modelling, design and optimisation of equipment for

i

Modelling, Design And Optimisation of Equipment

for Toluene Emissions Abatement and

Concentration/Purification of Pigment Dispersions

in Inkjet Colorants Manufacturing Processes

Ana Sofia Vaz Cardoso

Dissertação para obtenção do Grau de Mestre em

Engenharia Química

Júri

Presidente: Prof. João Carlos Salvador Fernandes (IST)

Orientadores: Prof.ª Maria Norberta Neves Correia de Pinho (IST)

Gary Cuthbertson (Fujifilm Imaging Colorants)

Vogal: Prof. Vítor Manuel Geraldes Fernandes (IST)

Outubro 2008

ii

ACKNOWLEDGEMENTS __________________________________ _____

Professor Maria Norberta de Pinho for the patience and disponibility.

I would like to thank everyone in Fujifilm Imaging Colorants for the support and experience.

To

Gary Cuthbertson for being an excellent supervisor at the membrane lab, for his patience,

support whenever I needed and for having corrected my report.

Alan Wilson my supervisor in the Engineering Department for sharing his knowledge with me

and for all the good mood.

Zac Meadows for being a good professional and for having corrected my report.

Richard Griffiths and Marie Ging for helping me in the lab and for their experience.

My Portuguese colleagues Isabel Ferreira and Ricardo Duarte for the support and for making

me laugh in the morning.

I would also like to thank to:

My friends for all the support.

My boyfriend Bruno Custódio for being such a good friend and for all the support and

strength.

And last but surely not least, my parents and brothers for believing in me and for all the

encouragement, support and strength.

iii

RESUMO ___________________________________________________

Esta dissertação aborda o abatimento de compostos orgânicos voláteis (VOC) nomeadamente

tolueno e a purificação/concentração de dispersões de pigmento em processos de fabrico de corantes

para impressoras de jacto de tinta na Fujifilm Imaging Colorants.

As emissões de tolueno provenientes do processo de fabrico das tintas para impressoras a jacto de

tinta foram quantificadas utilizando equações da Agência Protectora do Ambiente (EPA) e o SuperPro

Designer (SPD, programa de simulação de processos de Engenharia Química). Foi desenvolvido um

modelo baseado na absorção gasosa para um lavador de gases (scrubber) já existente a fim de calcular

a eficiência na redução de COVs (VOCs). O modelo consiste em dois scrubbers, o primeiro consiste

numa primeira lavagem com recirculação contínua sendo o segundo sem recirculação.

Os valores da quantificação das emissões de tolueno calculadas através das equações da EPA foram

comparadas com os resultados obtidos pelo SPD, a fim de avaliar as alterações recentes ao cálculo para

a concepção e simulação do software.

Foi encontrado um valor máximo de 50% para a eficiência do primeiro scrubber. No entanto, devido

a um efeito de stripping, foram também observados valores negativos. Para o segundo scrubber foi

encontrado um valor de 34% resultando num valor máximo para eficiência global de 64%. Aumentar o

caudal de líquido terá o benefício mais imediato em termos de eficiência remoção.

O actual sistema de lavagem foi capaz de atingir níveis insignificantes para as emissões a longo

prazo, mas não conseguiu alcançar rotineiramente os níveis requeridos para as emissões a curto prazo.

A utilização do condensador no reactor do processo (não considerado para os cálculos) e/ou um

aumento do caudal de líquido no scrubber irá garantir o abatimento das emissões global de curto e longo

prazo ao nível do solo.

No que diz respeito à produção de dispersões reactivas, é investigada a ultrafiltração no modo de

diafiltração na concentração e purificação de dispersões de pigmento a fim de produzir um produto de

melhor qualidade com uma cor mais intensa.

Os ensaios de ultrafiltração foram realizados num módulo plano de membranas do laboratório 5 de

tecnologia de processo. Foram utilizadas membranas de polisulfona com uma superfície total de 0.684

m2. Ao longo dos ensaios de concentração e diafiltração foram realizadas medidas do fluxo de permeado

e de conductividade.

As medições de condutividade são utilizadas para avaliar o grau de remoção de impurezas. A sua

variação com os volumes de lavagem utilizados na fase de diafiltração foi ajustada a uma lei de potência.

A remoção de uma impureza, aqui chamada de componente X por motivos de confidencialidade, foi

estimada através de uma análise de sólidos totais feito no início e no final dos ensaios, bem como

iv

através de uma curva de calibração calculada anteriormente. Foram detectadas algumas discrepâncias e

foi proposto trabalho a realizar posteriormente.

Os valores das taxas de fluxo de permeado durante a etapa de purificação são diferentes mediante a

origem das amostras, ou seja, as amostras obtidas na unidade piloto apresentam taxas mais baixas do

que as que foram obtidas no laboratório.

Palavras-chave: Compostos Orgânicos Voláteis, Absorção Gasosa, Tintas para impressoras a jacto

de tinta (inkjet dyes), Ultrafiltração, Dispersões de pigmento.

v

ABSTRACT __________________________________________ _______

This thesis addresses the abatement of volatile organic compounds (VOC) namely toluene and

the purification/concentration of pigment dispersions in inkjet colorants manufacturing processes at

Fujifilm Imaging Colorants.

Toluene emissions from the inkjet dye manufacturing process were quantified using

Environmental Protection Agency (EPA) equations and SuperPro Designer (SPD, Chemical Engineering

Simulation Program). A model based in gas absorption for an existing scrubber was developed in order to

calculate the efficiency in the VOC abatement. The model consisted in a multi-bed scrubber made up of a

first scrubber with recirculation and a continuous second scrubber.

Quantification of toluene emissions with EPA equations were compared with the results from SPD in

order to assess recent calculation changes to the design and simulation software.

A maximum efficiency value of 50% was found for the first scrubber. However, due to stripping,

negative values were also observed. For the second scrubber a value of 34% was found. This resulted in

an overall maximum efficiency value of 64%. Increasing the liquid flow rates will have the most immediate

benefit in terms of removal efficiency.

The current scrubber system was able to achieve insignificant levels for long term emissions but was

unable to routinely achieve short term ones. Use of the existing condenser in the process reaction vessel

(not consider for calculations) and/or increased liquid flow to the scrubber will ensure that overall

abatement would satisfy both short and long term ground level concentrations.

In the reactive dispersants production ultrafiltration in diafiltration mode is investigated for the

concentration and purification of pigment dispersions in order to yield a better quality product with a

stronger color.

The ultrafiltration permeation experiments were performed in the PT (Process Technology) Lab. 5 flat

sheet membrane unit with polysulphone membranes with a total surface area of 0.684 m2. Flux rates and

conductivity measurements were taken along the diafiltration and concentration stages.

The conductivity measurements are used to assess the degree of impurities removal. Its variation

with diafiltration wash volumes was fitted through a power-law correlation.

An impurity removal (named as Component X due to confidentiality issues) was estimated through a

total solids analysis done in the beginning and at the end of runs as well as through a calibration curve

calculated previously. Some discrepancies were found and further work was proposed.

Permeate flux rates values during the diafiltration purification stage are different upon the samples

origin. That is, the samples obtained at the pilot plant scale yield lower permeate flux rates than the ones

obtained in the lab.

vi

Keywords : Volatile Organic Compounds, Gas Absorption, Inkjet Dye, Ultrafiltration, Pigment

Dispersions.

vii

TABLE OF CONTENTS ________________________________ _______

Acknowledgements ............................................................................................................................. ii

Resumo ..............................................................................................................................................iii

Abstract ............................................................................................................................................... v

Index of figures .................................................................................................................................... x

Index of tables ................................................................................................................................... xiii

Nomenclature .................................................................................................................................... xv

List of abbreviations ......................................................................................................................... xvii

1. Thesis Introduction .......................................................................................................................... 1

1.2. Work developed ....................................................................................................................... 2

1.3. State-Of-The-Art for VOC Abatement and Membranes ............................................................. 2

1.3.1. Membrane technology and VOCs ...................................................................................... 2

1.3.1.1. Removal of VOCs from air by membrane-based absorption and stripping ................... 3

1.3.1.2. Performance of commercial-size plasmapolymerized PDMS-coated hollow fiber

modules in removing VOCs from N2/air ................................................................................... 5

1.3.1.3. Toluene Removal From Waste Air Using a Flat Composite Membrane Bioreactor ....... 5

1.4. Dyes and Pigments Dispersions ............................................................................................... 6

1.4.1. Dyes ................................................................................................................................. 6

1.4.1.1. Manufacture ............................................................................................................... 7

1.4.2. Pigment Dispersions.......................................................................................................... 8

Toluene Emissions Abatement ....................... .................................................................................... 10

1. Introduction ................................................................................................................................... 10

1.1. Environmental Regulations ..................................................................................................... 10

1.1.1. Toluene Emissions .......................................................................................................... 11

1.2. VOC Control Systems ............................................................................................................ 11

1.3. Basic Air Emission Models...................................................................................................... 13

1.4. SuperPro Designer ................................................................................................................. 13

2. Theory ........................................................................................................................................... 14

2.1. Gas Absorption ...................................................................................................................... 14

2.1.1. Solubility ......................................................................................................................... 14

2.1.2. Equations ........................................................................................................................ 15

2.1.3.1. Prediction of the height of a transfer unit ................................................................... 17

2.1.3.2. Onda’s method ......................................................................................................... 18

viii

3. Experimental ................................................................................................................................. 19

3.1. Process .................................................................................................................................. 19

3.1.1. Process Emissions .......................................................................................................... 20

3.2. Toluene Abatement Equipment ............................................................................................... 22

3.2.1. Scrubbers description - Modelling .................................................................................... 23

4. Results and discussion .................................................................................................................. 26

4.1. Process Emissions Results ..................................................................................................... 26

4.2. Scrubbers Modelling Results .................................................................................................. 27

4.2.1. Scrubbers Analysis .......................................................................................................... 32

4.2.1.1. Scrubbers sensitivity analysis summary .................................................................... 39

5. Conclusion .................................................................................................................................... 40

Pigment Dispersions Concentration/Purification .... .......................................................................... 42

1. Membrane Technology Introduction ............................................................................................... 42

1.1. History .................................................................................................................................... 42

1.2. Definition ................................................................................................................................ 43

1.2.1. Cross flow vs. dead end .................................................................................................. 44

1.3. Types of Membrane ................................................................................................................ 45

1.4. Membrane Modules ................................................................................................................ 46

1.4.1. Spiral-wound module ....................................................................................................... 46

1.4.2. Tubular Module ............................................................................................................... 47

1.4.3. Hollow-Fibre Module........................................................................................................ 48

1.4.4. Plate and Frame .............................................................................................................. 49

1.4.5. Membrane modules comparison ...................................................................................... 50

1.5. Membrane Applications .......................................................................................................... 50

1.5.1 Pressure Driven Processes .............................................................................................. 51

2. Experimental ................................................................................................................................. 54

2.1. Ultrafiltration in Reactive Dispersants ..................................................................................... 54

2.2. Membrane Unit Description .................................................................................................... 54

2.3. Experimental Procedure ......................................................................................................... 58

2.3.1. Diafiltration ...................................................................................................................... 61

2.3.2. Working conditions: Inlet Pressure 8 bar & no back pressure applied ............................... 62

2.4. Water Analysis ....................................................................................................................... 62

3. Results and Discussion ................................................................................................................. 64

3.1. Excel Run Spreadsheet .......................................................................................................... 64

3.1.1. Mass balance .................................................................................................................. 67

3.1.1.1. Pigment Recovery .................................................................................................... 67

ix

3.1.1.2. Component X removal .............................................................................................. 68

3.2. Samples Results Comparison ................................................................................................. 70

3.2.1. Permeate conductivity vs. run time .................................................................................. 70

3.2.2. Permeate conductivity vs. final concentration factor ......................................................... 75

3.2.3. Flux rate vs. wash volumes.............................................................................................. 77

3.2.4. Mass balance .................................................................................................................. 79

3.3. Cold Water Flow Monitoring .................................................................................................... 81

4. Conclusion .................................................................................................................................... 84

References ........................................ ................................................................................................... 86

Appendix .......................................... .................................................................................................... 89

x

INDEX OF FIGURES __________________________________________

Figure 1. Schematic process diagram for VOC removal from air by absorption and stripping in hollow fiber

modules [9]. .................................................................................................................................... 4

Figure 2. Experimental setup for VOC removal by hollow-fibre vapour permeation membrane process [8].

....................................................................................................................................................... 5

Figure 3. Basic steps of dye manufacture [13]. ......................................................................................... 7

Figure 4. Gas absorption concentration relationships [27]. ..................................................................... 16

Figure 5. Schematic diagram of a venturi (on the left) [24] and a packed tower scrubber (on the right) [25].

..................................................................................................................................................... 22

Figure 6. Scrubber Schematics .............................................................................................................. 23

Figure 7. First scrubber efficiency variation with time (negative absorption efficiency values are due to

stripping). ...................................................................................................................................... 27

Figure 8. Operating lines of the first scrubber system ............................................................................. 28

Figure 9. Variation with time of toluene in the liquid phase in the first scrubber (red line indicates toluene

solubility in water at 20C) .............................................................................................................. 28

Figure 10. Second scrubber efficiency variation with time ...................................................................... 29

Figure 11. Variation with time of toluene in the liquid phase in the second scrubber (red line indicates

toluene solubility in water at 20 ºC) ................................................................................................ 29

Figure 12. Toluene emissions variation with time (mg/m3) ...................................................................... 30

Figure 13. Toluene emissions variation with time (kg/h) ......................................................................... 31

Figure 14. Overall efficiency variation with time ...................................................................................... 31

Figure 15. Comparison between first scrubber efficiency variation with time for toluene constant flow rate

of 0.833 kg/h (on the left) and 4.16 kg/h (on the right). Calculations were made for several nitrogen

flow rates. ..................................................................................................................................... 32

Figure 16. Comparison between second scrubber efficiency variation with time for first scrubber toluene

constant flow rate of 0.833 kg/h (on the left) and 4.16 kg/h (on the right). Calculations were made for

several nitrogen flow rates. ............................................................................................................ 33

Figure 17. Comparison between toluene emissions variation with time for first scrubber toluene constant

flow rate of 0.833 kg/h (on the left) and 4.16 kg/h (on the right). Calculations were made for several

nitrogen flow rates. ........................................................................................................................ 34

Figure 18. Comparison between variation with time of the toluene in the liquid phase for toluene flow rate

of 0.833 kg/h (on the left) and 4.16 kg/h (on the right). Calculations were made for several nitrogen

flow rates (red line indicates toluene solubility in water at 20 ºC). ................................................... 35

xi

Figure 19. Comparison between variation with time of the overall efficiency for toluene flow rate of 0.833

kg/h (on the left) and 4.16 kg/h (on the right). Calculations were made for several nitrogen flow

rates.............................................................................................................................................. 36

Figure 20. Comparison between variation with time of the efficiency in the continuous scrubber for toluene

flow rate of 0.833 kg/h (on the left) and 4.16 kg/h (on the right). Calculations were made for several

water flow rates. ............................................................................................................................ 36

Figure 21. Second scrubber efficiency variation with time for several water flow rates ............................ 37

Figure 22. Overall efficiency variation with time for several water flow rates ........................................... 38

Figure 23. Toluene emissions variation with time for several water flow rates ........................................ 38

Figure 24. Schematic diagram of a membrane with selective permeability. ............................................. 43

Figure 25. Tangential vs. dead-end flow [31]. ......................................................................................... 44

Figure 26. Schematic diagrams of the principal types of membrane [13]................................................. 45

Figure 27. Schematic diagram of spiral-wound module [30], [32]. ........................................................... 47

Figure 28. Schematic diagram and picture of tubular modules [33], [34]. ................................................ 48

Figure 29. Hollow-fibre module (left) and single fibre (right) [30]. ............................................................ 48

Figure 30. Picture and schematic diagram of a plate and frame module [35]. ......................................... 49

Figure 31. Filtration Spectrum [38]. ........................................................................................................ 52

Figure 32. Reactive Dispersants Process. .............................................................................................. 54

Figure 33. DDS Flat sheet unit at Fujifilm membrane lab ........................................................................ 55

Figure 34. Plate, spacers and membranes of the flat sheet unit .............................................................. 55

Figure 35. Closer look of a spacer ......................................................................................................... 56

Figure 36. Plate and frame unit schematics and picture of the DDS unit. ................................................ 57

Figure 37. SEMS of GRM 0.2PP membranes ........................................................................................ 58

Figure 38. Water cold flow step (recirculation). ....................................................................................... 59

Figure 39. Initial concentration (steps 5 and 7 on the left, step 6 on the right). ........................................ 60

Figure 40. Diafiltration step. ................................................................................................................... 60

Figure 41. Final concentration and water recirculation step. ................................................................... 61

Figure 42. Cylinders for the producing of deionised water (on the left) and biofilters (on the right) [39],

[40]. .............................................................................................................................................. 62

Figure 43. Bacteria analysis test [41]. .................................................................................................... 63

Figure 44. Excel run spreadsheet .......................................................................................................... 64

Figure 45. Feed temperature vs. time for a yellow sample ...................................................................... 65

Figure 46. Permeate conductivity vs. time for a yellow sample ............................................................... 66

Figure 47. Permeate flux rate vs. time for a yellow sample ..................................................................... 67

Figure 48. Mass balance ....................................................................................................................... 68

Figure 49. Component X removal calculation example ........................................................................... 69

xii

Figure 50. Permeate conductivity vs. run time for black (K), cyan (C), yellow (Y) and magenta (M)

samples processed in the DDS unit ............................................................................................... 70

Figure 51. Permeate conductivity vs. wash volumes for black (K), cyan (C), yellow (Y) and magenta (M)

samples processed in the DDS unit. Exponential trendline adjustment. .......................................... 71

Figure 52. Permeate conductivity vs. wash volumes for black (K), cyan (C), yellow (Y) and magenta (M)

samples processed in the DDS unit. Power trendline adjustment. .................................................. 73

Figure 53. Permeate conductivity vs. wash volumes for all the samples processed in the DDS unit.. ...... 74

Figure 54. Permeate conductivity vs. wash volumes for all the samples processed in the DDS unit. Final

concentration values. .................................................................................................................... 75

Figure 55. Final permeate conductivity values vs. concentration factor. .................................................. 76

Figure 56. Permeate flux rate vs. wash volumes for black (K), cyan (C), yellow (Y) and magenta (M)

samples processed in the DDS unit. .............................................................................................. 77

Figure 57. Permeate flux rate vs. wash volumes for all the samples processed in the DDS unit. ............. 78

Figure 58. Product yield (pigment) vs. samples processed in the DDS unit. ............................................ 79

Figure 59. Unit losses vs. samples processed in the DDS unit. .............................................................. 79

Figure 60. Displacement losses vs. samples processed in the DDS unit................................................. 80

Figure 61. Comparison between Component X removal estimation by total solids and Component X

calibration curve. ........................................................................................................................... 80

Figure 62. Cold water flow measurements ............................................................................................. 82

Figure 63. Difference between final and initial cold water flow rate vs. samples processed in the DDS unit

(blue). Difference between final and initial back pressure applied vs. samples processed in the DDS

unit (orange).................................................................................................................................. 83

Figure A. 1. Henry’s constant for toluene in water versus temperature [46]. .......................................... 101

Figure A. 2. Three-dimensional plot of permeate flow rate vs. crossflow pump setting and vs.

transmembrane pressure (TMP). ................................................................................................. 101

Figure A. 3. Three-dimensional plot of permeate conductivity vs. crossflow pump setting and vs.


Figure A. 4. Three-dimensional plot of component X removal index vs. crossflow pump setting and vs.


