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Modelling of kraft pulp mill total reduced sulphur emissions Jensen, Allan Stewart 2007

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M O D E L L I N G OF K R A F T P U L P M I L L T O T A L R E D U C E D S U L P H U R EMISSIONS  by A L L A N STEWART JENSEN B . A . S c , University of British Columbia, 1989  A T H E S I S S U B M I T T E D IN P A R T I A L F U L F I L L M E N T O F T H E R E Q U I R E M E N T S FOR T H E D E G R E E OF  D O C T O R OF P H I L O S O P H Y  in  T H E F A C U L T Y OF G R A D U A T E STUDIES  (Chemical and Biological Engineering)  T H E U N I V E R S I T Y OF BRITISH C O L U M B I A October 2007 © A l l a n Stewart Jensen, 2007  Abstract  Atmospheric release of odorous total reduced sulphur (TRS) emissions from kraft pulp mills has been an ongoing concern worldwide. Organic T R S compounds are formed in the digester by ^undesired side reactions during the kraft pulping o f wood. These, along with H S , being highly 2  volatile, are released from mill processes, such as brown stock washing. T R S gases are extremely noxious, described as rotting eggs or rotting cabbage, and have a threshold o f odour detectability in the range o f a few parts per billion. The general objective o f this work was to develop and test a method to predict emissions o f these T R S compounds from kraft pulp mills using a vapour-liquid equilibrium ( V L E ) model. This technique could then be utilized to optimize the process to minimize emissions, or to optimize the design and operation o f T R S control systems. A mill T R S sampling and testing program was conducted around the brown stock washing area o f the Howe Sound pulp mill located in Port M e l l o n , British Columbia. Over 90% o f the sulphur emissions from the T R S compounds were in the form of dimethyl sulphide. This compound was subsequently chosen as a surrogate compound for modelling o f T R S . Analytical testing was done on black liquor and various solutions containing the substances found in the highest concentrations in black liquor, including mixed sodium salts solutions to 6 wt% and lignin mixtures to 6 wt%. The V L E of dimethyl sulphide, in the form o f an activity coefficient, for these solutions was determined using a headspace gas chromatographic method. The adjustable parameters that provided the best fit for the electrolyte non-random two-liquid ( e N R T L ) equation for the experimental activity coefficients were determined using statistical regression techniques.  Simulation software, incorporating a V L E model using the e N R T L  correlation, was used to construct a base-case heat and mass balance representing current operation of the Howe Sound brown stock washing process. This balance was used to evaluate potential process modifications and their effect on T R S emissions.  Table of Contents  Abstract  i  List of Tables  vi  List of Figures  viii  Nomenclature  xii  Glossary  xiv  Acknowledgments  xxiii  Dedication  xxiv  Chapter 1  Introduction  1  Chapter 2  Background  4  2.1  Kraft Pulp M i l l Non-Combustion Source T R S Emissions  4  2.2  T R S Formation  5  2.2.1  Hydrogen Sulphide Formation  6  2.2.2  Organic T R S Formation  7  2.2.3  Kinetics o f Organic T R S Formation  9  2.2.4  T R S Formation in Black Liquor Evaporators  13  2.3  T R S Properties  13  2.4  T R S Health Effects  15  2.4.1  T R S Odour and Health Threshold Levels  18  2.4.2  Odour Detection Threshold  20  2.4.3  Odour Identification Threshold  20  2.4.4  Nuisance Odour Threshold  21  2.4.5  Health Effects Threshold  22  2.4.6  What to Make o f These Threshold Levels?  22  2.5  Kraft Pulp M i l l Environmental Regulations  23  2.5.1  Environmental Guidelines in Canada  23  2.5.1.1 British Columbia  25  2.5.1.2 Alberta  25  . 