3 Calculating the Minimum SROI Ratio
4.8.3.1 Overall Results of the Capital SROI Ratio
4.8.3.2 Continental Comparison of the Capital SROI Ratio
4.8.3.3 Overall Results of the Minimum SROI Ratio
4.8.3.4 Continental Comparison of the Minimum SROI Ratio
4.8.4 Making Meaning of the Results
4.9 Summary and Conclusion
5 Qualitative Data Analysis
5.1 Content Analysis
5.2 Sustainability
5.2.1 Sustainability Rating Definition
5.2.2 Sustainability Rating Categories
5.3 Bank Performance
5.3.1 Bank Performance Definition
5.3.2 Bank Performance Categories
5.4 Borrower Performance
5.4.1 Borrower Performance Definition
5.4.2 Borrower Performance Categories
6 Results of the Qualitative Data Analysis
6.1 Sustainability
6.1.1 Quantitative Assessment of Sustainability Ratings
6.1.2 Outcome of the Content Analysis
6.1.2.1 Types of Reasons
6.1.2.2 Overall Results
6.1.2.3 Results in Haiti
6.1.2.4 Continent Comparison
6.1.3 Excursus: Positive NPV Projects
6.1.4 Summary and Conclusion
6.2 Bank Performance
6.2.1 Quantitative Assessment of Bank Performance Ratings
6.2.2 Outcome of the Content Analysis
6.2.2.1 Types of Reasons
6.2.2.2 Overall Results
6.2.2.3 Results in Haiti
6.2.2.4 Continent Comparison
6.2.3 Summary and Conclusion
6.3 Borrower Performance
6.3.1 Quantitative Assessment of Borrower Performance Ratings
6.3.2 Outcome of the Content Analysis
6.3.2.1 Types of Reasons
6.3.2.2 Overall Results
6.3.2.3 Results in Haiti
6.3.2.4 Continent Comparison
6.3.3 Summary and Conclusion
7 Overall Summary and Conclusion
8 Critical Acclaim and Recommendations
9 Outlook and Future Research
List of Appendices
Appendix
References
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