Figure A. 5. Component X concentration vs. conductivity. .................................................................... 103

xiii

INDEX OF TABLES ___________________________________ ________

Table 1. Reagents used in the process .................................................................................................. 19

Table 2. VOCs emissions equations [19]. ............................................................................................... 21

Table 3. Toluene emissions during processing ....................................................................................... 21

Table 4. Toluene emissions from process (before condensation & abatement) ....................................... 26

Table 5. Scrubbers sensitivity results summary ...................................................................................... 39

Table 6. Membrane modules comparison [36]. ....................................................................................... 50

Table 7. Membrane processes characteristics [37]. ................................................................................ 51

Table 8. Characteristics and operating conditions for the DDS membranes ............................................ 57

Table A. 1. Nitrogen inlet stream (first scrubber) .................................................................................... 90

Table A. 2. Toluene inlet stream (first scrubber) ..................................................................................... 90

Table A. 3. Gas mixture entering the first scrubber ................................................................................. 90

Table A. 4. Liquid mixture inlet stream (top of first scrubber) .................................................................. 90

Table A. 5. Gas mixture entering the second scrubber ........................................................................... 90

Table A. 6. Liquid mixture inlet stream (top of second scrubber) ............................................................. 91

Table A. 7. First scrubber main results ................................................................................................... 91

Table A. 8. Second scrubber main results .............................................................................................. 91

Table A. 9. Onda method results (assuming Lm constant)....................................................................... 92

Table A. 10. Onda method results, kG values (x 10-3) ............................................................................. 92

Table A. 11. Efficiency values for the first scrubber ................................................................................ 93

Table A. 12. Efficiency values for the second scrubber........................................................................... 94

Table A. 13. Toluene emissions from second scrubber (mg/m3) ............................................................. 95

Table A. 14. Toluene solubility (bottom of first scrubber, g toluene/g H2O) .............................................. 96

Table A. 15. Overall efficiency ............................................................................................................... 97

Table A. 16. Second scrubber efficiency (%) for first scrubber inlet flow rate of toluene of 10kg/Bx and

50kg/Bx and for several water flow rates ....................................................................................... 97

Table A. 17. Overall efficiency (%) for first scrubber inlet flow rate of toluene of 10kg/Bx and 50kg/Bx and

for several water flow rates ............................................................................................................ 98

Table A. 18. Second scrubber efficiency (%) for actual toluene flow rates entering first scrubber (table

A.2) and for several water flow rates .............................................................................................. 98

Table A. 19. Overall efficiency (%) for actual toluene flow rates entering first scrubber (table A.2) and for

several water flow rates ................................................................................................................. 98

Table A. 20. Toluene emissions (kg/h) from second scrubber for actual toluene flow rates entering first

scrubber (table A.2) and for several water flow rates ..................................................................... 99

Table A. 21. Column details ................................................................................................................. 100

xiv

Table A. 22. Toluene properties ........................................................................................................... 100

Table A. 23. Methanol properties ......................................................................................................... 100

Table A. 24. Nitrogen properties .......................................................................................................... 100

Table A. 25. Water properties .............................................................................................................. 101

xv

NOMENCLATURE ____________________________________________

a Packing surface area per unit volume (m2/m3)

aw Effective interfacial area of packing per unit volume (m2/m3)

Ct Total molar concentration (kmol/m3)

DL Liquid diffusivity (m2/s)

DV Diffusivity of vapor (m2/s)

dp Packing size (m)

E Efficiency (%)

Gm flow rate of gas per unit area (kmol/m2.s or kg/m2.s)

g Gravitational acceleration (m/s2)

H Henry’s law constant (dimensionless or atm)

HG Height of gas film transfer unit (m)

HL Height of liquid film transfer unit (m)

HOG Height of overall gas phase transfer unit (m)

KG Overall gas phase mass transfer coefficient (kmol/m2.s.atm)

KL Overall liquid phase mass transfer coefficient (kmol/m2.s.atm)

K5 Constant in equation (15) (5.23 for packing sizes above 15 mm, and 2.00 for sizes below 15 mm)

kG Gas film mass transfer coefficient (m/s)

kL Liquid film mass transfer coefficient (m/s)

Lm flow rate of liquid per unit area (kmol/m2.s or kg/m2.s)

MWi Molecular weight of ith component

m Slope of equilibrium line

NOG Number of overall gas-phase transfer units

ninert Inert gas leaving the vessel during the operation (kmoles)

P Column operating pressure (atm or bar)

p* Vapor pressure of solute (atm)

P1 initial vessel pressure (Pa)

P2 final vessel pressure (Pa)

Pa1 initial pressure (Pa)

Pa2 final vessel pressure (Pa)

pi vapor pressure of ith component i at the exit temperature (Pa)

(pi)T1,T2 vapor pressure of component i at T1 or T2 (Pa)

(pj)T1,T2 vapor pressure of component j at T1 or T2 (Pa)

R ideal gas constant (8314 J/kmol.K)

T1 initial vessel temperature (K)

T2 final vessel temperature (K)

Vr volume of displaced gas (m3)

xvi

Vr,1 initial gas space volume (m3)

Vr,2 final gas space volume (m3)

x2 concentration of solute in solution at column top

xe the concentration in the liquid that would be in equilibrium with the gas concentration at any point

xi mole fraction of component i in the liquid mixture

xj mole fraction of component j in the liquid mixture

y1 concentration of solute in gas phase at column base

y2 concentration of solute in gas phase at column top

ye the concentration in the gas that would be in equilibrium with the liquid concentration at any point

Z Height of package (m)

σC Critical surface tension for packing material (N/m)

µL Viscosity of liquid (Pa.s)

µv Viscosity of vapor (Pa.s)

ρL Density of liquid (kg/m3)

ρv Density of vapor (kg/m3)

σL Liquid surface tension (N/m)

xvii

LIST OF ABBREVIATIONS _____________________________ ________

BAT – Best Available Techniques

CHIP – Control of Hazardous Information and Packaging Regulations

DV – Diafiltration volumes

EAL – Environmental Assessment Level

EPA – Environmental Protection Agency

EQS - Environmental Quality Standards

FFIC – Fujifilm Imaging Colorants

IPPC - Integrated Pollution Prevention and Control

PC – Permeate conductivity (in Concentration/Purification of Pigment Dispersions)

PC – Process Conditions (in Toluene Emissions Abatement)

PT – Process Technology

SEPA - Scottish Environment Protection Agency

SPD – SuperPro Designer

TMP – Transmembrane pressure

UF – Ultrafiltration

VOC – Volatile Organic Compounds

WV – Washing volumes

1

1. THESIS INTRODUCTION _____________________________________

FUJIFILM Imaging Colorants (FFIC) is a world leader in the development and supply of innovative,

high performance colorants for the global digital printing market. On Grangemouth site (Scotland) it

currently develops, manufactures and supplies colorants to major printer manufacturers. The

Grangemouth site is FFIC’s global centre of excellence for colorants manufacturing and process

technology [1].

The PT (Process Technology) Department within the Grangemouth site is the division responsible for

discovering innovative technical solutions and delivering individual business strategies for Fujifilm Imaging

Colorants. The department is committed to maintain and develop the technical competence of the

department in order to meet the current and future business opportunities. The PT department interacts

with Manufacturing, Plants and all Engineering activities [1].

Process Technology at Grangemouth is focused on new dye development processes and scale up of

the initial research samples. This involves the membrane team and the synthetic and organic chemists.

The latter develop new dyes from research of new synthetic routes, while the membrane team develops

the best ways to purify these new dyes.

The Ink Jet Group within the Process Technology Department works on a range of products designed

to meet customer’s needs for high quality dyes. It is responsible, within the Process Technology

Department, for developing processes to manufacture magenta, yellow, cyan and black dye bases on a

laboratory as well as pilot plant scale. The main product categories of the Inkjet Printing Materials

business are high purity dyes and a range of pigment-based and dye-based inks for use in ink jet printers.

The business has developed leading proprietary technologies to synthesize new generations of high

performance ink jet dyes and pigmented inks based on novel dispersants, resins and formulations. Part of

this work also includes, preparing samples for customers, for testing, and doing hazard analysis [1].

The new project Fujifilm Imaging Colorants has been involved is the investment in a new inkjet dye

manufacturing and finishing plant that will double the existing capacity. The project, for which the design

has already been completed, is for the new inkjet dyes production line within the existing facility [2]. The

new facility, now in commissioning stage, is expected to be completed and in full production by the end of

this year.

2

1.2. WORK DEVELOPED

The work developed in this thesis was within different inkjet colorants manufacturing processes: inkjet

dyes and pigment dispersions. The work in inkjet dyes within the engineering team involved modeling and

optimisation of an existing multi-bed scrubber which its main objective is the abatement of toluene

emissions produced in an inkjet dye manufacturing process. Within the reactive dispersants team in the

lab, work involved the concentration and purification of pigment dispersions in a flat sheet ultrafiltration

unit.

Due to the different nature of work developed the thesis will be divided in two parts: Toluene

Emissions Abatement and Concentration/Purification of Pigment Dispersions.

1.3. STATE-OF-THE-ART FOR VOC ABATEMENT AND MEMBRANES

Each year, new federal and state environmental regulations require higher destruction and improved

capture of volatile organic compounds (VOCs). Gas treating in gas industries and in oil and chemical

facilities is getting more complex due to emissions requirements established by environmental regulatory

agencies. Technology must be developed to meet these regulations while providing improvements in both

capital investment and operating costs [3].

The chemical industry as a whole is dedicated and rapidly advancing in their commitment to install

state-of-the-art technology systems for approaching and achieving, in many cases, zero discharge of

VOCs at the facility fence lines. For the destruction of fugitive VOCs, on-site technology in lieu of a

central waste processing facility is required. Maximum VOC destruction without the generation of harmful

by-products is the goal [4].

Currently, various processes are available for VOC abatement, such as thermal or catalytic oxidation,

adsorption, cryogenics, condensation, absorption and biological treatments [5].

For many years, vapor emission abatement has used absorption, adsorption, and incineration.

Membrane separation has recently gained increasing interest and acceptance. The use of gas

membranes in pollution abatement is relatively new [6]. Membrane separation techniques are gaining

increasing interest and acceptance for the recovery of VOCs.

1.3.1. MEMBRANE TECHNOLOGY AND VOCS

In a typical membrane separator, the waste gas stream is fed to an array of membrane modules,

where organic solvents preferentially permeate the membrane. The organics in the permeate stream are

3

then condensed and removed as a liquid for recycle or recovery. The purified gas stream is removed as

the residue. Transport through the membrane is induced by maintaining the vapor pressure on the

permeate (downstream) side of the membrane lower than the vapor pressure on the feed (upstream) side.

In some cases, a vacuum pump is required on the permeate side to maintain this driving force.

A compound permeates the membrane at a rate determined by its permeability in the membrane

material and partial-pressure driving force. In some systems, the feed stream is compressed on the feed

side of the membrane to provide the pressure drop for the membrane and/or to allow operation of the

solvent condenser at a higher temperature. Generally, the permeate is five to 20 times more concentrated

in VOC/HAP than the feed stream.

Membrane modules can be of either hollow-fiber or spiral-wound construction. Membrane separation

systems may have either one stage or multiple stages as necessary to achieve desired recovery

efficiencies. Most membranes are made from synthetic polymers; however, some vendors are considering

inorganic materials, such as ceramics, to deal with more rigorous applications. The membranes are thin,

multilayer films made by coating a microporous support membrane with a very thin, dense film. The

support membrane provides mechanical strength, while the thin film performs the separation. Thinner

films promote higher permeation rates. These membranes are then incorporated into modules that can

withstand temperatures up to 60degC. Membrane life can be as long as three years [7]. Membranes for

solvent vapor separation have to be selective for hydrocarbon vapors versus air. They also have to be

chemically and mechanically stable. The key element of the process is the separation efficiency of the gas

membrane expressed as selectivity towards permeation of VOCs versus air (N2, O2) [6]. Membrane

separations should be considered for low flow, high-concentration waste gas streams, where

condensation or adsorption proves to be either uneconomical or unable to achieve the desired level of

recovery efficiency [7].

Membrane-based separations provide a possible solution, so membranes with good separation

performance to support this technology needs to be developed. There is, however, no general theory

available to allow a suitable membrane to be designed for the removal of each individual VOC in view of

the large number of existing VOCs [8].

Some papers in the literature consider the use of membranes for VOC (including toluene) abatement.

The following paragraphs will describe a brief summary of the most recent membrane techniques.

1.3.1.1. REMOVAL OF VOCS FROM AIR BY MEMBRANE -BASED ABSORPTION AND STRIPPING

An emerging technique involves the use of a nonporous permselective rubbery membrane having a

high selectivity for VOCs. Here, the vapor-laden air is usually at atmospheric pressure and the permeate

side is maintained under vacuum. The feed VOC concentrations are generally low; thus the partial

4

pressure driving force for VOC permeation is small and decreases along the membrane length as the feed

VOC concentration is depleted by permeation.

The proposed scheme for VOC absorption consists in a hollow-fibre membrane unit. Contaminated air

flows in the fibre lumen and a suitable non-volatile and inert absorbent having a high VOC solubility is

pumped countercurrently over the outside of the fibers.

Figure 1. Schematic process diagram for VOC removal from air by absorption and stripping in hollow fiber modules

[9].

The VOCs are removed from N2/air and concentrated in the absorbent. They are removed next from

the spent absorbent which is regenerated by applying vacuum (and/or by heating the spent absorbent).

The solutes and the absorbent can be reused since the latter is essentially nonvolatile. Regeneration of

the Stripping is carried out in a separate hollow-fibre module. Combined absorption-stripping was

achieved here by recycling the absorbent liquid after VOC stripping.

The experiments included a VOC-N2 mixture that consisted in dicloromethane, methanol and toluene.

A microporous hydrophobic hollow-fibre made of polypropilene was used for the absorption. VOCs were

efficiently removed from a nitrogen stream by an inert organic nonvolatile absorbent to potentially very low

levels in a hollow-fiber-based continuous absorption and stripping process. For a given VOC-absorbent

system, combined absorption-stripping achieved somewhat lower gas cleanup level (in terms of gas

stream composition at the absorber outlet) than that for absorption experiments with fresh absorbent.

In such a technique it is uneconomic to bring down the VOC concentration below about 100-200

ppmv.

5

1.3.1.2. PERFORMANCE OF COMMERCIAL -SIZE PLASMAPOLYMERIZED PDMS-COATED HOLLOW FIBER MODULES IN

REMOVING VOCS FROM N2/AIR

This paper focus in membrane devices made out of hollow-fibres containing a thin PDMS coating on

the fibre outside diameter. Each membrane cartridge consisted of a simple shell-and-tube parallel flow

design built with microporous polypropylene hollow fibres having an ultrathin plasma polymerized silicone

skin.

Figure 2. Experimental setup for VOC removal by hollow-fibre vapour permeation membrane process [8].

Each cartridge has around 10,000 fibres providing a membrane area of about 4m2.

The feed gas is allowed to flow through the lumen of the hollow fibres at around atmospheric pressure

while the shell side of the fibres containing the coating was subjected to vacuum.

Removal of toluene vapors from the exhaust N2 stream were demonstrated using three membrane

cartridges in parallel. Inlet toluene vapor concentration was around 2.7% and its removal values were

between 83 and 98 % for a given gas flow rate per cartridge [10].

1.3.1.3. TOLUENE REMOVAL FROM WASTE AIR USING A FLAT COMPOSITE MEMBRANE BIOREACTOR

Biofilters (BFs) and biotrickling filters (BTFs) are the most frequently used biological techniques for

treatment of waste air. In both techniques, air flows through a packed bed of carrier material on which

microorganisms grow as a biofilm. The biofilm is covered by a water layer, forming a barrier between the

microorganisms and hydrophobic compounds in the air phase. In a membrane bioreactor (MBR) for waste

air treatment, the liquid and air phase are separated by a membrane. Pollutants diffuse through the

membrane and are subsequently degraded by the microorganisms in the biofilm. Because of the

separation of the liquid and air phase, waste air containing hydrophobic compounds can be treated

effectively. Oxygen is supplied from the air phase, while nutrients are present in the liquid phase.

6

Biotreatment results in total destruction of the compounds rather than physical transfer of the

contaminant to another medium and it has the potential for low cost implementation [11].

1.4. DYES AND PIGMENTS DISPERSIONS

1.4.1. DYES

The first synthetic dye called Mauveine after its mauve color was obtained in 1856 by Perkin in an

attempt to synthesize quinine. Perkin, with his father and brother, founded the first factory to manufacture

synthetic dyes in Greenford Green, near London, starting the dye and pigment industry. Fuchsine,

nowadays magenta, was first synthesized in 1859 [12].

Many thousands of dyes were synthesized within a few decades due to the advance in structural

organic chemistry. Many of the large chemical plants in operation in Germany and Switzerland today were

built as dye factories in the second half of the 19th century. The manufacture of dyes has spread from

Europe throughout the world; Western Europe still accounts for 40 % of the worldwide total [12]. The

geographical focus of dye production lies in Germany, England, and Switzerland. Far Eastern countries,

such as Japan, Korea, and Taiwan, and Third World countries, such as India (becoming much more

significant), Brazil, and Mexico, also produce dyes.

The introduction of the synthetic fibers, nylon, polyester, and polyacrylonitrile during the period 1930-

1950, produced a challenge to the dyes industry. The discovery of reactive dyes in 1956 heralded a big

breakthrough in the dyeing of cotton; intensive research into reactive dyes followed over the next two

decades and, indeed, is still continuing today.

The scale and growth of the dyes industry is linked to that of the textile industry. World textile

production has grown steadily to an estimated 35 million tons in 1990, being the world production of dyes

1 million tons, a much lower value since 1 t of dye is sufficient to color 16 650 cars or 42 000 suits [13].

There is also considerable activity in dyes for high technology applications, especially for the

electronics and reprographics industries. For example, they are used in photocopying and laser printing, in

ink jet printing and in direct and thermal transfer printing [13].

Dyes are highly colored chemical combinations of carbon and hydrogen with other chemical elements,

such as nitrogen, oxygen, chlorine, iodine, bromine or sulphur. Each dye possesses a certain

configuration, which is said to cause the formation of the intense color. Most of the dyes that are

manufactured are substantially soluble in the medium in which they are used. Those that are insoluble

may qualify as pigments provided they are also insoluble in water [14].

7

Dyes may be classified according to chemical structure or by their usage or application method.

Accordingly to their use or application method dyes can be classified as: reactive, direct, vat, sulphur,

disperse, basic, solvent and acid dyes; and accordingly to their chemical structure: azo, anthraquinone,

benzodifuranone, polycyclic aromatic carbonyl, indigoid, polymethine, phthalocyanines, quinophthalones,

sulphur, nitro and nitroso, The former approach is adopted by practicing dye chemists who use terms such

as azo dyes, anthraquinone dyes, and phthalocyanine dyes [13].

1.4.1.1. MANUFACTURE

The basic steps of dye (and intermediate) manufacture are shown in Figure 3. There are usually

several reaction steps or unit processes.

Figure 3. Basic steps of dye manufacture [13].

The manufacture of the chemical (color paste) and that of the finished product are separate

operations, although the two are often fully integrated. Finishing (or conditioning) changes the physical

form, most simply by drying and grinding; this technology is as important as the chemical synthesis,

especially in the manufacture of water-insoluble dyes. These two classes should be distinguished from

water-soluble dyes at the finishing stage.

Reactants and the reaction medium (water or solvent) are delivered to the reactor using standard

materials handling procedures. The dye industry usually employs a batch process; agitation and mixing

are critical.

Crystallization of the final product requires careful control to obtain the most desirable physical form;

the filtration equipment is chosen accordingly, with a view to both speed and maximum liquid removal.

Drying is usually necessary unless the color paste is to be converted to a liquid product. The water

content of these pastes varies from 20 to 80 %; drying costs vary accordingly.

Particle size is reduced by grinding or milling. Dry grinding is usually carried out in impact mills

equipped to control dust [12].

8

1.4.2. PIGMENT DISPERSIONS

A pigment may be defined generally as an intensely colored, black, white, or translucent substance,

which is essentially insoluble in water and in the medium in which it is applied. It is used to impart a

desirable colour and/or other physical properties such as bulk, opacity or translucency, viscosity, printing

qualities [14].

Many organic pigments and dyes have the same basic chemical structure. The insolubility required in

pigments can be obtained by excluding solubilizing groups, by forming insoluble salts of carboxylic or

sulfonic acids, by metal-complex formation in compounds without solubilizing groups, and particularly by

incorporating groups that reduce solubility [13].

Pigments alter appearance either by selective absorption and/or scattering of light. They are usually

incorporated by dispersion in a variety of systems and retain their crystal or particulate nature throughout

the pigmentation process.

Dyes, on the other hand, are colored substances which are soluble or go into solution during the

application process and impart color by selective absorption of light. In contrast to dyes, whose coloristic

properties are almost exclusively defined by their chemical structure, the properties of pigments also

depend on the physical characteristics of its particles.

Pigments can be classified according to their chemical origin (organic and inorganic). The organic

pigments are either dyes or derived from them by some chemical treatment, whereas inorganic pigments

are not derived from dyes.

Organic and inorganic pigment powders are finely divided crystalline solids that are essentially

insoluble in application media such as ink or paint. The carrier used for dispersion of a pigment is usually

a liquid or solid that is deformable at the processing conditions of high temperature and/or shear. The

color strength of the dispersed pigment increases markedly with decrease in particle size. Optimum color

strength from a given pigment in practice requires a mean particle size of the order of 0.1 mm or less,

which is half the wavelength of the light involved. Therefore, the dispersion process involves size

reduction of the pigment particle to the smallest practical size, reasonably complete wetting of its solid

surfaces by the carrier, and stabilization of the resulting dispersion.

Because the intensity and colour strength of pigments are largely dependent on the exposed surface,

it is desirable to reduce the particles to primary particle size. This is the size of the solid pigment crystals

as they are precipitated in their synthesis. In practice, the size reduction processes are limited by the

nature of pigment, dispersion system, constraints of the processing equipment, the requirements imposed

9

by the product application, and the overall economics. The maximum aggregate size permissible in a

given dispersion system depends on the thickness of the film or the coating [13].

Occasionally large agglomerates, several millimetres in diameter, form during the initial stages of

dispersion in a highly viscous system. The commercial processes used in dispersion manufacturing may

not fully eliminate the aggregates. However, the design and operation of pigment dispersion equipment is

aimed at application of mechanical forces to break down the agglomerates and even some less tightly

held aggregates. Ideally, an excellent dispersion should consist mainly of primary pigment particles and

few loosely held aggregates [13].

10

TOLUENE EMISSIONS ABATEMENT

1. INTRODUCTION ____________________________________________

Volatile Organic Compounds (VOCs) are a group of chemicals that contain organic carbon, and

readily evaporate changing from liquids to gases when exposed to air. VOCs are emitted as gases from

certain solids or liquids through the volatilization of organic compounds at the liquid surface. VOCs are

generated by power plants, municipal waste combustors, motor vehicles, solvent use, and the chemical

and food industries. They can also be generated by natural sources such as forests. In the present case

the emissions come from ink manufacturing operations, being VOCs formed during manufacturing and

solvents handling. They are a function of displacement (e.g., charging, transfer), heating, gas sweep (e.g.,

convective drying, inerting) and vacuum drying operations during manufacturing. VOCs include a variety

of chemicals, some of which may have short- and long-term adverse health effects.

1.1. ENVIRONMENTAL REGULATIONS

SEPA (Scottish Environment Protection Agency) is Scotland’s environmental regulator. SEPA is

tasked with applying a wide range of legislation and seeks to achieve good air quality in line with the aims

of the European initiative, Clean Air for Europe, to protect against significant negative effects of air

pollution on human health and the environment. SEPA’s role is to monitor and regulate industry to reduce

pollutants [15].

The Environment Agency’s Horizontal Guidance (H1) provides a structured methodology to

demonstrate that an activity uses the Best Available Techniques (BAT) by [16]:

• Conducting an environmental assessment to demonstrate that no significant pollution is caused;

• Assessing the costs and environmental benefits of options for pollution prevention and control

techniques.

The predicted Process Contributions (PC) of all pollutants released to air are compared to the

Environmental Benchmarks to determine whether the emission rate is insignificant [16].

Accordingly to the screening process for long-term emissions, emissions are considered insignificant if

[16]:

11

PClong-term ≤ 1% EALlong-term (Environmental Assessment Level) (or EQSlong-term, Environmental Quality

Standards)

For short term emissions the rule is:

PCshort-term ≤ 10% EALshort-term (or EQSshort-term)

1.1.1. TOLUENE EMISSIONS

For toluene the appraisal methodology in the horizontal guidance note (H1 screening) for peak (short

term) process contributions (<10% of the EAL, Environmental Assessment Levels) and long term process

contributions (<1% of EAL) at ground level equate to maximums of 0.738 kg/h and 4069 kg/annum

respectively.

The regulator can also apply solvent emission directive benchmarks with mass and concentration

rates of 0.1 kg/h and 20 mg/m3 for Class A VOCs or 2 kg C/h and 75 mg C/m3 for Class B VOCs

(emissions at the point source, vent outlet). Toluene was originally classified as a class B VOC according

to IPPC (Integrated Pollution Prevention and Control) S4.02 guidance document [17], however, recent

CHIP (Control of Hazardous Information and Packaging Regulations) risk phrase changes for toluene

include “R63:category 3 repro”1 , which would reclassify toluene as a class A VOC [18].

1.2. VOC CONTROL SYSTEMS

A VOC control system typically consists of a capture device and a removal device. The capture

device (such as a hood or enclosure) captures the VOC-laden air from the emission area and ducts the

exhaust air stream to removal equipment such as a recovery device or a destructive control device. In

either case, the purpose of the control system is to remove VOCs from the exhaust air stream. The

overall efficiency of a control system is a function of the specific removal efficiency for each device in the

system.

Example of recovery devices [19]:

• Condensers are one of the most frequently used control devices in industry. They work by

reducing the temperature of the emission exhaust gas so that VOC vapors are recovered through

condensation.

1R63 (risk phrase): Possible risk of harm to the unborn child

Category 3 repro: category 3 reproductive toxins

12

• Adsorption Devices that incorporate activated carbon are capable of removing VOC vapors from

exhaust emission streams to very low levels in the final gas stream.

• Dust collectors are used to collect particulate matter from the emission stream.

• A floating roof on a storage tank helps to reduce solvent emissions by eliminating the headspace

that is present in conventional storage tanks.

Example of destructive control devices [19]:

• Venturi Scrubbers are used to remove particulate material from vent exhaust streams. These

units normally incorporate a spray nozzle section where liquid is discharged at a high velocity, a

mixing section where liquid droplets contact the incoming emission gas stream and a

settling/separation section where scrubber fluid is recycled to the inlet spray nozzle and the exit

gas is discharged to the atmosphere or to a secondary control device.

In Packed-bed scrubbers the gas stream is forced to follow a circuitous path through the packing

material. The liquid on the packing material collects the VOC and flows down the chamber

towards the drain at the bottom of the tower. A mist eliminator (also called a “de-mister”) is

typically positioned above/after the packing and scrubbing liquid supply. Any scrubbing liquid and

wetted VOC entrained in the exiting gas stream will be removed by the mist eliminator and

returned to drain through the packed bed.

• Catalytic Incinerators are used to eliminate VOCs from process exhaust gases. The catalyst

section operates at between 315°C to 400°C to conve rt VOC to CO2 and H2O.

• Thermal Incinerators control VOC levels in a gas stream by passing the stream through a

combustion chamber where the VOCs are burned in air at temperatures between 700°C to

1,300°C. Fuel is burned in the unit to supply the necessary heat for decomposition of the VOC’s.

• Enclosed Oxidizing Flares convert VOCs into CO2 and H2O by way of direct combustion.

Toluene emissions released from the process will be subjected to gas treatment in a multi-bed

scrubber consisting of a recirculation first scrubber and a continuous second scrubber. First scrubber has

a venturi scrubber at the gas main entrance, however, this was not considered for the calculations. A

model is proposed to calculate the scrubbers efficiency using gas absorption theory and the ONDA

method. Gas absorption theory as well as a brief description of the scrubbers is shown in section 2 and 3

respectively.

13

1.3. BASIC AIR EMISSION MODELS

Processes for manufacturing paint and ink, consist of different unit operations including filling, mixing,

dispersing, milling, and others. A mathematical approach to estimating air emissions from these types of

processes is to model them as a collection of separate unit operations. For example, the filling model can

be used to estimate the emissions from charging the primary raw materials or transferring the batch from

one vessel to a second vessel. The heating model can be used to model dispersion operations and the

evaporation model can be used to calculate the losses from open roll milling [20].

In this report, toluene emissions were calculated using EPA (Environmental Protection Agency)

equations (section 3.1.1).

Toluene is emitted from a Fujifilm crystallization process (section 3.1.) by several ways:

• Material loading - vapour displacement due to transfer of material into or out of a vessel

• Purging of filled vessels (Gas sweep)

• Heating of vessels

• Nitrogen drying of isolated solid.

1.4. SUPERPRO DESIGNER

Calculations will be compared with a chemical engineering simulation program, SuperPro Designer

from Intelligen. SuperPro Designer is a tool for engineers and scientists in process development, process

engineering, and manufacturing that facilitate modeling, evaluation and optimisation of integrated

processes. It includes an extensive chemical component and mixture database and extensive equipment

and resource databases. It is also a valuable tool for professionals dealing with environmental issues

(e.g., wastewater treatment, air pollution control, waste minimization, pollution prevention) [21].

SuperPro Designer estimates emissions of regulated and other compounds from manufacturing

operations (primary emissions). It performs VOC emissions calculations for several batch operations that

are common in the specialty chemical industries. The VOC emission models are based on EPA guidelines

and are available for the following operations: displacement (i.e. charge, transfer in), evacuation/

depressuring, gas sweep, heating gas evolution, operation under vacuum, drying [21].

The design and simulation program include a variety of unit operations models for evaluating

treatment and purification of air and gaseous streams in general. Including unit operations as well as units

(e.g., condenser, scrubber, etc) for removing vapors of organic and other compounds [21].

14

2. THEORY __________________________________________________

2.1. GAS ABSORPTION

Absorption is a unit operation used in the chemical industry to separate gases by washing or

scrubbing a gas mixture with a suitable liquid. One or more of the constituents of the gas mixture are

absorbed in the liquid and can thus be removed from the mixture. In air pollution control, absorption

involves the removal of specific gaseous pollutants from a process stream by dissolving them into a liquid.

Absorption can be physical or chemical whenever the absorbed compound dissolves in the liquid or

reacts with it, respectively. Toluene absorption is physical.

Absorption is a mass-transfer operation. In any absorption process, possible removal efficiency is

controlled by the concentration gradient of the pollutant being treated between the gas and the liquid

phases. This concentration gradient is the driving force to mass transfer between phases. Therefore, the

solubility of the given pollutant in the gas and liquid phases will determine the equilibrium concentration of

the pollutant in the given example.

2.1.1. SOLUBILITY

Solubility is the factor that affects the amount of a pollutant, or solute, that can be absorbed and it’s a

function of both the temperature and the pressure of the system. Solubility data are obtained at

equilibrium conditions. If equilibrium were to be reached in the actual operation of an absorption tower, the

efficiency would fall to zero at that point since no net mass transfer could occur. The equilibrium

concentration, therefore, limits the amount of solute that can be removed by absorption. Solubility data are

analyzed by an equilibrium diagram that plots the mole fraction of solute in the liquid phase, denoted as x,

versus the mole fraction of solute in the gas phase, denoted as y. For low concentrations of a non-reacting

solute in the liquid phase, where a simple solution is formed, Henry’s Law applies:

p*= Hx (1)

Dividing both sides of Equation (1) by the total pressure of the system we obtain:

ye = H’x (2)

This is the equation of a straight line, where the slope (m) is equal to H’. Henry’s law can be used to

predict solubility only when the equilibrium line is straight. Equilibrium lines are usually straight when the

15

solute concentrations are very dilute. In air pollution control applications, this is usually the case as it is in

the present case for toluene.

If a pollutant is readily soluble in the scrubbing liquor, the slope m of the equilibrium curve is low. An

inverse relationship exists between m and driving force, the smaller the slope, the more readily the

pollutant will dissolve into the scrubbing liquor. If the slope is relatively large, 50 or more, this represents

limited solubility of pollutant in scrubbing liquor [22]. For absorption to occur with limited driving force, a

high liquid-to-gas ratio requirement is indicated if high removal efficiency of the pollutant is desired. As

indicated by reference [22] if m>50, a removal efficiency of the pollutant of 99% will most likely not be

practical.

2.1.2. EQUATIONS

The height of a packed column refers to the depth of packing material needed to accomplish the

required removal efficiency [23]. Where the concentration of the solute is small, the flow of gas and liquid

will be essentially constant throughout the column, and the height of packing required, Z, is given by [24]:

∫ −=

1

2

y

yeG

m

yy

dy

aPK

GZ (3)

in terms of the overall gas phase mass transfer coefficient KG and the gas composition. Or,

∫ −=

1

2

x

xetL

m

xx

dx

aCK

LZ (4)

in terms of the overall liquid phase mass transfer coefficient KL and the liquid composition.

The relation between the equilibrium concentrations and actual bulk concentrations is shown in Figure

5.

16

Figure 4. Gas absorption concentration relationships [24].

The group ( )∫ − eyydy , in Equation (3) has been defined by Chilton and Colburn as the number of

overall gas transfer units NOG. The number of overall gas transfer units is an integrated value of the

change in composition per unit driving force and expresses the difficulty of absorbing the solute from the

gas. The group in front of the integral sign is the height of a transfer unit, HOG.

Equation (3) can be written as:

OGOG NHZ = (5)

Problems involving stripping or desorption operations are handled most conveniently by calculating

NOL and HOL rather than NOG and HOG.

In the transfer unit concept there is a clear separation between the number of transfer units (NOG),

which is based on driving forces, and the height of a transfer unit (HOG), which represents the rate of mass

transfer. The specification for the amount of solute transferred from the gas phase determines the number

of transfer units required; the height of a transfer unit depends mainly on the choice of tower packing.

The relationship between the overall height of a transfer unit and the individual film transfer units HL

and HG, which are based on the concentration driving force across the liquid and gas films, is given by:

Lm

mGOG H

L

GmHH += (6)

where m is the slope of the equilibrium line and Gm/Lm the slope of the operating line.

17

The number of transfer units is obtained by graphical or numerical integration of equation of the group

( )∫ − eyydy in Equation (3). The true mean driving force is the logarithmic mean when both equilibrium

and operating lines are straight, and they can usually be considered to be so for dilute systems. For this

case, therefore,

( )lmeOG yy

yyN

−−= 21 (7)

This equation may be combined with the equilibrium relation ye = mx (for dilute concentrations Henry’s

law holds) and the material balance expression:

( ) ( )yyGxxL MM −=− 11 (8)

to eliminate the need for values of ye. The resulting equation which was proposed by Colburn is given

below:

( )MM

M

M

M

M

OG LmG

L

mG

mxy

mxy

L

mG

N−

+

−−

−

=1

1ln22

21

(9)

2.1.3.1. PREDICTION OF THE HEIGHT OF A TRANSFER UNIT

The height of a gas-film transfer unit and the height of a liquid-film transfer unit are given by,

respectively:

Pak

GH

wG

MG = (10)

twL

ML Cak

LH = (11)

Many correlations have been published for predicting the height of a transfer unit, and the mass-

transfer coefficients. Among existing correlations, the Onda et al. work can be described as the first and

still widely used, procedure for packed tower design in regard to mass-transfer coefficient predictions [25].

18

2.1.3.2. ONDA’S METHOD

Onda et al. published correlations for the film mass-transfer coefficients kG and kL and the effective

wetted area of the packing aW, which can be used to calculate HG and HL. Their correlations were based

on a large amount of data on gas absorption and distillation; with a variety of packings, which included

Pall Rings and Berl saddles [24].

The equation for the effective area is:

−−=

− 2.0205.0

2

21.075.0

45.1exp1a

L

g

aL

a

L

a

a

LL

m

L

m

L

m

L

cw

σρρµσσ

(12)

−−= − 2.005.01.0

75.0

Re45.1exp1 WeFra

a

L

cw

σσ

(13)

And for the mass coefficients:

( ) 4.0213231

0051.0 pLL

L

Lw

m

L

LL ad

Da

L

gk

−

=

ρµ

µµρ

(14)

( ) 0.2317.0

5−

= p

vv

v

v

m

v

G adDa

GK

aD

k

ρµ

µ

(15)

19

3. EXPERIMENTAL ___________________________________________

Toluene emissions abatement work includes:

1. Determine potential toluene emissions from the process (using EPA equations).

2. Compare these emissions against an existing simulation model (SuperPro Designer) used to

assess recent emission calculation changes to the simulation software.

3. Develop a model which allows to determine the removal effectiveness of the existing water based

scrubber for toluene.

3.1. PROCESS

Toluene emissions derive from a Fujifilm process involving a crystallization step described below.

Table 1. Reagents used in the process

MATERIALS Act Wt (kg) Str % 100% wt (kg) Density (kg/m 3) Volume (m 3)

Intermediate paste 1855 90 1669 1500 1.11 Toluene 2164 100 2164 865 2.50

Methanol 1. 4745 100 4745 791 6.00 Methanol 2 1582 100 1582 791 2.00

• Crystallization of Intermediate paste (20m3)

Start the agitator and charge toluene (4329 kg) into reaction vessel A. Charge the intermediate paste

(1669 kg @ 100 % wt) over a minimum of 2 hours. Heat the contents to 55 to 60 °C and hold at 55 to 60

°C for four hours. Whilst maintaining the temperature at 55 to 60 °C, add methanol (Methanol 1) over two

hours.

• Isolation and Water Wash of Intermediate

Pre-heat vessel B to 40 °C and transfer in contents vessel A using methanol (Methanol 2, 600 liters)

as a follow through wash. Cool batch to 5 to 20 °C. Material is then passed to the filter for isolation and

nitrogen drying. Nitrogen drying was not considered as the emissions are sent to a different scrubber from

that being evaluated.

20

3.1.1. PROCESS EMISSIONS

Toluene emissions prior to filtration are a function of the following process operations [19]:

Material Loading Emissions: VOC emissions may occur during material loading of mixing and

grinding equipment due to the displacement of organic vapors. VOCs may be emitted from a mixing tank

when the device is uncovered or when a lid is open. For certain grinding equipment, VOCs may be

released from the chute through which ingredients are added.

Heat-up Losses: Heat-up losses occur during the operation of high-speed dispersers, ball and pebble

mills and from heating the components in the vessel. During the grinding/dispersing process, there is a

rise in temperature as some of the kinetic mixing energy is converted to thermal energy. This rise in

temperature in many cases is controlled through the use of cold water jackets on the process vessel. As

the VOCs in the mixers heat up, the vapor in the headspace expands and leads to solvent emissions from

the equipment. Emissions that escape the process equipment through loose fittings or duct connections

and enter the room air are considered to be fugitive emissions. Emissions that exit the process equipment

through the vent duct to the emissions handling system are considered to be process emissions.

Purge or Gas Sweep: Air or another noncondensable gas is emitted into the vessel at a controlled

rate. The discharge vapors from the vessel during this operation are normally assumed to be at

equilibrium or saturated with the vessel's liquid contents within certain flow rate criteria. Further, it is

assumed that the inlet purge rate is known.

21

The amount of the VOC compound emitted during the listed operations is calculated using the

following EPA equations:

Table 2. VOCs emissions equations [19].

OPERATION EQUATIONS

A. MATERIAL LOADING

(kg/episode) riii

episode VRT

MWxpE

⋅⋅= (16)

B. PURGING OF FILLED

VESSELS (GAS SWEEP)

(mol/episode)

inert

jjj

iiepisode n

pxP

xpE

∑ ⋅−

⋅=

(17)

C. HEATING OF VESSELS *

( )( )

( )( )

−+

−=

∑∑j

Tjj

iTi

jTjj

iTiinertepisode

pxP

xp

pxP

xpnE

2

2

1

1

212

(mol/episode) (18)

−=

2

22,

1

11,1

T

PaV

T

PaV

Rn

rrinert (19)

( )

( )∑

∑

−=

−=

jTij

jTij

pxPPa

pxPPa

2

1

22

11

(20)

(21)

* calculation method in Appendix, A.1. Where episode equates to a single batch.

Regarding the previous process description, only the steps where toluene emissions arise were

considered (in parenthesis is the respective operation from Table 2.).

Table 3. Toluene emissions during processing

Operation Time (h)

1 Charge toluene (A) 0.64

2 Gas Sweep 1 (B) 0.64

3 Charge Intermediate paste (A) 2.55

4 Gas sweep 2 (B) 2.55

5 Heating 1 (C) 0.58

6 Charge methanol (A) 0.9

7 Gas sweep 3 (B) 0.9

8 Heating 2 (C) 2

9 Transfer batch (A) 1.2

10 Transfer line wash (A) 0.1

Note that: Gas sweep operations occur concurrently with charging operations for safety reasons

22

3.2. TOLUENE ABATEMENT EQUIPMENT

Gas absorption is usually carried out in vertical countercurrent columns. The solvent is fed in at the

top of the absorber and the gas mixture from the bottom. The absorber may be a packed column, plate

tower, spray column or a bubble column. Packed-bed scrubbers consist of a chamber containing layers of

variously-shaped packing material, such as Raschig rings, spiral rings, or Berl saddles, that provide a

large surface area for liquid-gas contact. The packing is held in place by wire mesh retainers and

supported by a plate near the bottom of the scrubber. Scrubbing liquid is evenly introduced above the

packing and flows down through the bed. The liquid coats the packing and establishes a thin film. The

pollutant to be absorbed must be soluble in the fluid. In vertical designs, the gas stream flows up the

chamber (countercurrent to the liquid) [26]. A venturi scrubber is designed to effectively use the energy

from the inlet gas stream to atomize the liquid being used to scrub the gas stream.

For the toluene case, the gas is feed into a venturi mixing with water and the mixture is then re-

circulated around a packed bed. Any solvent in the gas stream not absorbed or desorbed due to inert gas

passing through the liquid will be passed through a second packed bed operating on a continuous basis.

Recirculation tank

Packing suport grid

Packing media

Mist eliminator

Scrubber inlet

Liquid distribution nozzle system

Outlet from the scrubber

Figure 5. Schematic diagram of a venturi (on the left) [27] and a packed tower scrubber (on the right) [28].

23

3.2.1. SCRUBBERS DESCRIPTION - MODELLING

The main multi-bed scrubber (see Figure 6) is made up of a recirculation first scrubber (bottom tier)

and a continuous second scrubber (top tier). This report considers the abatement effectiveness of the

scrubber system for toluene removal. The scrubber vent header leading to the scrubber is purged with a

constant flow of Nitrogen (120 m3/h) for safety reasons. Nitrogen will therefore dilute any toluene emitted

from the process as it reaches the scrubber.

Toluene emitted will be partially absorbed by water in the venturi, which is then re-circulated to the

first scrubber, and unabsorbed toluene exits to the second scrubber along with nitrogen. This stream

enters the second scrubber where the same thing happens without any recirculation and accumulation.

The recirculation scrubber works with a water flow rate of 12 m3/h and the second scrubber with a water

flow rate of 8 m3/h.

Gas out (y2')

Liq in (x2')

Liq out (x1')

Nitrogen

Toluene

Water

Toluene

Water

Toluene

Water

Nitrogen

Toluene

Nitrogen

Toluene

x: mol fraction of toluene in liquidy: mol fraction of toluene in gas

Figure 6. Scrubber Schematics.

24

Due to the recirculation in the first scrubber, some equations have to be modified to take into account

any toluene accumulated.

For the liquid re-circulating around the bottom packed bed (base):

tOHintt

mixin bottomliqtoluenenn .2 +=∆+

(22)

tttxx 12 =

∆+ (23)

The initial conditions (t=0) for equations (22) and (23) are respectively: nin mix = nin H2O and x2 = 0.

For the liquid exiting the bottom of the scrubber:

t bottomliqtoluenenE

bottomliqtoluene in toluenett .100

. +⋅=∆+ (24)

bottomoutliqtoluenen

bottomoutliqtoluenex

mixin .

.

1 +

= (25)

In the initial conditions (t=0) for equation (24), the parameter toluene liq. bottom equals to zero.

A model was developed to determine how the toluene absorption within the multi-bed scrubber varies

with time. The calculations were made accordingly with the theory shown in section 2 (ONDA’s method)

and using the following equations for the mole fraction of toluene exiting the scrubbers and for scrubber

efficiency, respectively:

( )

( )[ ]2

21

2

1exp

1

mx

L

mGNLmG

L

mGmxy

y

M

MOGMM

M

M

+−⋅−

−⋅−

= (26)

−⋅=

1

21100(%) y

yEfficiency (27)

25

Equations (26) and (27) are for the bottom tier. Equations for the top tier are similar considering y2, x1’,

x2’ and y2’ instead of y1, x1, x2 and y2 respectively\.

Equation (26) is equation (9) in section 2 for the number of transfer units, rearranged for the mole

fraction of solute in the gas phase exiting the scrubber. The number of transfer units (NOG) is calculated

using equation (5), being HOG from this equation calculated using equation (6).

Calculations for the scrubbers efficiency among other calculations involved the following calculation

method:

1. Using equations (12), (14) and (15), the effective area (aw) and mass coefficients for the liquid and

gas phase respectively (kG and kL) can be determined.

2. The height of a transfer unit for the gas and liquid phase (HG and HL respectively) are calculated

with the values of the effective area and mass coefficients calculated previously and using

equations (10) and (11) respectively.

3. The overall height of a transfer unit for the gas phase (HOG) is calculated using equation (6) and

the number of transfer units (NOG) is calculated using equation (5). Column height is known

(Appendix, table A.21).

4. The amount of toluene that wasn’t absorbed by the water (y2) in the recirculation scrubber is

calculated using equation (26) (see Figure 6). The values of x2 from equation (26) are calculated

using equation (23) and (25). For the second scrubber y2’ is calculated with the same equation,

using y2 and x2’ instead of y1 and x2 respectively. Here, x2’ equals zero.

5. The recirculation scrubber efficiency is calculated using equation (27). Calculation method for the

second scrubber efficiency is similar to the one for the recirculation scrubber considering y2’ and

y2 instead of y2 and y1 in equation (27) respectively (see Figure 6).

6. Overall efficiency is calculated with equation (27) using y2’ instead of y2.

7. The amount of toluene in the liquid phase (x1 for the recirculation scrubber and x1’ for the second

scrubber) is known doing a mass balance to the scrubber.

The values of the constants used in the previous equations can be found in Appendix, tables A.21,

A.22, A.24 and A.25. Values for the flow rate of liquid and gas per unit area (Lm and Gm respectively) can

be found in Appendix, tables A.3, A.4, A.5 and A.6.

26

4. RESULTS AND DISCUSSION _________________________________

4.1. PROCESS EMISSIONS RESULTS

Toluene emissions prior to any chilled condensation at the reactor (not considered) and scrubber

abatement applied (worse scenario) are tabulated below (see table 4). The calculations were compared

with SPD ones.

Table 4. Toluene emissions from process (before condensation & abatement)

Operation Time (h)

Emissions (kg/h)

Excel

spreadsheet SPD Model

1 Charge toluene 0.64 0.36 0.38

2 Gas Sweep 1 0.64 1.20 0.97

3 Charge Intermediate paste 2.55 0.06 0.07

4 Gas sweep 2 2.55 0.53 0.47

5 Heating 1 0.61 2.14 2.20

6 Charge methanol 0.9 0.19 0.14

7 Gas sweep 3 0.9 0.44 0.35

8 Heating 2 2 0.23 0.23

9 Transfer batch 1.2 0.60 0.70

10 Transfer line wash 0.1 0.22 0.28

As we can see by the previous table highest emissions are from the vessel first heating. Due to the

heating effect toluene vapors are formed in a larger quantity. The temperature at which the vessel is

heated has an important effect on the toluene emissions, a temperature of 50ºC instead of the 55ºC would

lead to a value of 1.5 kg/h in the Heating 1 operation. This effect can also be observed in the gas sweep

calculations. If the second gas sweep were conducted at the same time as the first heating and

considering a temperature of 55ºC instead of the 20ºC we would have a value of 3 kg/h of toluene

emissions instead of the 0.53 kg/h.

The results from SPD are in close agreement with those from the Excel spreadsheet (model) and

small discrepancies can be due to small differences in some of the parameters used by SPD to do the

calculations.

27

4.2. SCRUBBERS MODELLING RESULTS

The results for the scrubbers calculations modeling are shown from Figure 7 to 14. Tables with the

respective values as well as scrubber entering stream values can be found in Appendix, A.2.

-120

-100

-80

-60

-40

-20

0

20

40

60

80

100

0 1 2 3 4 5 6 7 8 9 10

t (h)

Firs

t Scr

ubbe

r Eff

icie

ncy

(%)

Figure 7. First scrubber efficiency variation with time (negative absorption efficiency values are due to stripping).

The plot from Figure 7 shows us that the first scrubber switches between absorption and stripping

depending on the amount of toluene in the feed gas and toluene already accumulated. Stripping effect

occurs when some of the toluene absorbed by the water (x2, Figure 6) goes to the gas phase (y2). If this

amount is higher than the toluene coming in (y1) the efficiency will be negative.

As we can see by Figure 7 the maximum toluene removal efficiency for the first scrubber is about 50%

and as the concentration of toluene in the gas stream decreases (table A.2., Appendix), the absorption

driving force reduces and stripping takes effect (Figure 8). In order to improve absorption efficiency in very

dilute systems, where m = Henry’s constant = 258, increasing the flow rate of liquid in the continuous

packed bed or reducing the inert gas flow to the scrubber are the best options. The latter is not feasible

due to safety requirements. This is discussed later.

28

0.0E+00

1.0E-03

2.0E-03

3.0E-03

4.0E-03

5.0E-03

6.0E-03

0.0E+00 2.5E-06 5.0E-06 7.5E-06 1.0E-05 1.3E-05 1.5E-05 1.8E-05 2.0E-05

x (molar fraction in the liquid phase)

y (molar fraction in the gas phase)

t=0

t=1

t=2

t=3

t=4

t=5

t=6

t=7

t=8

t=9

t=10

Time (h):

Figure 8. Operating lines of the first scrubber system.

The previous figure is for the actual toluene-water system (modeling results). When the operating

lines are below the equilibrium line it means that some of the toluene that is in the liquid phase in the

recirculation stream is passing to the gas phase (stripping).

0.0E+00

5.0E-05

1.0E-04

1.5E-04

2.0E-04

2.5E-04

3.0E-04

3.5E-04

4.0E-04

4.5E-04

5.0E-04

0 1 2 3 4 5 6 7 8 9 10t (h)

g T

olue

ne/g

H2O

bott

om fi

rst s

crub

ber

Figure 9. Variation with time of toluene in the liquid phase in the first scrubber (red line indicates toluene solubility in

water at 20ºC).

Equilibrium line

Operating lines

29

Analyzing Figure 9 one can see that the amount of toluene being absorbed (liquid phase) is not

increasing, despite the recirculation, due to the negative efficiency (amount of gas exiting the column, y2,

is higher than what is coming in, y1, due to stripping).

0

10

20

30

40

50

60

70

80

90

100

0 1 2 3 4 5 6 7 8 9 10t (h)

Sec

ond

Scr

ubbe

r Eff

icie

ncy

(%)

Figure 10. Second scrubber efficiency variation with time.

For the efficiency in the second scrubber, Figure 10, one can see that it practically remains constant

at approximately 34% as there is no recirculation, being a once-through scrubbing. The efficiency in the

second scrubber is lower due to the lower L/G ratio, as the liquid flow rate is lower (8 m3/h instead of 12

m3/h).

0.0E+00

5.0E-05

1.0E-04

1.5E-04

2.0E-04

2.5E-04

3.0E-04

3.5E-04

4.0E-04

4.5E-04

5.0E-04

0 1 2 3 4 5 6 7 8 9 10

t (h)

g T

olue

ne/g

H2O

bo

ttom

sec

ond

scru

bber

Figure 11. Variation with time of toluene in the liquid phase in the second scrubber (red line indicates toluene solubility

in water at 20 ºC).

30

The amount of toluene being absorbed also remains approximately constant at around 1/10th of the

maximum solubility (because of the constant efficiency). The difference between the solubility value for

toluene in water at 20 ºC ( ≈ 0.0005 g/g) and the results obtained show us that there is no phase

separation between toluene and water. However, its behavior is like that of a saturated solution despite

being at 1/10th of the max solubility.

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

0 1 2 3 4 5 6 7 8 9 10t (h)

Tol

uene

em

issi

ons

(mg/

m3 )

se

cond

scr

ubbe

r

Figure 12. Toluene emissions variation with time (mg/m3).

Analyzing Figure 12 one can see that the concentration rate of emissions exiting the scrubber will be

above the benchmark guidance. The latter is due to the very low carrier gas flow compared to other

chemical installation scrubbers, where the volumetric flow of carrier gas (air) through a scrubber used to

provide through-pan draughting is typically 10-500 times higher than the carrier gas (nitrogen) flow

through the existing scrubber. This is because the existing plant is fully enclosed & nitrogen-blanketed –

where it is important to exclude air (safety) & to minimize nitrogen usage (due to cost, environmental & N2

supply limitations). As a result, the very small mass flows of toluene leaving the scrubber result in

disproportionately high outlet concentrations.

31

0

0.2

0.4

0.6

0.8

1

1.2

0 1 2 3 4 5 6 7 8 9 10t (h)

Tol

uene

em

issi

ons

(kg/

h)se

cond

scr

ubbe

r

Figure 13. Toluene emissions variation with time (kg/h).

Toluene emissions are directly related with the amount of toluene that is being released in the gas

phase by the first scrubber and with the efficiency in the second scrubber, as was expected. Emissions

are higher for higher amounts of toluene coming in and for lower efficiencies. Analyzing Figure 13 one can

see that the environmental limits for toluene emissions without further abatement measures (e.g., chilled

condensation) will on occasions exceed the maximum short term rate.

-65

-50

-35

-20

-5

10

25

40

55

70

85

100

0 1 2 3 4 5 6 7 8 9 10

t (h)

Ove

rall

Eff

icie

ncy

(%)

Figure 14. Overall efficiency variation with time.

Overall efficiency, Figure 14, has a minimum value of about 30% (without taking into account the

negative values) and a maximum of 67%. The reason for such low values is due to the limitation of

toluene solubility in water. In reference [29] the value of 30% was found for toluene removal efficiency in a

32

wet scrubber. The fluctuations observed in Figure 14 are due to the stripping effect in the recirculation

scrubber.

4.2.1. SCRUBBERS ANALYSIS

Industry standard calculations (as described in section 3.2.1) were used to determine the amount of

toluene that would be emitted over time. Calculations were then made to understand the sensitivity of the

model to the changes in liquid, inert gas and toluene concentrations.

Two toluene flow rates scenarios entering the recirculation scrubber were considered; 10 kg/batch

and 50 kg/batch on a 12h batch simulation analysis (0.833 kg/h and 4.16 kg/h respectively). Due the high

Henry’s constant (m=258), the scrubber efficiency is likely to be function of the G/L ratio, therefore, a

range of gas and liquid flow rates were assessed to understand the sensitivity within the model. For

Nitrogen, since the normal flow rate is 120 m3/h, calculations were carried out with a range of lower (20

and 60 m3/h) and higher values (200, 250, 300, 400, 500, 700, 1000 and 10000 m3/h). Liquid flow rates of

10, 15, 20 and 25 m3/h were carried out for the continuous bed. The results are shown from Figure 15 to

23. Tables with the respective values can be found in Appendix, A.2.

Calculation method is in agreement with the one shown in section 3.2.1. where Lm and Gm adopt the

selected values.

• Efficiency versus time

- Bottom (recirculation) Scrubber (H 2O=12 m3/h)

0

10

20

30

40

50

60

70

80

90

100

0 1 2 3 4 5 6 7 8 9 10 11 12t (h)

Firs

t Scr

ubbe

r Eff

icie

ncy

(%)

0

10

20

30

40

50

60

70

80

90

100

0 1 2 3 4 5 6 7 8 9 10 11 12t (h)

Firs

t Scr

ubbe

r Eff

icie

ncy

(%)

Figure 15. Comparison between first scrubber efficiency variation with time for toluene constant flow rate of 0.833 kg/h

(on the left) and 4.16 kg/h (on the right). Calculations were made for several nitrogen flow rates.

N2 flow rates (m3/h)

Toluene flow rate: 0.833 kg/h (Entering first scrubber)


33

- Top (continous) Scrubber (H 2O=8 m3/h)

010

20

30

4050

60

70

80

90

100

0 1 2 3 4 5 6 7 8 9 10 11 12t (h)

Sec

ond

Scr

ubbe

r Eff

icie

ncy

(%)

010

203040

50

60708090

100

0 1 2 3 4 5 6 7 8 9 10 11 12t (h)

Sec

ond

Scr

ubbe

r Eff

icie

ncy

(%)

Figure 16. Comparison between second scrubber efficiency variation with time for first scrubber toluene constant flow

rate of 0.833 kg/h (on the left) and 4.16 kg/h (on the right). Calculations were made for several nitrogen flow rates.

Analyzing Figure 15 and 16 we see that the amount of toluene coming in doesn’t affect efficiency

values within both scrubbers at the various nitrogen flow rates. In agreement, with that discussed earlier

for very dilute systems with m>50.

The decreasing effect for the first scrubber efficiency is a result of the recirculation/accumulation as

previously mentioned.




34

• Toluene emissions versus time (second scrubber, H 2O=8 m3/h)

0

1000

2000

3000

4000

5000

6000

0 1 2 3 4 5 6 7 8 9 10 11 12t (h)

Tol

uene

gas

out

(m

g/m

3 )S

econ

d S

crub

ber

0

5000

10000

15000

20000

25000

30000

0 1 2 3 4 5 6 7 8 9 10 11 12t (h)

Tol

uene

gas

out

(m

g/m

3 )

Sec

ond

Scr

ubbe

r

Figure 17. Comparison between toluene emissions variation with time for first scrubber toluene constant flow rate of

0.833 kg/h (on the left) and 4.16 kg/h (on the right). Calculations were made for several nitrogen flow rates.

As expected the amount of toluene coming out in the gas phase is considerably less for the toluene

flow rate of 0.833 kg/h. Less coming in means less coming out due to the efficiency for both flow rates

remain constant (Figure 16). Due to the dilution effect of toluene at the vent outlet by nitrogen, the

concentration rate of emissions is lower for higher nitrogen flow rates. However, an exception was found

for nitrogen flow rate of 20 m3/h.




35

• Toluene in the liquid phase (bottom of first scrubb er) versus time (H 2O=12 m3/h)

0.0E+00

5.0E-05

1.0E-04

1.5E-04

2.0E-04

2.5E-04

3.0E-04

3.5E-04

4.0E-04

4.5E-04

5.0E-04

0 1 2 3 4 5 6 7 8 9 10 11 12t (h)

g T

olue

ne/g

H2O

bott

om fi

rst s

crub

ber

0.0E+00

2.5E-04

5.0E-04

7.5E-04

1.0E-03

1.3E-03

1.5E-03

0 1 2 3 4 5 6 7 8 9 10 11 12t (h)

g T

olue

ne/g

H2O

bo

ttom

firs

t scr

ubbe

r

Figure 18. Comparison between variation with time of the toluene in the liquid phase for toluene flow rate of 0.833

kg/h (on the left) and 4.16 kg/h (on the right). Calculations were made for several nitrogen flow rates (red line

indicates toluene solubility in water at 20 ºC).

From these two figures one can see that we won’t have a phase separation between water and

toluene since the values are below the solubility at 20ºC, except for higher toluene flow rate and a nitrogen

flow rate of 20 m3/h. At lower, nitrogen flow rates, toluene solubility in water increases as less toluene is

being stripped out.

At a constant toluene emission flow rate of 4.16 kg/h, toluene solubility of 5×10-4 is obtained with a

nitrogen flow rate of 42 m3/h. This results in an overall efficiency of 85%.




36

• Overall Efficiency versus time

0

1020

3040

50

6070

8090

100

0 1 2 3 4 5 6 7 8 9 10 11 12

t (h)

Ove

rall

Eff

icie

ncy

(%)

0

10

20

30

40

50

6070

80

90

100

0 1 2 3 4 5 6 7 8 9 10 11 12t (h)

Ove

rall

Eff

icie

ncy

(%)

Figure 19. Comparison between variation with time of the overall efficiency for toluene flow rate of 0.833 kg/h (on the

left) and 4.16 kg/h (on the right). Calculations were made for several nitrogen flow rates.

The overall efficiency results take the same course as the ones for Figure 16 as was expected.

• Scrubbing efficiency at various liquid flow rates t o the Top Scrubber (N 2=120m3/h)

30

40

50

60

70

80

90

100

0 1 2 3 4 5 6 7 8 9 10 11 12

t ( h)

Sec

ond

Scr

ubbe

r Eff

icie

ncy

(%)

30

40

50

60

70

80

90

100

0 1 2 3 4 5 6 7 8 9 10 11 12t (h)

Sec

ond

Scr

ubbe

r Eff

icie

ncy

(%)

Figure 20. Comparison between variation with time of the efficiency in the continuous scrubber for toluene flow rate of

0.833 kg/h (on the left) and 4.16 kg/h (on the right). Calculations were made for several water flow rates.






37

From the previous figure one can see that the water amount fed to the continuous scrubber has a big

impact on its efficiency. Increasing the water to the continuous packed bed will increase the efficiency by

1.5x that for a doubling of the liquid flow rate (10 to 20 m3/h).

The flow of the liquid phase has also an impact on the first scrubber efficiency: a water flow rate of 15

m3/h and of 20 m3/h will increase the efficiency for the first hour to 60% and 74% respectively (efficiency

for the next hours will also be increased).

Since the nitrogen flow rate is fixed due to safety reasons, an analysis was made to see how does the

water flow rate for the second scrubber (with the actual toluene flow rates) affects the efficiency and

toluene emissions.

30

40

50

60

70

80

90

100

0 1 2 3 4 5 6 7 8 9 10t (h)

Sec

ond

Scr

ubbe

r Eff

icie

ncy

(%)

Figure 21. Second scrubber efficiency variation with time for several water flow rates

38

-40

-20

0

20

40

60

80

100

0 1 2 3 4 5 6 7 8 9 10

t (h)

Ove

rall

Eff

icie

ncy

(%)

Figure 22. Overall efficiency variation with time for several water flow rates

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0 1 2 3 4 5 6 7 8 9 10t (h)

Tol

uene

gas

out

(kg

/h)

Sec

ond

Scr

ubbe

r

Figure 23. Toluene emissions variation with time for several water flow rates

As we can see by the previous graphs (and as seen in Figure 20) increasing the water flow rate to the

continuous scrubber will have a major impact to the removal efficiency and consequently to the toluene

emissions. Increasing the water to the continuous packed bed will decrease toluene emissions by 2.25x

that for a doubling of the liquid flow rate (10 to 20 m3/h).

39

4.2.1.1. SCRUBBERS SENSITIVITY ANALYSIS SUMMARY

Accordingly to the previous results a summary of the sensitivity results was performed.

Table 5. Scrubbers sensitivity results summary

CHANGED PARAMETER CONSEQUENCES

TOLUENE FLOW RATE:

10 kg/batch (0.833 kg/h)

↓

50 kg/batch (4.16 kg/h)

First scrubber efficiency (A): constant

Second scrubber efficiency (B): constant

Toluene gas out, second scrubber (C): increases 5x

g toluene/g H2O first scrubber (D): increases 5x

Overall Efficiency (E): constant

NITROGEN FLOW RATE:

20 → 120 m3/h

and

20 → 10000 m3/h

A: decreases 2x and 150x

B: decreases 3x and 240x

D: decreases 6x and 5x

E: decreases 3x and 241x

NITROGEN FLOW RATE:

20 → 60 m3/h

60 → 120 m3/h

60 → 10000 m3/h

C:

increases 26x

decreases 1x

decreases 60x

WATER FLOW RATE:

10 m3/h

↓

25 m3/h

B: increases 2x

C: decreases 3.7x

E: increases 2x (not accounting for negative values)

40

5. CONCLUSION _____________________________________________

A crystallization process from a Fujifilm Inkjet Dye produces toluene emissions that are minimized by

gas absorption using a multi-bed scrubber. The scrubber employed was not originally designed for use

with toluene. A scrubber model was devised to assess the potential capability of the existing scrubber for

the new duty and what improvements would be required (if any) to achieve compliance with the

regulations.

Emissions from the process vessels were calculated using EPA equations and the heating process

with toluene only in the vessel is the one who produces major emissions. Preliminary emissions

calculations were feed back to the development chemist, which resulted in a number of process changes

that allowed an immediate reduction in toluene emitted. An example of this is the Gas Sweep 2 (Table 4)

that is done before the Heating 1. One of the early versions of the process considered the Gas sweep 2

done at the same time as Heating 1.

The final process emissions were used to assess recent emission calculation changes to Intelligen’s

design and simulation software (v7.5).

Final results for the toluene emissions calculations from SPD are in close agreement with the ones

from the Excel spreadsheet and small discrepancies are likely to be due to differences in some of the

parameters used by SPD to do the calculations.

The process emissions were then fed into a new toluene scrubbing model that used the ONDA

equations. Toluene is only partially soluble in water (520 ppm), with a Henry’s constant of 258 at 20ºC

(m>50). In the Appendix, Figure A.21, we can see the dependence of the Henry’s constant with the

temperature for this system. The efficiency of very dilute systems will be dependent on the L/G flow rate,

and this dependency was shown to be the case for toluene scrubbing (figures 15 to 23).

Accumulation in the first scrubber is limited due to poor solubility and gas stripping. The first scrubber

appears to be smoothing out the toluene released to second scrubber, potentially reducing the extent of

any peak emissions.

Lower nitrogen flow rates will greatly improve toluene absorption efficiency (see figures 15-19).

However, nitrogen in the process is used to maintain an inert atmosphere for safety reasons and cannot

be changed. Unfortunately, this means additional toluene is emitted during charging operations (gas

sweep) and scrubbing efficiency is reduced due to stripping (see figure 7 and 8) at the system nitrogen

flow rate (120 m3/h).

41

Increasing the liquid flow rates will have the most immediate benefit in terms of removal efficiency, as

seen in Figures 20 to 23. At a flow rate of 13 m3/h of water in the second scrubber H1 screening for short

term could also be achieved routinely. However, the impact of increase flow in terms of equipment

associated with the scrubber and downstream effluent consideration will need to be assessed and costed

for.

The existing scrubber system using water has limited potential for toluene abatement, due to the poor

solubility.

The current scrubber system was able to achieve insignificance levels for long term emissions (H1

screening) but unable to routinely achieve short term (H1 screening) insignificance levels and either Class

A or B benchmarks without additional measures. Although, the latter is not a function of the scrubber per

se. Failure to meet the concentration benchmarks is due in part to the very low carrier gas flow compared

to other chemical installation scrubbers, where the volumetric flow of carrier gas [air] through a scrubber

used to provide through-pan draughting is typically 10-500 times higher than the carrier gas [nitrogen] flow

through the existing scrubber.

Use of the existing condenser and/or increased liquid flow to the scrubber will ensure the overall

abatement measures satisfy both short and long term ground level concentrations and although

disproportionately high outlet concentrations will still be observed, given the elevated location of the outlet

(away from any receptors including personnel) and the very low ground level concentrations indicated by

the H1 Screening Assessment, no environmental impact would therefore be expected.

The condenser in the reaction vessel A (section 2.2) will be used and will address the worst case

emission from this vessel (Heating 1, section 2.2.1) having a positive effect in the toluene emissions

control.

Potential improvement measures to be assessed include:

• Chilled condensation on the process vessel

• Increasing the second scrubber liquid flow rate

• Alternative process solvent

• Alternative scrubbing medium

• Additive to water to increase toluene solubility

The best available techniques will be fully assessed and cost benefit determined.

Future modeling work should consider:

• Inclusion of venturi section to assess impact on mass transfer within the existing model

• Comparison of current model with those available within SuperPro Designer.

42

PIGMENT DISPERSIONS CONCENTRATION/PURIFICATION

1. MEMBRANE TECHNOLOGY INTRODUCTION _______________ ____

1.1. HISTORY

Systematic studies of membrane phenomena can be traced to the eighteenth century philosopher

scientists. Through the nineteenth and early twentieth centuries, membranes were used as laboratory

tools to develop physical/chemical theories having no industrial or commercial uses [13].

Membranes found their first significant application in the filtration of drinking water samples at the end

of World War II. Drinking water supplies serving large communities in Germany and elsewhere in Europe

had broken down, and filters to test for water safety were needed urgently [13].

By 1960, the elements of modern membrane science had been developed, but membranes were used

in only a few laboratory and small, specialized industrial applications. It was in the early 1960’s with the

Loeb-Sourirajan process for making defect-free, high flux, asymmetric reverse osmosis membranes that

transformed membrane separation from a laboratory to an industrial process. These membranes consist

of an ultrathin, selective surface film on a microporous support, which provides the mechanical strength.

The work of Loeb and Sourirajan resulted in the commercialization of reverse osmosis and was a primary

factor in the development of ultrafiltration and microfiltration [13].

1960 to 1980 produced a significant change in the status of membrane technology. Methods of

packaging membranes into spiral-wound, hollow-fine fibre, capillary, and plate-and-frame modules were

developed, and advances were made in improving membrane stability. By 1980, microfiltration,

ultrafiltration, reverse osmosis, and electrodialysis were all established processes with large plants

installed around the world [13].

Membranes have gained an important place in chemical technology and are being used increasingly

in a broad range of applications. The key property that is exploited in every application is the ability of a

membrane to control the permeation of a chemical species in contact with it. In separation applications,

the goal is to allow one component of a mixture to permeate the membrane freely, while hindering

permeation of other components [12].

43

Today, membranes are used on a large scale to produce potable water from the sea; to clean

industrial effluents and recover valuable constituents; to concentrate, purify, or fractionate macromolecular

solutions in the food and drug industries; to remove urea and other toxins from the bloodstream in artificial

kidneys; and to release drugs at a controlled rate in medicine [12].

Membrane processes may differ in their basic operating mode and areas of application. However,

they share several features that make them particularly attractive tools for the separation of molecular

mixtures. Separation is performed by physical means at ambient temperature without damaging or

chemically altering the constituents [12].

1.2. DEFINITION

A membrane is an interphase that separates two phases and restricts the transport of chemical

species in a specific manner.

Figure 24. Schematic diagram of a membrane with selective permeability.

A mixture of components of different sizes is brought to the surface of a semipermeable membrane.

Under a driving force, some components permeate the membrane, whereas others are retained. A feed

solution is separated into a filtrate/permeate that is depleted of particles or molecules and a

retentate/concentrate in which these components are concentrated.

44

1.2.1. CROSS FLOW VS. DEAD END

Throughput can often be significantly improved by using a cross flow system rather than a dead-end

flow system.

Dead end or frontal membrane microfiltration, in which the particle containing fluid is pumped directly

through a polymeric membrane, is used for the industrial clarification and sterilization of liquids. Such a

process allows the removal of particles down to 0.1 µm or less, but is only suitable for feeds containing

very low concentrations of particles as otherwise the membrane becomes too rapidly blocked.

In cross flow filtration the particle-containing fluid to be filtered is pumped parallel to the face of the

membrane. The liquid permeates through the membrane and the feed emerges in a more concentrated

form at the exit of the module [30].

Figure 25. Tangential vs. dead-end flow [31].

As shown in Figure 25, in dead-end flow the flow rate gradually decreases as a polarized layer builds

up on the surface of the filter. Eventually, an unacceptable pressure differential is reached [31].

In the case of the cross flow system configuration the particles or molecules are continuously swept

away from the surface of the membrane by the flow stream across the surface [31].

The advantages of cross-flow filtration over conventional filtration are [30]:

• A higher overall liquid removal rate is achieved by prevention of the formation of an extensive filter

cake.

• The process feed remains in the form of a mobile slurry suitable for further processing.

45

• The solids content of the product slurry may be varied over a wide range.

• It may be possible to fractionate particles of different sizes.

1.3. TYPES OF MEMBRANE

Membranes can be homogeneous or heterogeneous, symmetric or asymmetric in structure, it may be

solid or liquid and it may be neutral, carry either positive or negative charges, or have functional groups

with specific binding or complexing abilities.

Figure 26. Schematic diagrams of the principal types of membrane [13].

Mass transport through a membrane can occur via diffusion of individual molecules or convection

induced by a concentration, pressure, temperature, or electrical potential gradient. All materials

functioning as membranes have one common characteristic: they restrict the passage of different

components in a very specific manner.

46

1.4. MEMBRANE MODULES

A useful membrane process requires the development of a membrane module containing large

surface areas of membrane per unit of volume and with the capacity of processing fluids in adequate

hydrodynamic and pressure conditions and should be easy to clean and achieve high efficiencies.

1.4.1. SPIRAL-WOUND MODULE

In Spiral-Wound module the membrane is laminated with a feed spacer separating two sheets of

membrane. The permeate side of the membrane contacts a fluid-conductive fabric, in turn connected to a

perforated central pipe. The edges are glued to make a complete seal between the feed and permeate

sides of the device, and the wound module is placed inside a tubular pressure vessel, and feed gas is

circulated axially down the module across the membrane envelope. A portion of the feed permeates into

the membrane envelope, where it spirals toward the centre and exits through the collection. Multiple

leaves are used because the pressure drop in the permeate-conducting fabric becomes limiting at leaf

lengths much over 1 m.

47

Figure 27. Schematic diagram of spiral-wound module [30], [32].

These modules make better use of space than tubular or flat-sheet types, although they are rather

prone to fouling and difficult to clean.

1.4.2. TUBULAR MODULE

The tubular membrane module consists of membrane tubes placed in porous stainless steel or

fibreglass-reinforced plastic pipes. The pressurized feed solution flows down the tube bore, and the

permeate is collected on the outer side of the porous support pipe. Individual modules contain a cluster of

tubes in series held within a stainless steel permeate shroud.

48

Figure 28. Schematic diagram and picture of tubular modules [33], [34].

Tubular modules are widely used where it is advantageous to have a turbulent flow regime and are

easily cleaned. Their main disadvantages are the relatively low membrane surface area contained in a

module of given overall dimensions and their high volumetric hold-up.

1.4.3. HOLLOW-FIBRE MODULE

Hollow-fibre modules consist of bundles of fine fibres, 0.1–2.0 mm in diameter, sealed in a tube. This

gives very compact units capable of high pressure operation, although the flow channels are less than 0.1

mm wide and are therefore readily fouled and difficult to clean. At one end the fibres are embedded in an

epoxy tubesheet and at the other end they are sealed. The filtrate passes through the fibre walls and flows

up the bore to the open end of the fibres at the epoxy head.

Figure 29. Hollow-fibre module (left) and single fibre (right) [30].

FeedRetentate

Permeate

Permeate

Permeate

49

1.4.4. PLATE AND FRAME

Plate-and-frame systems consist of plates each with a membrane on both sides. The plates have a

frame around their perimeter which forms flow channels ca 1 mm wide between the plates when they are

stacked. The stack is clamped between two end plates, sealing the frames together.

At least one hole near the perimeter of each plate connects the flow channels from one side of the

plate to the other. The membrane is sealed around the hole to isolate the permeate from the concentrate.

Permeate collects in a drain grid behind the membrane and exits from a withdrawal port on the frame

perimeter.

Figure 30. Picture and schematic diagram of a plate and frame module [35].

Permeate is collected from each membrane pair so that damaged membranes can be easily

identified, though replacement of membranes requires dismantling of the whole stack.

50

1.4.5. MEMBRANE MODULES COMPARISON

A comparison between membrane modules is shown in the following table.

Table 6. Membrane modules comparison [36].

1.5. MEMBRANE APPLICATIONS

The principal use of membranes in the chemical processing industry is in various separation

processes. The developed separation processes are microfiltration (MF), ultrafiltration (UF), nanofiltration

(NF), reverse osmosis (RO), electrodialysis (ED) and pervaporation (PV). These processes are grouped

according to the driving force that is used to conduct the separation. The driving force in all these

processes may be a hydrostatic pressure gradient, a concentration gradient, a thermal gradient and an

electrical potential gradient.

51

Table 7. Membrane processes characteristics [37].

The most relevant processes for the purpose of this thesis are the pressure driven ones, namely the

ultrafiltration process.

1.5.1 PRESSURE DRIVEN PROCESSES

Ultrafiltration, microfiltration, and reverse osmosis are the most important pressure-driven membrane

separation processes. When the feed mixture of molecules and particles is brought to the surface of a

semipermeable membrane by convection, solvent or small solutes pass through the membrane as filtrate

under a hydrostatic pressure driving force, whereas larger particles and molecules are retained by the

membrane and concentrated in the retentate. Both the retentate and the filtrate are assumed to be well

mixed and to have no concentration gradients. These processes differ principally in the size of the

particles separated by the membrane.

52

Figure 31. Filtration Spectrum [38].

Microfiltration is considered to refer to membranes with pore diameters from 0.1 mm (100 nm) to 10

mm. Microfiltration membranes are used to filter suspended particulates, bacteria, or large colloids from

solutions.

Ultrafiltration refers to membranes having pore diameters in the range 2-100 nm. Ultrafiltration

membranes can be used to filter dissolved macromolecules, such as proteins, from solution. Typical

applications of ultrafiltration membranes are concentrating proteins from milk whey, or recovering colloidal

paint particles from electrocoating paint rinse waters. Ultrafiltration membranes are characterized, in

addition to other properties, by their nominal molecular weight cut-off (MWCO). All the molecules larger

than the molecular weight cut-off of a particular membrane are generally retained and those smaller than

the molecular weight cut-off level generally pass through the membrane.

Nanofiltration is a process, with characteristics between those of ultrafiltration and reverse osmosis,

which is finding increasing application in pharmaceutical processing and water treatment. Membrane

pores are 1 nm and this process can separate particles whose size range is between 200 and 1000 Da.

53

In reverse osmosis membranes, the pores are in the range 0.5- 2 nm in diameter. Reverse osmosis

membranes are used to separate dissolved microsolutes, such as salt, from water. The principal

application of reverse osmosis is the production of drinking water from brackish groundwater or seawater.

54

2. EXPERIMENTAL ___________________________________________

2.1. ULTRAFILTRATION IN REACTIVE DISPERSANTS

The reactive dispersant team at Fujifilm is concerned with producing aqueous pigment dispersion

inks. The reactive dispersant inks consist of pigment particles suspended in aqueous solution. These

pigment particles are surrounded by a component (named as Component X due to confidentiality issues)

which prevents the particles from forming aggregates or flocking. A physical process is needed next, but

due to confidentiality issues it cannot be described here. The component added is stabilized by a

chemistry step, and after a separation step the ink is washed and excess of this component is removed

(an Ultrafiltration step) before the ink can be sent to customers. A diagram of the reactive dispersants

process is shown below.

FinalizationPurification

Step

Confidential

Separation

Step

ConfidentialPack Off &

Labelling

Ultrafiltration

Purification

Step

Separation

Step

Confidential

Chemistry

Step

Confidential

Physical

Step

ConfidentialPigment

Dispersion

Figure 32. Reactive Dispersants Process.

The UF membrane unit in reactive dispersants receives sample batches from the Fujifilm Pilot Plant

for Pigment Dispersions or directly from the Fujifilm Laboratory.

2.2. MEMBRANE UNIT DESCRIPTION

The membrane unit used in the reactive dispersants is a DDS flat sheet module. The unit includes a

25 litre feed tank, a centrifugal pump to allow the sample to flow through the unit, a centrifugal pump to

add deionised water to the feed tank, a level sensor to control the water added to the feed tank, a

deionised water vessel, a temperature sensor, a heat exchanger (though not in use) and a control panel.

The module consists of a number of spacers (frames) and membrane covered plates mounted in

sandwich fashion and held together by a centre bolt, where each membrane sheet has an area of 0.036

m2. The unit has a total of 19 plates meaning a total area of 0,684 m2.

55

Figure 33. DDS Flat sheet unit at Fujifilm membrane lab.

The membrane sheets are held with a seal either side of the support plate that removes the permeate.

The membrane is separated by the spacer plates which are designed with holes in it to allow the

concentrate to flow across each membrane sheet. The membranes support and spacers are presented in

Figure 34.

Figure 34. Plate, spacers and membranes of the flat sheet unit.

56

The vertical stack of spacers, plates and membranes is arranged in a way that flow channels covered

with membranes are formed when hydraulically compressed. It is of major importance that the spacers in

the stack be with the ridged edges pointing upwards as in Figure 35. Just above the bottom end flange, a

spacer is placed and then a membrane, a support plate, a membrane and so on.

Figure 35. Closer look of a spacer.

The inlet flow from the feed tank passes through a heat exchanger to remove any excess heat

generated (this heat exchanger was not used during the experiments). The flow then passes up through

the membrane stack surrounding the central bolt where the permeate is being rejected, perpendicular to

the stack, through the permeate tubes located in the membrane support plates perimeter. The outlet flow,

concentrate, is collected in the top end flange and led to a pressure regulating valve, where the pressure

can be regulated by adjusting the screw beneath the valve.

57

Figure 36. Plate and frame unit schematics and picture of the DDS unit.

The membranes that can be used in this unit are those pointed out below as well as its characteristics.

Table 8. Characteristics and operating conditions for the DDS membranes

The current cross-flow membrane filtration system of choice for the purification and concentration of

pigment dispersions in the DDS unit is the Alfa Laval flat-sheet stack fitted with Polysulphone polymer

micro-filtration membranes. The pore size of the membranes used has been 0.2 micron (Reference

GRM0.2PP). Scanning Electron Micrographs (SEM) of these type of membranes are showed in Figure

37.

58

Figure 37. SEMS of GRM 0.2PP membranes.

Picture a in Figure 37 show evidence of a mottled surface and craters. In b a possible evidence of a

surface layer while core appears more porous.

2.3. EXPERIMENTAL PROCEDURE

To process the pigment dispersion samples in the DDS unit is necessary concentration (initial and

final) and diafiltration steps. Before and after each run a water cold flow measurement is always

performed. This procedure is needed to check if the membranes were affected by the sample. The

procedure is as it follows:

a

b

59

Water Cold Flow

1. Make sure unit is clean

2. Recirculate deionised water at a pump speed of 5.2 (control panel) and at 8 bar inlet pressure

until the unit reaches 25°C. Back pressure is neede d to allow an inlet pressure of 8 bar.

3. Measure permeate flow rate at these conditions

4. Take note of the back pressure applied

5. Stop unit

Permeate

line

Concentrate line

Deionised w ater

8 bar

Figure 38. Water cold flow step (recirculation).

Start up/ Initial Concentration

1. Remove water from the tank.

2. Take C1 from the sample, which should be at approximately 5% pigment strength.

3. Add sample to the tank and note volume.

4. With a low motor speed remove volume equivalent to unit’s hold-up to remove the water from the

system.

5. Recirculate sample for 10 minutes by adjusting the cross flow (pump speed) and with no back

pressure applied until it reaches 8 bar pressure.

6. Concentrate sample to 10% pigment strength and adjust the cross flow accordingly.

7. Recirculate for a further 10 minutes.

8. Unit is now ready to be processed further.

60

Permeate line

Concentrate line

Deionised w ater

8 bar

Permeate line

Concentrate line

Deionised w ater

8 bar

Figure 39. Initial concentration (steps 5 and 7 on the left, step 6 on the right).

Washing/Diafiltration

1. Ultrafiltrate the sample at 10% pigment strength by adjusting the cross flow (pump speed) and

with no back pressure applied at 8 bar inlet pressure.

2. Keep tank level constant by the addition of deionised water when washing for 10 wash volumes

noting all measurements on to run sheet.

Permeate line

Concentrate line

Deionised w ater

8 bar

Figure 40. Diafiltration step.

Final concentration

1. Once 10 wash volumes have been achieved stop the water to start concentration stage.

2. Keep a check on the pressure reducing motor speed when pressure increases.

3. Do one final flow rate near the end of the concentration stage.

4. Once over concentrating the sample by 2- 3 Litres, stop unit and note all measurements

5. Remove sample from tank.

61

6. Add fresh water to the tank and displace 1 litre from the system into the sample (concentrate line)

7. Displace a further 1 Litre into a sample bottle as your D1. If necessary, displace a further litre into

another sample bottle as your D2.

8. Stir sample and take C2.

9. Recirculate unit so that the membranes do not get coated in pigment and cause pore blocking.

Permeate line

Concentrate line

Deionised w ater

8 bar

Permeate line

Concentrate line

Deionised w ater

Figure 41. Final concentration and water recirculation step.

The samples collected during the process, C1, C2, D1 and D2 are used to perform the mass balance

(total solids analysis). These measurements allow one to know how much pigment is recovered and how

much impurity is removed from the sample.

2.3.1. DIAFILTRATION

The technique of continuous diafiltration (also referred to as constant volume diafiltration) involves

washing out the original buffer salts (or other low molecular weight species) in the retentate (sample) by

adding water or a new buffer to the retentate at the same rate as filtrate is being generated. As a result,

the retentate volume and product concentration does not change during the diafiltration process. Diafiltration

improves the degree of separation between retained and permeable species. If water is used for diafiltering,

the salts will be washed out and the conductivity lowered.

The amount of salt removed is related to the filtrate volume generated, relative to the retentate

volume. The filtrate volume generated is usually referred to in terms of “diafiltration volumes”. A single

diafiltration volume (DV) or wash volume (WV) is the volume of retentate when diafiltration is started. For

continuous diafiltration, liquid is added at the same rate as filtrate is generated. When the volume of filtrate

collected equals the starting retentate volume, 1 DV has been processed.

62

Concentrating a sample first can significantly reduce the volume of diafiltration solution required.

Therefore, if the sample is first concentrated to the final concentration required and then continuous

diafiltration performed, acceptable results should be obtained. However, above a certain concentration,

filtrate flux rates may become prohibitively slow.

2.3.2. WORKING CONDITIONS: INLET PRESSURE 8 BAR & NO BACK PRESSURE APPLIED

Pressure conditions for the processing in the DDS unit were carefully optimized and consisted in a

previous work done with the membranes (not part of this thesis).

During the washing stage the serial membrane arrangement of the DDS unit has given in the pass

back-pressure problems such that one cannot operate at the desired range of cross-flow rate and TMP.

Careful experimentation using a single membrane element to decouple cross-flow and TMP

parameters allowed to obtain the data of where one should actually operate. High TMP increases flux

rate but the extra flux is merely water. The best conditions to remove Component X are very low TMP

and high cross-flow (Appendix, section A.4).

2.4. WATER ANALYSIS

Water parameters of the water used in the DDS membrane unit were controlled by an ion exchange

resin contained in a cylinder and by biofilters.

Figure 42. Cylinders for the producing of deionised water (on the left) and biofilters (on the right) [39], [40].

63

Every two weeks in the DDS unit lab a water analysis was performed in order to check water ph,

conductivity and bacteria growth.

Figure 43. Bacteria analysis test [41].

The results allow one to know when the cylinder and/or biofilters need to be changed, in order to have

a proper water to use in the DDS unit.

64

3. RESULTS AND DISCUSSION ________________________________

3.1. EXCEL RUN SPREADSHEET

After the sample has been processed in the membrane unit an Excel spreadsheet is filled with the

data collected during the run. Data collected include the diafiltration and final concentration stage and

don’t take into account the initial concentration stage.

The next figures/tables are examples from a yellow sample of the Excel spreadsheet containing the

data collected during the sample processing.

Project Reactive Dispersant Colour Yellow Sample NBZ/6070/49

Date 02-06-2008Plant Membrane Suite

Run No DDS2/174

Membrane GRM-0.2PPNumber of plates 19

Area 0,684 m2

Strength 10,14 %Starting Volume 28 l

Final Volume 12,5 l

1st. Disp. Volume 1 l2nd. Disp. Volume 1 l

Cold Water Flow 242,4 l/h

Inlet Pressure 8 BarOutlet Pressure 5,1 Bar

Temperature 25 °C

Cold Water Flow 158,4 l/hInlet Pressure 8 Bar

Outlet Pressure 4,4 BarTemperature 25 °C

Initial Data

Final Data

Wash Volumes

9,86

22,0 °C

Bar8,1

Average temperature

Average Pressure

Clock Time

Time (min)

Flow rate (ml/min)

Flux Rate

(L/m2.h)

Permeate Conductivity

(µµµµS)

Bulk Permeate

Conductivity (µs)

Pressure In

(Bar)

Pressure Out

(Bar)

TMP (Bar)

Temperature (°C)

Permeate Volume (L)

Cumulative Volume

(L)

Tank Level

(L)Comments

Wash Volumes

10:55 0 420,0 36,84 2860,0 8,1 0,7 7,4 24,00 0 0 14 0,00

11:53 58 460,0 40,35 694,0 1017,0 8 0,7 7,3 23,00 25 25 14 PB1 1,72

12:47 112 460,0 40,35 195,0 723,0 8 0,6 7,4 22,00 25 50 14 PB2 3,45

13:44 169 460,0 40,35 92,0 133,0 8,1 0,6 7,5 22,00 25 75 14 PB3 5,17

14:41 226 460,0 40,35 72,0 102,0 8,1 0,6 7,5 21,00 25 100 14 PB4 6,90

15:26 271 440,0 38,60 64,0 66,0 8,1 0,6 7,5 21,00 20 120 14 PB5 8,28

16:10 315 460,0 40,35 60,0 63,0 8,4 0,6 7,8 21,00 20 140 14 PB6 9,6616:17 322 400,0 35,09 79,0 69,0 8,1 0,6 7,5 22,00 3 143 11 9,86

* Final concentration*

Figure 44. Excel run spreadsheet.

Figure 44 shows the data collected during the diafiltration and final concentration stage as well as the

cold water flow measurements and sample/membrane unit data.

Some of the values are direct measurements like the flow rate, permeate and bulk permeate

conductivity, pressure in and out, temperature, permeate volume and tank level. Flux rate, TMP

(transmembrane pressure) and wash volumes are calculated by the spreadsheet.

From the table of Figure 44 some graphs are generated, temperature, conductivity and flow rate

versus time of processing.

65

0,0

5,0

10,0

15,0

20,0

25,0

30,0

0 50 100 150 200 250 300 350Time (min)

Tem

pera

ture

(°C

)

Figure 45. Feed temperature vs. time for a yellow sample. Experimental conditions: Flat-sheet stack fitted with 19

plates of Polysulphone polymer micro-filtration membranes with pore size of 0.2 micron; no back pressure applied

at 8 bar inlet pressure; 10 wash volumes.

From the previous graph one can see that the temperature remains almost constant during the

processing of the sample. However, despite not significant, in the beginning and at the end of the run the

temperature is slightly higher to this constant value. At the beginning of the run, before the processing, a

recirculation stage is always performed and since no deionised water is being added the temperature

increases (first point of Figure 45). In the end (last point of the graph), at the concentration stage, the

addition of deionised water is stopped and as a consequence, despite there’s no recirculation, the

temperature rises.

66

Figure 46. Permeate conductivity vs. time for a yellow sample. Experimental conditions: Flat-sheet stack fitted with 19



The permeate conductivity decreases drastically in the first minutes (75% in the first 50 minutes; 93%

in the first 100 minutes), decreasing really slowly for the rest of the run. In the concentration stage there’s

an increase in the conductivity value.

The sample contains impurities such as metallic ions, salts, among other compounds that for

confidentiality issues cannot be described here. All these impurities contribute to the conductivity values

and, at the starting of the run since no washing has been performed yet, these impurities are in a higher

concentration being more easily removed. The fact that the membrane is cleaner at the beginning

contributes also for a quicker impurity removal.

The sudden increase in the conductivity value during the concentration stage is a consequence of the

increase in the sample concentration. The strength of the solution will rise stimulating the ions passage

across the membrane.

0

500

1000

1500

2000

2500

3000

3500

0 50 100 150 200 250 300 350

Time (min)

Con

duct

ivity

(µµ µµ

S)

50

55

60

65

70

75

80

85

90

200 225 250 275 300 325 350Time (min)

Con

duct

ivity

(µµ µµ

S)

50

55

60

65

70

75

80

85

90

200 225 250 275 300 325 350Time (min)

Con

duct

ivity

(µµ µµ

S)

67

0

5

10

15

20

25

30

35

40

45

0 50 100 150 200 250 300 350

Time (min)

Flu

x ra

te (

l/m2

h)

Figure 47. Permeate flux rate vs. time for a yellow sample. Experimental conditions: Flat-sheet stack fitted with 19



The concentration stage is also responsible for a decrease in the permeate flux rate. Ions and salts

accumulation in the membrane surface causes blockage. As a consequence resistance to permeation

occurs decreasing the flux rate. An increase in the solution viscosity causing a gel layer formation

(concentration polarization) is also responsible for the permeate flux rate increase in the first minutes. The

lower initial value for the permeate flux rate can be explained by the same reasons.

During diafiltration, permeate flux rate remains approximately constant because the sample

concentration, due to the water being added to the tank, remains constant. In this case the gel formation

layer is in an equilibrium condition.

3.1.1. MASS BALANCE

3.1.1.1. PIGMENT RECOVERY

After the processing the samples taken are analyzed in moistness analysis equipment for a total

solids measurement. This will allow the determination of the mass balance to the process. The analysis is

performed in equipment that measures the moisture content with precision weighing technology using an

infra-red heating lamp. The results of the analysis are expressed in percentage of total solids and the

mass balance is then performed accordingly to Figure 48.

68

SampleTotal Solids (% solids)

Volume (l)

Dry weight of sample

(g)

C1 10,14 28,0 2839,2C2 17,85 12,5 2231,3D1 1,88 1,0 18,8D2 0,14 1,0 1,4

Figure 48. Mass balance.

The dry weight of sample is calculated multiplying the total solids percentage by the sample volume.

C1 will give the amount of dry weight of sample in the pigment dispersion before the run (feed), C2 the

amount after the run (product) and D1 and D2 the amount in the displacement. The yield of the process

can be determined doing a mass balance to the membrane unit.

This yellow sample had a yield of 78,6% and from the mass balance one can see that the amount of

color lost to the unit and permeate was high, 20,7%. The losses to the unit is a consequence of

accumulation and adsorption of the pigment by the membrane, samples taken during the run, pipes and

feed vessel, and transfer of the sample to the unit and displaced from it. The estimation of the losses are

difficult and relates to the determination of the final pigment strength. Further work is planned to explain

this higher than expected loss. There are also some minimal losses to the permeate stream but these are

not calculated.

3.1.1.2. COMPONENT X REMOVAL

One of the main objectives of the UF stage in Reactive Dispersants is the removal of the excess of a

component (Component X) that was added to the dispersion in the Chemistry Stage.

The calculations for the removal of Component X in the UF stage are based in the conductivity

measurements taken during the run accordingly to Figure 49.

69

Figure 49. Component X removal calculation example.

Component X concentration in the permeate is calculated using the values of bulk permeate

conductivity. A previous work had to be done to know how the variation of Component X with conductivity

is. This work is not a part of this thesis and was done previously. The work consists in doing several

Component X solutions with different concentrations and measuring the conductivity of each one. A

trendline is then adjusted to the graph Component X concentration vs. conductivity (this graph is in the

Appendix, section A.5).

Another way of calculating the loss of Component X is directly from the mass balance (total solids

analysis) by the difference between dry weight of sample C2 and C1.

The dry weight of Component X is calculated using its concentration and the volume of permeate and

the initial weight is calculated using the dry weight of C1 sample (Figure 48). Depending the sample color

is black, magenta, cyan or yellow an initial percentage of Component x is known and using the dry weight

of C1 sample the initial weight of Component x can be calculated.

The previous graph from Figure 49 show us that the component X removal is more efficient in the first

4 washing volumes and tend to a constant value for the next washing volumes.

1169,08 g

46,8 % 52,0 %546,9 g 608,0 g

Impurity Loss by Calibration Curve

Impurity Loss By Total Solids

Initial weight of impurity

0

100

200

300

400

500

600

0 1 2 3 4 5 6 7 8 9 10

Wash Volumes

Impu

rity

loss

(g)

0

10

20

30

40

50

60

70

80

90

100

Impu

rity

loss

(%

)

Volume (l)

Bulk Permeate

Conductivity (µµµµS)

Impurity concentration

w/w %

Dry weight impurity

(g)

Cumulative impurity weight

in permeate (g)

% Impurity loss

Wash volumes

0 0 0PB1 25 1017 1,16 290,48 290,48 24,85 1,72PB2 25 723 0,81 202,28 492,75 42,15 3,45PB3 25 133 0,10 25,28 518,03 44,31 5,17PB4 25 102 0,06 15,98 534,00 45,68 6,90PB5 20 66 0,03 6,64 540,64 46,24 8,28PB6 20 63 0,03 6,28 546,92 46,78 9,66

Total Impurity Lost 546,92 46,78

70

3.2. SAMPLES RESULTS COMPARISON

After processing some of the samples in the membrane unit a comparison was made between them

in terms of permeate conductivity, flux rates and mass balance values.

3.2.1. PERMEATE CONDUCTIVITY VS. RUN TIME

0

500

1000

1500

2000

2500

3000

0 100 200 300 400 500

Time (min)C 162 C 163 C 164 C 176 C 177

0

500

1000

1500

2000

2500

3000

0 100 200 300

Time (min)

Per

mea

te c

ondu

ctiv

ity (

µµ µµs)

Y 165 Y 168 Y 174 Y 175

0

500

1000

1500

2000

2500

3000

0 50 100 150 200 250 300

Time (min)M 159 M 160 M 161 M 172 M 173

0

500

1000

1500

2000

2500

3000

3500

4000

4500

0 100 200 300Time (min)

Per

mea

te c

ondu

ctiv

ity (

µµ µµs)

K 166 K 167 K 169 K 170

K 171 K 178 K 179 K 180

K 181 K 182A K 183B K 184

Run No.

Run No.

Run No. Run No.

Black Samples Cyan Samples

Yellow Samples Magenta Samples

Figure 50. Permeate conductivity vs. run time for black (K), cyan (C), yellow (Y) and magenta (M) samples processed

in the DDS unit. Experimental conditions: Flat-sheet stack fitted with 19 plates of Polysulphone polymer micro-filtration

membranes with pore size of 0.2 micron; no back pressure applied at 8 bar inlet pressure; 10 wash volumes.

71

Analyzing the above figure one can see that all the samples show the same behavior, conductivity

values decrease really fast in the first 100 minutes and slowly for the end of the run. Since the samples

don’t take the same time to process new plots of permeate conductivity (PC) against wash volumes (WV)

were made and a trendline was adjusted to the values.

0

500

1000

1500

2000

2500

3000

3500

4000

4500

0 1 2 3 4 5 6 7 8 9 10 11

Wash Volumes

Per

mea

te c

ond

uctiv

ity (

µS)

0

500

1000

1500

2000

2500

3000

0 1 2 3 4 5 6 7 8 9 10 11

Wash Volumes

0

500

1000

1500

2000

2500

3000

0 1 2 3 4 5 6 7 8 9 10 11

Wash Volumes

Per

mea

te c

ondu

ctiv

ity (

µS)

0

500

1000

1500

2000

2500

3000

0 1 2 3 4 5 6 7 8 9 10 11

Wash Volumes



Figure 51. Permeate conductivity vs. wash volumes for black (K), cyan (C), yellow (Y) and magenta (M) samples

processed in the DDS unit. Exponential trendline adjustment. Experimental conditions: Flat-sheet stack fitted with 19



72

An exponential trendline was adjusted to the plots from the previous figure. Black, cyan, yellow and

magenta graphs have the following equations respectively:

PC (µS) = 1621,1 e -0,429 WV

(R2=0,923) (28)

PC (µS) = 1097,6 e -0,346 WV

(R2=0,874) (29)

PC (µS) = 1416,9 e -0,383 WV

(R2=0,889) (30)

PC (µS) = 1301,9 e -0,385 WV

(R2=0,924) (31)

The plots from the previous figure (Figure 51) are for the diafiltration stage and don’t take into account

the final concentration stage, last point of the graphs from Figure 50.

Initial permeate conductivity is difficult to predict because it depends of the type of pigment used (even

for the same color), the amount of impurities like metal ions, salts, among others; and sample

concentration despite being approximately 10%. This can be seen in Figure 51 were for the beginning of

the run (0 wash volumes) different values for the permeate conductivity can be observed. Black samples

are the ones with higher initial permeate conductivity values.

The exponential trendline adjusted to the graphs is incapable of describing the initial permeate

conductivity but it describes with a relatively good accuracy the values of the permeate conductivity for the

remaining points, as one can see from graphs and the values of R2.

Another analysis was made without taking into account the initial permeate conductivity (and the

concentration stage also). A new trendline was adjusted and the results are in Figure 52.

73

0

200

400

600

800

1000

1200

1400

0 1 2 3 4 5 6 7 8 9 10 11

Wash Volumes

0

100

200

300

400

500

600

700

0 1 2 3 4 5 6 7 8 9 10 11

Wash Volumes

0

100

200

300

400

500

600

700

800

0 1 2 3 4 5 6 7 8 9 10 11

Wash Volumes

Per

mea

te c

ondu

ctiv

ity (

µS)

0

200

400

600

800

1000

1200

1400

0 1 2 3 4 5 6 7 8 9 10 11

Wash Volumes

Per

mea

te c

ondu

ctiv

ity (

µµ µµS

)



Figure 52. Permeate conductivity vs. wash volumes for black (K), cyan (C), yellow (Y) and magenta (M) samples

processed in the DDS unit. Power trendline adjustment. Experimental conditions: Flat-sheet stack fitted with 19 plates

of Polysulphone polymer micro-filtration membranes with pore size of 0.2 micron; no back pressure applied at 8

bar inlet pressure; 10 wash volumes.

For the plots from Figure 52 the best fit is a power trendline. Black, cyan, yellow and magenta graphs

have the following equations respectively:

PC (µS) = 2508,3 WV -1,872

(R2=0,924) (32)

PC (µS) = 1036,1 WV -1,313

(R2=0,917) (33)

74

PC (µS) = 1375,0 WV -1,468

(R2=0,916) (34)

PC (µS) = 1367,9 WV -1,507

(R2=0,934) (35)

From Figure 52 and respective equations one can conclude that the diafiltration stage (without

including the permeate conductivity initial values) for the different pigment colors can be described with a

good accuracy by a power trendline.

Putting all data in one graph the following figure is obtained.

0

500

1000

1500

2000

2500

3000

3500

4000

4500

0 1 2 3 4 5 6 7 8 9 10 11

Wash Volumes

Permeate conductivity (

µµ µµs)

Pilot Plant Bxs

Run No.

Figure 53. Permeate conductivity vs. wash volumes for all the samples processed in the DDS unit. Experimental

conditions: Flat-sheet stack fitted with 19 plates of Polysulphone polymer micro-filtration membranes with pore size of

0.2 micron; no back pressure applied at 8 bar inlet pressure; 10 wash volumes.

Despite having the same behavior permeate conductivity values in Figure 53 are higher for pilot plant

batches in the initial wash volumes than for lab batches. Pilot plant batches stay longer in containers at

the pilot plant and the use of a biocide is needed to control bacteria growth. The biocide used is

responsible for the higher conductivity values.

75

0

50

100

150

200

250

300

4 5 6 7 8 9 10 11

Wash Volumes

Permeate conductivity (

µµ µµs)

Run No.

Figure 54. Permeate conductivity vs. wash volumes for all the samples processed in the DDS unit. Final concentration

values. Experimental conditions: Flat-sheet stack fitted with 19 plates of Polysulphone polymer micro-filtration

membranes with pore size of 0.2 micron; no back pressure applied at 8 bar inlet pressure; 10 wash volumes.

Figure 54 show us that the permeate conductivity for all samples increase in the final concentration

stage for the reasons mentioned before.

3.2.2. PERMEATE CONDUCTIVITY VS. FINAL CONCENTRATION FACTOR

The final concentration factor is not the same for all samples. Knowing the final sample volume and

the tank volume in the diafiltration stage is possible to know the final concentration factor. In order to know

how the permeate conductivity varies with the final concentration a graph was made including all the

samples.

76

0

20

40

60

80

100

120

140

160

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0

Concentration factor

Fin

al C

ondu

ctiv

ity (

µµ µµS

)

Figure 55. Final permeate conductivity values vs. concentration factor. Experimental conditions: Flat-sheet stack fitted

with 19 plates of Polysulphone polymer micro-filtration membranes with pore size of 0.2 micron; no back pressure

applied at 8 bar inlet pressure; 10 wash volumes.

Due to the high variability of values a final conclusion cannot be made. However, the general trend is

the higher the concentration factor the higher the final permeate conductivity.

77

3.2.3. FLUX RATE VS . WASH VOLUMES

The following figures show us the permeate flux rate against wash volumes for all the samples.

0

10

20

30

40

50

60

70

80

0 2 4 6 8 10

Wash volumes

Flu

x ra

te (

l/m2 .

h)

K 166 K 167 K 169 K 170 K 171 K 178

K 179 K 180 K 181 K 182 K 183 K 184

0

10

20

30

40

50

60

70

80

0 2 4 6 8 10Wash volumes

C 162 C 163 C 164 C 176 C 177

0

10

20

30

40

50

60

70

80

0 2 4 6 8 10

Wash volumes

Flu

x ra

te (

l/m2 .

h)

Y 165 Y 168 Y 174 Y 175

0

10

20

30

40

50

60

70

80

0 2 4 6 8 10

Wash volumes

M 159 M 160 M 161 M 172 M 173

Black SamplesCyan Samples


Run No.

Run No. Run No.

Run No.

Figure 56. Permeate flux rate vs. wash volumes for black (K), cyan (C), yellow (Y) and magenta (M) samples

processed in the DDS unit. Experimental conditions: Flat-sheet stack fitted with 19 plates of Polysulphone polymer

micro-filtration membranes with pore size of 0.2 micron; no back pressure applied at 8 bar inlet pressure; 10

wash volumes.

As expected the flux rate remains approximately constant during the diafiltration stage. The initial and

final points of the graph are usually lower for the reasons mentioned before.

78

25

35

45

55

65

75

85

0 1 2 3 4 5 6 7 8 9 10 11Wash volumes

Flu

x ra

te (

l/m2 .

h)

LabBxs

Pilot PlantBxs

Samples No.

Figure 57. Permeate flux rate vs. wash volumes for all the samples processed in the DDS unit. Experimental

conditions: Flat-sheet stack fitted with 19 plates of Polysulphone polymer micro-filtration membranes with pore size of

0.2 micron; no back pressure applied at 8 bar inlet pressure; 10 wash volumes.

With all permeate flux rate values in the same plot is possible to distinguish two areas where there is a

high flux rate zone and low flux rate zone.

There is no separation between the colors processed since the permeate flux rate depends on several

things like polarization concentration on the membrane surface, heterogeneity of substances in solution,

molecular size. All the samples suffer the same process previous to ultrafiltration. However, some

samples are from the pilot plant and others directly from the lab as mentioned before. Pilot plant samples

have lower permeate flux rates and lab samples have generally high permeate flux rates. The main

reason for this separation is that pilot plant samples despite having the same process, the physical stage

is processed in different equipment from the one in the lab. Lower permeate flux may imply higher run

times and may be a consequence of differences in the samples from the ones produced in the lab.

79

3.2.4. MASS BALANCE

A comparison between results from the mass balance performed to the unit is shown in the following

figures.

0

10

20

30

40

50

60

70

80

90

100

M 159

M 160

M 161

C 162

C 163

C 164

Y 165

K 166

K 167

Y 168

K 169

K 170

K 171

M 172

M 173

Y 174

Y 175

C 176

C 177

K 178

K 179

K 180

K 181

K 182

K 183

K 184

Samples

Product Yield (%)

Figure 58. Product yield (pigment) vs. samples processed in the DDS unit. Experimental conditions: Flat-sheet stack

fitted with 19 plates of Polysulphone polymer micro-filtration membranes with pore size of 0.2 micron; no back

pressure applied at 8 bar inlet pressure; 10 wash volumes.

0

5

10

15

20

25

30

35

40

M 159

M 160

M 161

C 162

C 163

C 164

Y 165

K 166

K 167

Y 168

K 169

K 170

K 171

M 172

M 173

Y 174

Y 175

C 176

C 177

K 178

K 179

K 180

K 181

K 182

K 183

K 184

Samples

Unit losses (%)

Figure 59. Unit losses vs. samples processed in the DDS unit. Experimental conditions: Flat-sheet stack fitted with 19



Black Cyan Yellow Magenta


80

0

1

2

3

4

5

6

7

8

9

M 159

M 160

M 161

C 162

C 163

C 164

Y 165

K 166

K 167

Y 168

K 169

K 170

K 171

M 172

M 173

Y 174

Y 175

C 176

C 177

K 178

K 179

K 180

K 181

K 182

K 183

K 184

Samples

Displacement losses (%)

Figure 60. Displacement losses vs. samples processed in the DDS unit. Experimental conditions: Flat-sheet stack

fitted with 19 plates of Polysulphone polymer micro-filtration membranes with pore size of 0.2 micron; no back

pressure applied at 8 bar inlet pressure; 10 wash volumes.

0

20

40

60

80

100

120

140

159 161 163 165 167 169 171 173 175 177 179 181 183 185 187

Bx Sequence

Component X losses (%)

Total solids Calibration curve

Figure 61. Comparison between Component X removal estimation by total solids and Component X calibration curve.

Experimental conditions: Flat-sheet stack fitted with 19 plates of Polysulphone polymer micro-filtration membranes

with pore size of 0.2 micron; no back pressure applied at 8 bar inlet pressure; 10 wash volumes.

Accordingly to Figure 58 one can conclude that the product yield is approximately constant for all

samples with an average of 80%. A higher yield wasn’t possible due to high unit losses (Figure 59) that

decreased over the course lifetime by taking a second displacement from the unit. Displacement losses

are in the main very low (less than 1%) but there are some runs that yield a slightly greater loss, the most

recent runs show that Black pigment has the greatest loss.


81

Component X removal was estimated by total solids measurements and using Component X

calibration curve (Appendix, Figure A.5.). Results show an average of 54% removal with no significant

pigment permeate losses based in total solids measurement and 60% based in the calibration curve.

Discrepancy between values in Figure 61 are due to the fact that pigment dispersions samples have

other type of compounds in solution, making it difficult to measure how much of Component X is actually

being removed based on the calibration curve. Total solids measurements despite being the most realistic

values can show some deviations from reality because the removal measure of Component X is based on

the difference between total solids in the beginning of the run and in the end and this difference is not only

for Component X but also for salts and ions removal (as for some pigment losses).

3.3. COLD WATER FLOW MONITORING

Before and after processing a sample in the membrane unit cold water flow measurements are always

performed. These measurements are at a specific pump speed, 25ºC and at 8 bar pressure (inlet). Back

pressure is needed to reach the 8 bar inlet pressure.

A decrease in the water flow after one run means that the sample has had a negative effect on the

membranes. In the same way an increase means a positive effect. A negative effect implies membrane

fouling (blocking the pores) or in the worst case formation of a gel layer. When the final cold water flow is

greater than the initial one (positive effect), this generally indicates that the particular sample has had a

cleaning effect.

Back pressure must be applied in order to achieve an 8 bar inlet pressure. In the same way as for the

water flow, a decrease in the back pressure applied after one run also means that the sample has had a

negative effect in the membranes.

When the negative effect is really high a chemical cleaning is carried out. A caustic (NaOH) or a

polymer solution cleaning can be carried out to regenerate as much as possible the membrane. If the

membrane does not regenerate with the cleaning membranes must be replaced.

By monitoring the cold water flow and back pressure applied it is possible to keep the membrane

operating at an optimum level.

82

120

140

160

180

200

220

240

260

280

300

0 10 20 30 40 50 60Bx Sequence

Col

d w

ater

flow

(l/h

)Before

AfterBx 159

Bx 163

Before

After NaOH cleaning

Polymer solution cleaning

NaOH cleaning

MagentaYellow

Black

YellowCyan

Magenta

Cyan

Figure 62. Cold water flow measurements. Experimental conditions: Flat-sheet stack fitted with 19 plates of

Polysulphone polymer micro-filtration membranes with pore size of 0.2 micron; pump speed at 5.2; 8 bar inlet

pressure; temperature of 25ºC.

As shown in Figure 62, the cold water flow rate varies over the series of runs and the general trend is

a decline of membrane performance with increased numbers of runs.

Yellow and magenta samples seem to have a negative impact on the membrane since the water flow

tends to decrease after each run. Cyan and black samples may have a positive or negative effect. In

general, there does not seem to be any straightforward conclusions regarding the color of the pigment. In

fact, even within the same color, each pigment color may have many different samples representing it and

possesses different molecules that may interact differently with the membrane. Otherwise, chemical

cleaning has the effect of improving the cold water flow.

Plotting in a graph the difference between final and initial cold water flow values (∆ flow rate) and the

difference between final and initial back pressure applied (∆ pressure) is a good way to check the effect of

samples in membrane performance.

83

-150

-100

-50

0

50

100

150

0 5 10 15 20 25 30

Sequence

∆∆ ∆∆ F

low

Rat

e (l/

h)

-3.5

-3

-2.5

-2

-1.5

-1

-0.5

0

0.5

1

1.5

2

2.5

∆∆ ∆∆ P

ress

ure

(bar

)

Figure 63. Difference between final and initial cold water flow rate vs. samples processed in the DDS unit (blue).

Difference between final and initial back pressure applied vs. samples processed in the DDS unit (orange).

Figure 63 show one that, excluding some points, there is a connection between the two plots being

not independent one from each other. This means that generally the samples have the same effect in the

cold water flow and back pressure applied.

84

4. CONCLUSION _____________________________________________

The work done within the membrane lab was mainly focused on the reactive dispersants sample

processing for desalination and concentration of pigment dispersions (Yellow, Cyan, Magenta and Black)

by the diafiltration process using a flat sheet membrane unit.

Permeate conductivity measurements during sample processing show decreasing values with

diafilltration wash volumes. This was observed for Yellow, Cyan, Magenta and Black samples. An

exponential trendline was adjusted to the plots of permeate conductivity vs. wash volumes showing a

good relation. However, initial permeate conductivity is difficult to predict for all samples. Excluding initial

permeate conductivity values a power trendline is what best describes the permeate conductivity

behaviour for all the samples.

Permeate flux rates are not characteristic of a single color, however, a separation is observed

between pilot plant and lab samples. Pilot plant samples have high permeate flux rates while lab ones

have low permeate flux rates.

Cold water flow monitoring revealed that membrane performance generally decreases over the course

lifetime, despite particular samples are able to have a positive impact on membrane, by performing a

cleaning operation themselves. There was no irreversible fouling noted during all the runs. It was

concluded that membrane performance does not depend or is specific to the colour of the pigment.

From the mass balance an average yield of 80% in pigment recovery was achieved. The reasons for

not having higher yield values are the high unit losses that decreased over the course lifetime by taking a

second displacement. More and careful analyses of the initial and final pigment strength is planned to try

to explain and in turn minimise this displacement loss further. Unit losses are characterized by

accumulation and adsorption on the membrane, losses in pipes and in the feed vessel, losses in sampling

and also losses when the sample is initially transferred to the unit.

The experiments made in DDS unit for the Reactive Dispersants project demonstrated an average of

54% in Component X removal from the solution with no significant pigment permeate losses based in total

solids measurement. From Component X calibration curve an average of 60% was obtained. Discrepancy

of values between total solids measurements and Component X calibration curve are due to the fact that

pigment dispersions samples have other type of compounds in solution, making it difficult to measure how

much of Component X is actually being removed based on the calibration curve. Total solids

measurements despite being the most realistic values can show some deviations from reality because the

removal measure of Component X is based on the difference between total solids in the beginning of the

85

run and in the end and this difference is not only for Component X but also for salts and ions removal (as

for some pigment losses).

Further work in the membrane unit would include:

• Measuring sample strength (pigment) in the beginning and at the end of the runs by absorbance

measurements using a spectrophotometer;

• Developing a new calibration curve for Component X removal (including the other compounds in

solution);

• Using data from the runs as a way to found discrepancies in reactive dispersants process.

86

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November (1996)

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[8] B.G. Wang, Y. Miyazaki, T. Yamaguchi and S.I. Nakao, Design of a vapor permeation membrane for

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waste air using a flat composite membrane bioreactor, Biotech. & Bioeng. 85 (2004), 68-77

[12] Ullmann’s Encyclopedia of Industrial Chemistry, Sixth Edition, 2002

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87

[14] Larsen, Louis M., Industrial Printing Inks, Reinhold Publishing Corporation, 1962

[15] www.sepa.org.uk (03.06.2008)

[16] www.warwickshire.gov.uk/Web/corporate/pages.nsf/Links/84DE4628111FC007802573FA0040A57E/

$file/Chapter+11complete+rev1.pdf (22.09.2008)

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Volume 2, chapter 8, EPA February 2005

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Volume 2, chapter 8, EPA February 2004

[21] www.intelligen.com (03.06.2008)

[22] Wang, L. K.; Pereira, N. C.; Hung, Y., Handbook of Environmental Engineering, Volume 1 - Air

pollution control engineering, Humana Press, 2004

[23] yosemite.epa.gov/oaqps/EOGtrain.nsf/ (03.06.2008)

[24] Sinnott, R. K., Coulson & Richardson’s Chemical Engineering, Volume 6 – Chemical Engineering

Design, Butterworth Heinemann, 1997

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Interfacial Mass Transfer in Randomly Packed Towers: A Confident Correlation For Environmental

Applications

[26] www.p2pays.org/ref/10/09883.pdf (06.06.2008)

[27] en.wikipedia.org/wiki/Venturi_scrubber (06.05.2008)

[28] www.tri-mer.com/pdf-files/packed-bed-tower-scrubbers.pdf (06.05.2008)

88

[29] Bunyakan, C.; Nikom, R., Removal of VOCs by oxidation reaction in wet scrubber

(www.intania.com/files/EN04.pdf)

[30] Coulson, J.M.; Richardson, J. F., Chemical Engineering, Volume 2, fourth edition, Butterworth

Heinemann, 1991

[31] www.spectrapor.com/lit/abc.pdf (23.09.2008)

[32] www.mtrinc.com/faq.html (23.09.2008)

[33] www.memos-filtration.de/en/wir.php (23.09.2008)

[34] www.techbriefs.com/content/view/2294/14/ (23.09.2008)

[35] www.nbimcc.org/BioINEP/Book/M%20III%20part%203.pdf (23.09.2008)

[36] www.kochmembrane.com/

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Instituto Superior Tecnico, Lisboa, Portugal.

[38] www.osmolabstore.com/library_main.htm (14.08.2008)

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[47] CRC Handbook of Chemistry and Physics

89

APPENDIX

A.1. CALCULATION METHOD – HEATING OF VESSELS

Organic hazardous air pollutants (HAP) caused by the heating of a vessel shall be calculated using

the following procedures:

(1) If the final temperature to wich the vessel contents is heated is lower than 50 K below the boiling

point of the HAP in the vessel, then organic HAP emissions shall be calculated using the

equations for heating of vessels in Table 2.

(2) If the vessel contents are heated to a temperature greater than 50 K below the boiling point, then

organic HAP emissions shall be calculated in accordance to the following paragraphs:

2.1. For the interval from the initial temperature to the temperature 50 K below the boiling point,

organic HAP emissions shall be calculated using equations for heating of vessels in Table

2. where T2 is the temperature 50 K below the boiling point.

2.2. For the interval from the temperature 50 K below the boiling point to the final temperature,

organic HAP emissions shall be calculated as the summation of emissions for each 5 K

increment, where the emissions for each increment shall be calculated using equations for

heating of vessels in Table 2.

2.2.1 If the final temperature of the heatup is at or lower than 5 K below the boiling point, the

final temperature for the last increment shall be the final temperature for the heatup,

even if the last increment is less than 5 K.

2.2.2 If the final temperature of the heatup is higher than 5 K below the boiling point, the

final temperature for the last increment shall be the temperature 5 K below the boiling

point, even if the last increment is less than 5 K.

90

A.2. DATA OF STREAMS ENTERING SCRUBBERS & MAIN RESULTS

Table A. 1. Nitrogen inlet stream (first scrubber)

0 1 2 3 4 5 6 7 8 9 10

Qin (m3/h) 120 120 120 120 120 120 120 120 120 120 120

Win (kg/h) 139.69 139.69 139.69 139.69 139.69 139.69 139.69 139.69 139.69 139.69 139.69

nin (kmol/h) 4.989 4.989 4.989 4.989 4.989 4.989 4.989 4.989 4.989 4.989 4.989

Table A. 2. Toluene inlet stream (first scrubber)

0 1 2 3 4 5 6 7 8 9 10

Qin (m3/h) 0.364 0.364 0.145 0.145 0.145 0.511 0.147 0.056 0.056 0.140 0.051

Win (kg/h) 1.560 1.560 0.620 0.620 0.620 2.190 0.630 0.240 0.240 0.600 0.220

nin (kmol/h) 0.017 0.017 0.007 0.007 0.007 0.024 0.007 0.003 0.003 0.007 0.002

Table A. 3. Gas mixture entering the first scrubber

0 1 2 3 4 5 6 7 8 9 10

Qin (m3/h) 120.36 120.36 120.14 120.14 120.14 120.51 120.15 120.06 120.06 120.14 120.05

nin total (kmol/h) 5.006 5.006 4.996 4.996 4.996 5.013 4.996 4.992 4.992 4.995 4.991

Gm (kmol/(m2.s)) 0.003 0.003 0.003 0.003 0.003 0.003 0.003 0.003 0.003 0.003 0.003

Gm (kg/(m2.s)) 0.078 0.078 0.078 0.078 0.078 0.078 0.078 0.077 0.077 0.078 0.077

yN2 in 0.997 0.997 0.999 0.999 0.999 0.995 0.999 0.999 0.999 0.999 1.000

ytoluene in (y1) 0.00339 0.00339 0.00135 0.00135 0.00135 0.00475 0.00137 0.00052 0.00052 0.00131 0.00048

Table A. 4. Liquid mixture inlet stream (top of first scrubber)

0 1 2 3 4 5 6 7 8 9 10

Qin (m3/h) 12 12 12 12 12 12 12 12 12 12 12

ntotal liq (kmol/h) 665.473 665.482 665.482 665.477 665.477 665.477 665.485 665.477 665.475 665.475 665.477

Lm (kmol/(m2.s) 0.368 0.368 0.368 0.368 0.368 0.368 0.368 0.368 0.368 0.368 0.368

x2 0 1.26E-05 1.31E-05 5.52E-06 5.24E-06 5.23E-06 1.79E-05 5.79E-06 2.17E-06 2.03E-06 4.95E-06

xH2O top 1 0.999987 0.999987 0.999994 0.999995 0.999995 0.999982 0.999994 0.999998 0.999998 0.999995

Table A. 5. Gas mixture entering the second scrubber

0 1 2 3 4 5 6 7 8 9 10

Qin (m3/h) 120.18 120.36 120.25 120.15 120.14 120.33 120.32 120.11 120.06 120.10 120.09

nin total (kmol/h) 4.997 5.006 5.001 4.996 4.996 5.004 5.004 4.994 4.992 4.993 4.993

Gm (kmol/(m2.s)) 0.003 0.003 0.003 0.003 0.003 0.003 0.003 0.003 0.003 0.003 0.003

Gm (kg/(m2.s)) 0.078 0.078 0.078 0.078 0.078 0.078 0.078 0.077 0.077 0.077 0.077

yN2 in 0.998 0.997 0.998 0.999 0.999 0.997 0.997 0.999 0.999 0.999 0.999

ytoluene in (y1) 0.002 0.003 0.002 0.001 0.001 0.003 0.003 0.001 0.001 0.001 0.001

91

Table A. 6. Liquid mixture inlet stream (top of second scrubber)

0 1 2 3 4 5 6 7 8 9 10

Qin (m3/h) 8 8 8 8 8 8 8 8 8 8 8

ntotal liq (kmol/h) 443.6 443.6 443.6 443.6 443.6 443.6 443.6 443.6 443.6 443.6 443.6

Lm (kmol/(m2.s) 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25

x2 0 0 0 0 0 0 0 0 0 0 0

xH2O top 1 1 1 1 1 1 1 1 1 1 1

Table A. 7. First scrubber main results

0 1 2 3 4 5 6 7 8 9 10

Gm/Lm 0.00752 0.00752 0.00751 0.00751 0.00751 0.00753 0.00751 0.00750 0.00750 0.00751 0.00750

HG (m) 0.244 0.244 0.245 0.245 0.245 0.244 0.245 0.245 0.245 0.245 0.245

HL (m) 0.713 0.713 0.713 0.713 0.713 0.713 0.713 0.713 0.713 0.713 0.713

m 258 258 258 258 258 258 258 258 258 258 258

HOG (m) 1.627 1.627 1.625 1.625 1.625 1.628 1.625 1.624 1.624 1.625 1.624

NOG 2.766 2.766 2.770 2.770 2.770 2.764 2.770 2.771 2.771 2.770 2.771

y2 0.0017 0.0033 0.0024 0.0014 0.0014 0.0031 0.0030 0.0010 0.0005 0.0009 0.0009

Toluene gas out top (kg) 0.786 1.531 1.084 0.637 0.621 1.413 1.373 0.462 0.248 0.422 0.402

Toluene gas out top (kmol) 0.009 0.017 0.012 0.007 0.007 0.015 0.015 0.005 0.003 0.005 0.004

Toluene gas out top (mg/m3) 6552 12759 9037 5312 5172 11777 11438 3846 2070 3513 3350

y1/y2 1.98 1.02 0.57 0.97 1.00 1.55 0.46 0.52 0.97 1.42 0.55

Efficiency (%) 49.6 1.9 -74.9 -2.8 -0.1 35.5 -117.9 -92.3 -3.5 29.7 -82.7

Toluene liq. out bottom (kmol) 0.008 0.009 0.004 0.003 0.003 0.012 0.004 0.001 0.001 0.003 0.001

Toluene liq. out bottom (kg) 0.774 0.803 0.338 0.321 0.320 1.097 0.354 0.133 0.124 0.303 0.121

x1 1.26E-05 1.31E-05 5.52E-06 5.24E-06 5.23E-06 1.79E-05 5.79E-06 2.17E-06 2.03E-06 4.95E-06 1.97E-06

g Toluene/g H2O bottom 6.46E-05 6.70E-05 2.82E-05 2.68E-05 2.67E-05 9.16E-05 2.96E-05 1.11E-05 1.04E-05 2.53E-05 1.01E-05

Table A. 8. Second scrubber main results

0 1 2 3 4 5 6 7 8 9 10

Gm/Lm 0.0113 0.0113 0.0113 0.0113 0.0113 0.0113 0.0113 0.0113 0.0113 0.0113 0.0113

HG (m) 0.278 0.277 0.278 0.278 0.278 0.277 0.277 0.278 0.278 0.278 0.278

HL (m) 0.650 0.650 0.650 0.650 0.650 0.650 0.650 0.650 0.650 0.650 0.650

m 258 258 258 258 258 258 258 258 258 258 258

HOG (m) 2.166 2.168 2.167 2.165 2.165 2.168 2.168 2.165 2.164 2.165 2.165

NOG 2.078 2.075 2.077 2.078 2.078 2.076 2.076 2.079 2.079 2.079 2.079

y'2 0.0011 0.0022 0.0016 0.0009 0.0009 0.0020 0.0020 0.0007 0.0004 0.0006 0.0006

Toluene gas out top (kg) 0.519 1.012 0.716 0.421 0.410 0.934 0.907 0.305 0.164 0.278 0.265

Toluene gas out (mg/m3) 4326 8431 5969 3507 3414 7781 7557 2539 1366 2318 2211

y'1/y'2 1.515 1.513 1.514 1.515 1.515 1.514 1.514 1.515 1.515 1.515 1.515

Efficiency (%) 34.0 33.9 34.0 34.0 34.0 33.9 33.9 34.0 34.0 34.0 34.0

Toluene liq out bottom (kmol) 0.0029 0.0056 0.0040 0.0024 0.0023 0.0052 0.0051 0.0017 0.0009 0.0016 0.0015

Toluene liq out bottom (kg) 0.267 0.519 0.368 0.217 0.211 0.480 0.466 0.157 0.084 0.143 0.137

x'1 6.54E-06 1.27E-05 9.02E-06 5.31E-06 5.17E-06 1.17E-05 1.14E-05 3.84E-06 2.07E-06 3.51E-06 3.35E-06

g Toluene/g H2O bottom 3.35E-05 6.50E-05 4.61E-05 2.71E-05 2.64E-05 6.01E-05 5.83E-05 1.97E-05 1.06E-05 1.79E-05 1.71E-05

92

Table A. 9. Onda method results (assuming Lm constant)

First scrubber Second scrubber

Re 30.73 20.48

Fr 0.0010 0.0004

We 0.0028 0.0012

aw (m2/m

3) 83.7 73.7

kL (m/s) 1.11E-04 9.22E-05

Table A. 10. Onda method results, kG values (x 10-3)

0 1 2 3 4 5 6 7 8 9 10

First scrubber 3.264 3.264 3.243 3.243 3.243 3.243 3.27 3.27 3.245 3.245 3.236

Second scrubber 3.248 3.263 3.253 3.244 3.243 3.238 3.252 3.269 3.257 3.245 3.24

93

SCRUBBERS ANALYSIS

Table A. 11. Efficiency values for the first scrubber

Toluene (kg/h)N2

(m3/h)0 1 2 3 4 5 6 7 8 9 10 11 12

20 99.99 70.22 49.32 34.64 24.33 17.09 12.00 8.43 5.92 4.16 2.92 2.05 1.44

60 88.19 19.17 4.17E+00 9.06E-01 1.97E-01 4.28E-02 9.32E-03 2.03E-03 4.40E-04 9.58E-05 2.08E-05 4.53E-06 9.85E-07

120 53.83 2.48 1.15E-01 5.29E-03 2.45E-04 1.13E-05 5.22E-07 2.41E-08 1.12E-09 5.15E-11 2.39E-12 1.11E-13 1.11E-14

200 33.31 0.56 9.63E-03 1.65E-04 2.83E-06 4.85E-08 8.32E-10 1.43E-11 2.44E-13 0 0 0 0

250 26.79 0.32 3.85E-03 4.68E-05 5.68E-07 6.90E-09 8.38E-11 1.02E-12 1.11E-14 0 0 0 0

300 22.39 0.21 1.96E-03 1.87E-05 1.78E-07 1.70E-09 1.62E-11 1.44E-13 1.11E-14 0 0 0 0

400 16.84 0.11 7.66E-04 5.29E-06 3.66E-08 2.53E-10 1.75E-12 0 0 0 0 0 0

500 13.49 0.07 4.04E-04 2.28E-06 1.28E-08 7.22E-11 4.11E-13 0 0 0 0 0 0

700 9.65 0.04 1.74E-04 7.63E-07 3.35E-09 1.47E-11 5.55E-14 0 0 0 0 0 0

1000 6.76 0.02 8.06E-05 2.88E-07 1.03E-09 3.67E-12 1.11E-14 0 0 0 0 0 0

10000 0.68 0.00 2.72E-06 5.50E-09 1.11E-11 1.11E-14 1.11E-14 0 0 0 0 0 0

20 99.99 69.08 4.77E+01 3.30E+01 2.28E+01 1.57E+01 1.09E+01 7.52E+00 5.20E+00 3.59E+00 2.48E+00 1.72E+00 1.19E+00

60 87.75 18.53 3.92E+00 8.29E-01 1.75E-01 3.71E-02 7.85E-03 1.66E-03 3.51E-04 7.43E-05 1.57E-05 3.33E-06 7.04E-07

120 53.53 2.42 1.11E-01 5.13E-03 2.36E-04 1.09E-05 5.01E-07 2.30E-08 1.06E-09 4.88E-11 2.25E-12 1.11E-13 2.22E-14

200 33.18 0.56 1.00E-02 1.81E-04 3.25E-06 5.85E-08 1.05E-09 1.90E-11 3.55E-13 0 0 0 0

250 26.71 0.31 4.19E-03 5.51E-05 7.25E-07 9.55E-09 1.26E-10 1.65E-12 2.22E-14 0 0 0 0

300 20.45 0.17 1.63E-03 1.55E-05 1.49E-07 1.43E-09 1.36E-11 1.44E-13 0 0 0 0 0

400 15.38 0.09 7.04E-04 5.14E-06 3.80E-08 2.80E-10 2.05E-12 3.33E-14 0 0 0 0 0

500 12.32 0.06 3.96E-04 2.43E-06 1.52E-08 9.45E-11 6.00E-13 0 0 0 0 0 0

700 8.82 0.03 1.82E-04 9.01E-07 4.55E-09 2.29E-11 1.11E-13 0 0 0 0 0 0

1000 6.18 0.02 8.76E-05 3.59E-07 1.50E-09 6.27E-12 2.22E-14 0 0 0 0 0 0

10000 0.62 0.00 2.65E-06 5.72E-09 1.24E-11 2.22E-14 0 0 0 0 0 0 0

4.166

0.833

94

Table A. 12. Efficiency values for the second scrubber

Toluene (kg/h)N2

(m3/h)

0 1 2 3 4 5 6 7 8 9 10 11 12

20 99.56 99.55 99.55 99.54 99.54 99.54 99.54 99.53 99.53 99.53 99.53 99.53 99.53

60 64.15 64.02 63.99 63.99 63.99 63.99 63.99 63.99 63.99 63.99 63.99 63.99 63.99

120 33.88 33.85 33.85 33.85 33.85 33.85 33.85 33.85 33.85 33.85 33.85 33.85 33.85

200 20.51 20.50 20.50 20.50 20.50 20.50 20.50 20.50 20.50 20.50 20.50 20.50 20.50

250 16.43 16.43 16.43 16.43 16.43 16.43 16.43 16.43 16.43 16.43 16.43 16.43 16.43

300 13.71 13.71 13.71 13.71 13.71 13.71 13.71 13.71 13.71 13.71 13.71 13.71 13.71

400 10.29 10.29 10.29 10.29 10.29 10.29 10.29 10.29 10.29 10.29 10.29 10.29 10.29

500 8.24 8.24 8.24 8.24 8.24 8.24 8.24 8.24 8.24 8.24 8.24 8.24 8.24

700 5.89 5.89 5.89 5.89 5.89 5.89 5.89 5.89 5.89 5.89 5.89 5.89 5.89

1000 4.12 4.12 4.12 4.12 4.12 4.12 4.12 4.12 4.12 4.12 4.12 4.12 4.12

10000 0.41 0.41 0.41 0.41 0.41 0.41 0.41 0.41 0.41 0.41 0.41 0.41 0.41

20 99.56 99.52 99.49 99.47 99.45 99.44 99.43 99.43 99.42 99.42 99.42 99.42 99.41

60 64.06 63.42 63.29 63.26 63.26 63.26 63.26 63.26 63.26 63.26 63.26 63.26 63.26

120 33.77 33.62 33.61 33.61 33.61 33.61 33.61 33.61 33.61 33.61 33.61 33.61 33.61

200 20.45 20.41 20.41 20.41 20.41 20.41 20.41 20.41 20.41 20.41 20.41 20.41 20.41

250 16.39 16.37 16.37 16.37 16.37 16.37 16.37 16.37 16.37 16.37 16.37 16.37 16.37

300 13.68 13.67 13.67 13.67 13.67 13.67 13.67 13.67 13.67 13.67 13.67 13.67 13.67

400 10.27 10.27 10.27 10.27 10.27 10.27 10.27 10.27 10.27 10.27 10.27 10.27 10.27

500 8.23 8.22 8.22 8.22 8.22 8.22 8.22 8.22 8.22 8.22 8.22 8.22 8.22

700 5.88 5.88 5.88 5.88 5.88 5.88 5.88 5.88 5.88 5.88 5.88 5.88 5.88

1000 4.12 4.12 4.12 4.12 4.12 4.12 4.12 4.12 4.12 4.12 4.12 4.12 4.12

10000 0.41 0.41 0.41 0.41 0.41 0.41 0.41 0.41 0.41 0.41 0.41 0.41 0.41

4.166

(Scrubber 1)

0.833

(Scrubber 1)

95

Table A. 13. Toluene emissions from second scrubber (mg/m3)

Toluene

(kg/h)

N2

(m3/h) 0 1 2 3 4 5 6 7 8 9 10 11 12

20 1.68E-02 55.734 95.976 124.800 145.325 159.880 170.172 177.435 182.553 186.157 188.691 190.474 191.727

60 588.26 4039.28 4792.56 4956.49 4992.14 4999.89 5001.58 5001.94 5002.02 5002.04 5002.04 5002.04 5002.04

120 2120.0 4480.1 4588.8 4593.8 4594.0 4594.0 4594.0 4594.0 4594.0 4594.0 4594.0 4594.0 4594.0

200 2209.0 3294.0 3312.3 3312.6 3312.6 3312.6 3312.6 3312.6 3312.6 3312.6 3312.6 3312.6 3312.6

250 2039.3 2776.8 2785.6 2785.7 2785.7 2785.7 2785.7 2785.7 2785.7 2785.7 2785.7 2785.7 2785.7

300 1860.4 2392.1 2397.0 2397.0 2397.0 2397.0 2397.0 2397.0 2397.0 2397.0 2397.0 2397.0 2397.0

400 1554.2 1866.8 1868.9 1868.9 1868.9 1868.9 1868.9 1868.9 1868.9 1868.9 1868.9 1868.9 1868.9

500 1323.1 1528.2 1529.3 1529.3 1529.3 1529.3 1529.3 1529.3 1529.3 1529.3 1529.3 1529.3 1529.3

700 1012.3 1119.9 1120.4 1120.4 1120.4 1120.4 1120.4 1120.4 1120.4 1120.4 1120.4 1120.4 1120.4

1000 745.0 798.8 799.0 799.0 799.0 799.0 799.0 799.0 799.0 799.0 799.0 799.0 799.0

10000 82.4 83.0 83.0 83.0 83.0 83.0 83.0 83.0 83.0 83.0 83.0 83.0 83.0

20 0.1 310.4 557.6 745.8 884.7 985.2 1056.7 1107.3 1142.7 1167.5 1184.7 1196.7 1205.0

60 3056.7 20692.4 24492.2 25299.1 25470.0 25506.1 25513.8 25515.4 25515.7 25515.8 25515.8 25515.8 25515.8

120 10685.9 22491.3 23025.9 23050.5 23051.6 23051.6 23051.6 23051.6 23051.6 23051.6 23051.6 23051.6 23051.6

200 11073.7 16489.1 16579.6 16581.2 16581.2 16581.2 16581.2 16581.2 16581.2 16581.2 16581.2 16581.2 16581.2

250 10213.1 13894.0 13937.2 13937.8 13937.8 13937.8 13937.8 13937.8 13937.8 13937.8 13937.8 13937.8 13937.8

300 9537.8 11970.8 11990.5 11990.7 11990.7 11990.7 11990.7 11990.7 11990.7 11990.7 11990.7 11990.7 11990.7

400 7908.8 9338.3 9346.8 9346.9 9346.9 9346.9 9346.9 9346.9 9346.9 9346.9 9346.9 9346.9 9346.9

500 6705.2 7643.3 7647.9 7647.9 7647.9 7647.9 7647.9 7647.9 7647.9 7647.9 7647.9 7647.9 7647.9

700 5108.3 5600.4 5602.3 5602.3 5602.3 5602.3 5602.3 5602.3 5602.3 5602.3 5602.3 5602.3 5602.3

1000 3748.1 3994.2 3995.0 3995.0 3995.0 3995.0 3995.0 3995.0 3995.0 3995.0 3995.0 3995.0 3995.0

10000 412.4 414.9 414.9 414.9 414.9 414.9 414.9 414.9 414.9 414.9 414.9 414.9 414.9

0.833

(Scrubber 1)

4.166

(Scrubber 1)

96

Table A. 14. Toluene solubility (bottom of first scrubber, g toluene/g H2O)

Toluene

(kg/h)

N2

(m3/h) 0 1 2 3 4 5 6 7 8 9 10 11 12

20 6.96E-05 1.18E-04 1.53E-04 1.77E-04 1.94E-04 2.06E-04 2.14E-04 2.20E-04 2.24E-04 2.27E-04 2.29E-04 2.30E-04 2.31E-04

60 6.14E-05 7.47E-05 7.76E-05 7.82E-05 7.84E-05 7.84E-05 7.84E-05 7.84E-05 7.84E-05 7.84E-05 7.84E-05 7.84E-05 7.84E-05

120 3.75E-05 3.92E-05 3.93E-05 3.93E-05 3.93E-05 3.93E-05 3.93E-05 3.93E-05 3.93E-05 3.93E-05 3.93E-05 3.93E-05 3.93E-05

200 2.32E-05 2.36E-05 2.36E-05 2.36E-05 2.36E-05 2.36E-05 2.36E-05 2.36E-05 2.36E-05 2.36E-05 2.36E-05 2.36E-05 2.36E-05

250 1.86E-05 1.89E-05 1.89E-05 1.89E-05 1.89E-05 1.89E-05 1.89E-05 1.89E-05 1.89E-05 1.89E-05 1.89E-05 1.89E-05 1.89E-05

300 1.56E-05 1.57E-05 1.57E-05 1.57E-05 1.57E-05 1.57E-05 1.57E-05 1.57E-05 1.57E-05 1.57E-05 1.57E-05 1.57E-05 1.57E-05

400 1.17E-05 1.18E-05 1.18E-05 1.18E-05 1.18E-05 1.18E-05 1.18E-05 1.18E-05 1.18E-05 1.18E-05 1.18E-05 1.18E-05 1.18E-05

500 9.38E-06 9.43E-06 9.43E-06 9.43E-06 9.43E-06 9.43E-06 9.43E-06 9.43E-06 9.43E-06 9.43E-06 9.43E-06 9.43E-06 9.43E-06

700 6.71E-06 6.74E-06 6.74E-06 6.74E-06 6.74E-06 6.74E-06 6.74E-06 6.74E-06 6.74E-06 6.74E-06 6.74E-06 6.74E-06 6.74E-06

1000 4.70E-06 4.72E-06 4.72E-06 4.72E-06 4.72E-06 4.72E-06 4.72E-06 4.72E-06 4.72E-06 4.72E-06 4.72E-06 4.72E-06 4.72E-06

10000 4.71E-07 4.72E-07 4.72E-07 4.72E-07 4.72E-07 4.72E-07 4.72E-07 4.72E-07 4.72E-07 4.72E-07 4.72E-07 4.72E-07 4.72E-07

20 3.48E-04 5.88E-04 7.54E-04 8.69E-04 9.48E-04 1.00E-03 1.04E-03 1.07E-03 1.08E-03 1.10E-03 1.11E-03 1.11E-03 1.12E-03

60 3.05E-04 3.70E-04 3.83E-04 3.86E-04 3.87E-04 3.87E-04 3.87E-04 3.87E-04 3.87E-04 3.87E-04 3.87E-04 3.87E-04 3.87E-04

120 1.86E-04 1.95E-04 1.95E-04 1.95E-04 1.95E-04 1.95E-04 1.95E-04 1.95E-04 1.95E-04 1.95E-04 1.95E-04 1.95E-04 1.95E-04

200 1.15E-04 1.17E-04 1.17E-04 1.17E-04 1.17E-04 1.17E-04 1.17E-04 1.17E-04 1.17E-04 1.17E-04 1.17E-04 1.17E-04 1.17E-04

250 9.29E-05 9.40E-05 9.40E-05 9.40E-05 9.40E-05 9.40E-05 9.40E-05 9.40E-05 9.40E-05 9.40E-05 9.40E-05 9.40E-05 9.40E-05

300 7.11E-05 7.17E-05 7.17E-05 7.17E-05 7.17E-05 7.17E-05 7.17E-05 7.17E-05 7.17E-05 7.17E-05 7.17E-05 7.17E-05 7.17E-05

400 5.35E-05 5.38E-05 5.38E-05 5.38E-05 5.38E-05 5.38E-05 5.38E-05 5.38E-05 5.38E-05 5.38E-05 5.38E-05 5.38E-05 5.38E-05

500 4.29E-05 4.31E-05 4.31E-05 4.31E-05 4.31E-05 4.31E-05 4.31E-05 4.31E-05 4.31E-05 4.31E-05 4.31E-05 4.31E-05 4.31E-05

700 3.07E-05 3.08E-05 3.08E-05 3.08E-05 3.08E-05 3.08E-05 3.08E-05 3.08E-05 3.08E-05 3.08E-05 3.08E-05 3.08E-05 3.08E-05

1000 2.15E-05 2.16E-05 2.16E-05 2.16E-05 2.16E-05 2.16E-05 2.16E-05 2.16E-05 2.16E-05 2.16E-05 2.16E-05 2.16E-05 2.16E-05

10000 2.15E-06 2.16E-06 2.16E-06 2.16E-06 2.16E-06 2.16E-06 2.16E-06 2.16E-06 2.16E-06 2.16E-06 2.16E-06 2.16E-06 2.16E-06

0.833

4.166

97

Table A. 15. Overall efficiency

Toluene

(kg/h)

N2

(m3/h) 0 1 2 3 4 5 6 7 8 9 10 11 12

20 100 99.87 99.77 99.70 99.65 99.62 99.59 99.57 99.56 99.55 99.55 99.54 99.54

60 95.76 70.92 65.49 64.31 64.06 64.00 63.99 63.99 63.99 63.99 63.99 63.99 63.99

120 69.5 35.5 33.9 33.8 33.8 33.8 33.8 33.8 33.8 33.8 33.8 33.8 33.8

200 47.0 20.9 20.5 20.5 20.5 20.5 20.5 20.5 20.5 20.5 20.5 20.5 20.5

250 38.8 16.7 16.4 16.4 16.4 16.4 16.4 16.4 16.4 16.4 16.4 16.4 16.4

300 33.0 13.9 13.7 13.7 13.7 13.7 13.7 13.7 13.7 13.7 13.7 13.7 13.7

400 25.4 10.4 10.3 10.3 10.3 10.3 10.3 10.3 10.3 10.3 10.3 10.3 10.3

500 20.6 8.3 8.2 8.2 8.2 8.2 8.2 8.2 8.2 8.2 8.2 8.2 8.2

700 15.0 5.9 5.9 5.9 5.9 5.9 5.9 5.9 5.9 5.9 5.9 5.9 5.9

1000 10.6 4.1 4.1 4.1 4.1 4.1 4.1 4.1 4.1 4.1 4.1 4.1 4.1

10000 1.1 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4

20 100 99.9 99.7 99.6 99.6 99.5 99.5 99.5 99.5 99.4 99.4 99.4 99.4

60 95.6 70.2 64.7 63.6 63.3 63.3 63.3 63.3 63.3 63.3 63.3 63.3 63.3

120 69.2 35.2 33.7 33.6 33.6 33.6 33.6 33.6 33.6 33.6 33.6 33.6 33.6

200 46.8 20.9 20.4 20.4 20.4 20.4 20.4 20.4 20.4 20.4 20.4 20.4 20.4

250 38.7 16.6 16.4 16.4 16.4 16.4 16.4 16.4 16.4 16.4 16.4 16.4 16.4

300 31.3 13.8 13.7 13.7 13.7 13.7 13.7 13.7 13.7 13.7 13.7 13.7 13.7

400 24.1 10.4 10.3 10.3 10.3 10.3 10.3 10.3 10.3 10.3 10.3 10.3 10.3

500 19.5 8.3 8.2 8.2 8.2 8.2 8.2 8.2 8.2 8.2 8.2 8.2 8.2

700 14.2 5.9 5.9 5.9 5.9 5.9 5.9 5.9 5.9 5.9 5.9 5.9 5.9

1000 10.0 4.1 4.1 4.1 4.1 4.1 4.1 4.1 4.1 4.1 4.1 4.1 4.1

10000 1.0 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4

0.833

(Scrubber 1)

4.166

(Scrubber 1)

Table A. 16. Second scrubber efficiency (%) for first scrubber inlet flow rate of toluene of 10kg/Bx and 50kg/Bx and for several water flow rates

Toluene

(kg/h)

Water

(m3/h) 0 1 2 3 4 5 6 7 8 9 10 11 12

10 42.1 42.0 42.0 42.0 42.0 42.0 42.0 42.0 42.0 42.0 42.0 42.0 42.0

15 60.2 60.2 60.2 60.2 60.2 60.2 60.2 60.2 60.2 60.2 60.2 60.2 60.2

20 74.5 74.4 74.4 74.4 74.4 74.4 74.4 74.4 74.4 74.4 74.4 74.4 74.4

25 84.4 84.4 84.3 84.3 84.3 84.3 84.3 84.3 84.3 84.3 84.3 84.3 84.3

10 41.9 41.7 41.7 41.7 41.7 41.7 41.7 41.7 41.7 41.7 41.7 41.7 41.7

15 60.0 59.8 59.8 59.8 59.8 59.8 59.8 59.8 59.8 59.8 59.8 59.8 59.8

20 74.3 74.1 74.1 74.1 74.1 74.1 74.1 74.1 74.1 74.1 74.1 74.1 74.1

25 84.2 84.1 84.1 84.1 84.1 84.1 84.1 84.1 84.1 84.1 84.1 84.1 84.1

0.833

(Scrubber 1)

4.166

(Scrubber 1)

98

Table A. 17. Overall efficiency (%) for first scrubber inlet flow rate of toluene of 10kg/Bx and 50kg/Bx and for several water flow rates

Toluene

(kg/h)

Water

(m3/h) 0 1 2 3 4 5 6 7 8 9 10 11 12

10 70.8 43.1 42.1 42.0 42.0 42.0 42.0 42.0 42.0 42.0 42.0 42.0 42.0

15 80.0 60.9 60.2 60.2 60.2 60.2 60.2 60.2 60.2 60.2 60.2 60.2 60.2

20 87.1 74.9 74.4 74.4 74.4 74.4 74.4 74.4 74.4 74.4 74.4 74.4 74.4

25 92.1 84.6 84.4 84.3 84.3 84.3 84.3 84.3 84.3 84.3 84.3 84.4 84.3

10 70.6 42.8 41.8 41.7 41.7 41.7 41.7 41.7 41.7 41.7 41.7 41.8 41.7

15 79.8 60.6 59.9 59.8 59.8 59.8 59.8 59.8 59.8 59.8 59.8 59.8 59.8

20 87.0 74.5 74.1 74.1 74.1 74.1 74.1 74.1 74.1 74.1 74.1 74.1 74.1

25 92.0 84.4 84.1 84.1 84.1 84.1 84.1 84.1 84.1 84.1 84.1 84.1 84.1

0.833

(Scrubber 1)

4.166

(Scrubber 1)

Table A. 18. Second scrubber efficiency (%) for actual toluene flow rates entering first scrubber (table A.2) and for several water flow rates

Water

(m3/h) 0 1 2 3 4 5 6 7 8 9 10

10 42.0 42.0 42.0 42.0 42.0 42.0 42.0 42.0 42.1 42.1 42.1

15 60.2 60.1 60.1 60.2 60.2 60.1 60.1 60.2 60.2 60.2 60.2

20 74.4 74.3 74.4 74.4 74.4 74.4 74.4 74.4 74.5 74.5 74.5

25 84.4 84.3 84.3 84.4 84.4 84.3 84.3 84.4 84.4 84.4 84.4

Table A. 19. Overall efficiency (%) for actual toluene flow rates entering first scrubber (table A.2) and for several water flow rates

Water

(m3/h) 0 1 2 3 4 5 6 7 8 9 10

10 70.8 43.0 -1.5 40.4 42.0 62.6 -26.4 -11.5 40.1 59.3 -5.9

15 79.9 60.8 30.3 59.1 60.2 74.3 13.1 23.5 58.9 72.1 27.3

20 87.1 74.8 55.2 73.7 74.4 83.4 44.1 50.9 73.6 82.1 53.3

25 92.1 84.6 72.6 83.9 84.4 89.9 65.8 70.0 83.9 89.0 71.5

99

Table A. 20. Toluene emissions (kg/h) from second scrubber for actual toluene flow rates entering first scrubber (table A.2) and for several water flow rates

Water

(m3/h) 0 1 2 3 4 5 6 7 8 9 10

10 0.4558 0.89 0.63 0.37 0.36 0.82 0.80 0.27 0.14 0.24 0.23

15 0.31 0.61 0.43 0.25 0.25 0.56 0.55 0.18 0.10 0.17 0.16

20 0.20 0.39 0.28 0.16 0.16 0.36 0.35 0.12 0.06 0.11 0.10

25 0.12 0.24 0.17 0.10 0.10 0.22 0.22 0.07 0.04 0.07 0.06

100

A.3. COLUMN DETAILS & COMPONENTS PROPERTIES

Table A. 21. Column details

Height, Z (m) 4.5

Internal diameter, d (m) 0.8

PACKING

Type Polypropylene Pall rings

Nomin al size (mm) 25

Voidage (m 3/m3) 0.9

Surface area (m 2/m3) 215

Loading and flooding parameters FPF (m/s) 0.085

FLQ (m/s) 10.7

Pressure drop factors αααα 225

ββββ 30

Critical surface tension (mN/m) 33 [27]

Table A. 22. Toluene properties

Molecular Weight, MW (kg/kmol) 92

Vapor density (Air=1), ρρρρG (kg/m 3) 3.2 [42]

Diffusion coefficient in air, D T-Air (cm 2/s) 0.0804 [43]

Diffusion coefficient in water, D T-water (cm 2/s) 7.96 × 10-6 [43]

Gas viscosity @ 20 °°°°C, µ µ µ µ (cP) 0.00676 [44]

Toluene solubility in water @ 20 °°°°C (g/g) 0.0005 [45]

Henry’s constant @ 20 °°°°C (mole fraction basis) 258 [46]

Boiling temperature @ 1 atm ( °°°°C) 110.65

Antoine Parameters (P=Pa,T= °°°°C)

A 6.9546

B 1344.8

C 219.43

Table A. 23. Methanol properties

Boiling temperature @ 1 atm ( °°°°C) 64.5

Antoine Parameters (P=Pa,T= °°°°C)

A 7.8975

B 1474.08

C 229.08

Table A. 24. Nitrogen properties


Density @ 20 °°°°C, ρ ρ ρ ρ (kg/m 3) 1.1592 [47]

101

Table A. 25. Water properties


Density @ 20 °°°°C, ρρρρ (kg/m 3) 998.21 [47]

Viscosity @ 20 °°°°C, µµµµ (cP) 1.002 [47]

Surface tension @ 20 °°°°C, σσσσL (N/m) 0.07275 [47]

180

230

280

330

380

430

10 15 20 25 30 35

T (ºC)

Hen

ry's

con

stan

t (

mol

e fr

actio

n ba

sis)

Figure A. 1. Henry’s constant for toluene in water versus temperature [46].

A.4. GRAPHS FOR OPTIMUM DDS UNIT WORKING CONDITIONS

Comp. X conc.=10.02

Figure A. 2. Three-dimensional plot of permeate flow rate vs. crossflow pump setting and vs. transmembrane

pressure (TMP).

102

Comp. X conc.=10.02

Figure A. 3. Three-dimensional plot of permeate conductivity vs. crossflow pump setting and vs. transmembrane

pressure (TMP).

Comp. X conc.=10.02

Com

pone

nt X

Figure A. 4. Three-dimensional plot of component X removal index vs. crossflow pump setting and vs.

transmembrane pressure (TMP).

103

A.5. COMPONENT X CALIBRATION CURVE

y = 0,0012x - 0,0342R2 = 0,9997

0

1

2

3

4

5

6

7

0 1000 2000 3000 4000 5000 6000Conductivity ( µµµµS)

Com

pone

nt X

con

cent

ratio

n (%

w/w

)

Figure A. 5. Component X concentration vs. conductivity.

modelling, design and optimisation of equipment for

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