2.5.1.3 Ontario  26  2.5.1.4 Quebec  27 ii  2.5.1.5 Other Provinces  27  2.5.1.6 Canadian National Pollutant Release Inventory (NPRI)  28  2.5.2  Environmental Guidelines in the U . S . A  28  2.5.3  Environmental Guidelines in Rest o f the World  30  2.6  N C G Collection and Treatment Systems  31  2.7  Kraft M i l l Process Streams  37  2.7.1  37  Chapter 3  3.1  Literature Review  41  T R S Phase Equilibria Behaviour  41  3.1.1  Vapour-Liquid Equilibrium  41  3.1.2  Activity Coefficient Models  45  Factors Affecting T R S Systems  48  3.1.3.1 p H Effects on V L E  49  3.1.3.2 Inorganic Dissolved Solids Effects on V L E  51  3.1.3.3 Organic Dissolved Solids Effects on V L E  51  3.1.3.4 Other Effects on V L E  52  3.1.4  Henry's Constants and Activity Coefficients for T R S  52  3.1.5  T R S Vapour Pressure  58  • 3.1.3  3.2  Black Liquor Composition  Modelling o f the Kraft Pulping Process  58  3.2.1  Computer Software Modelling Tools  60  3.2.2  Previous Work Modelling Non-Combustion T R S Emissions  61  3.3  T R S Emissions Factors  66  3.4  T R S Sampling and Testing Considerations  68  Chapter 4  Research Objectives  71  Chapter 5  Materials and Methods  72  5.1  Gas Chromatographic Equipment  72  5.2  Phase Equilibria Testing  74  5.2.1  Phase Equilibria Testing Method  74  5.2.2  Recovery o f A l k a l i Lignin From Black Liquor  76  5.2.3  Phase Equilibria Sample Solution Preparation  76  5.2.4  Phase Equilibria Testing Procedure  80  in  5.2.5 5.3  5.4  5.5  Chapter 6  Testing o f Solutions for Other Properties  82  M i l l Testing  83  5.3.1  The Howe Sound Pulp and Paper M i l l  84  5.3.2  M i l l Testing Method  86  5.3.3  Sample Collection Procedure  87  5.3.4  Sample Collection Considerations  88  5.3.5  M i l l Testing Procedure  89  5.3.6  M i l l Testing Considerations  91  Activity Coefficient Modelling  95  5.4.1  97  Regression Analysis o f Phase Equilibria Testing Data  V L E Modelling  98  5.5.1  Phase Equilibrium Equation  99  5.5.2  M o l e Balance Equation  100  5.5.3  Energy Balance Equation  100  5.5.4  Temperature (Boiling Point Rise) Equation  101  5.5.5  Solution o f V L E Model  101  5.5.6  Commercial Software V L E Modules  104  Results and Discussion  105  6.1  Phase Equilibria Testing using Published Data  105  6.2  Phase Equilibria Testing Results  110  6.2.1  Other Properties o f Tested Solutions  113  6.2.2  Activity Coefficient as a Function o f Conductivity  115  6.2.3  Activity Coefficient as a Function o f Sodium Concentration  117  6.3  Phase Equilibria Testing Data Regression  121  6.3.1  Fitting o f Henry's Constant Equation  121  6.3.2  Fitting o f N R T L Equation for D M S - W a t e r System  124  6.3.3  Comparison o f N R T L Fit to Other Sources  126  6.3.4  Range o f Validity for Infinite Dilution  128  6.3.5  Fitting o f e N R T L Equation for DMS-Water-Sodium Salts System  6.3.6  Fitting o f e N R T L Equation for H2S-, M M - and D M D S - W a t e r -Sodium Salts Systems  ..  128  131 iv  6.4  6.5  M i l l Sampling and Testing Results  133  6.4.1  Howe Sound Equipment Dimensions and Operating Conditions . . . .  140  6.4.2  Time to Equilibrium for D M S in Black Liquor  144  Modelling of Howe Sound Equipment  146  6.5.1  Model Sensitivity Analysis  147  6.5.2  Equipment Modelling Results for D M S  148  6.5.3  Equipment Modelling Results for other T R S Compounds  152  6.5.4  Equipment Modelling Analysis  154  6.6  M i l l Testing Data Compared to Emission Factors  160  6.7  Howe Sound M i l l Modelling  165  6.7.1  Base-Case Balance o f Howe Sound Process  167  6.7.2  Predicted Effect on D M S Emissions from Process Changes  175  6.7.3  Reducing Brown Stock Washing D M S Emissions  180  6.8 Chapter 7  The Future of N C G Collection Systems Conclusions and Future W o r k  182 183  7.1  Conclusions  183  7.2  Future Work  187  References  189  Appendix A  U.S. E P A Cluster Rule S u m m a r y  206  Appendix B  N C G Collection and Treatment Systems  209  Appendix C  Matlab V L E Module Program  226  Appendix D  N C A S I M i l l Testing Data  235  Appendix E  Phase Equilibria Testing R a w Data  250  Appendix F  Howe Sound M i l l Testing R a w Data  261  Appendix G  Howe Sound M O P S Historian Data  286  v  L i s t of Tables  2.1  Total organic T R S formed during kraft pulping o f softwood (spruce) at a cooking temperature o f 170°C for 1, 2, 3, and 4 hour cooks (kg S/tonne dry wood)  ...  9  2.2  Physical properties o f selected T R S compounds  14  2.3  T R S health effects data  16  2.4  H S threshold concentrations  19  2.5  Ontario POI and A A Q C limits  26  2.6  Typical combined C N C G composition  32  2.7  U . S . E P A typical T R S emissions for C N C G and D N C G sources (ppmv)  33  2.8  N C A S I measured and averaged T R S emissions for C N C G and D N C G sources(ppmv)  34  2.9  Components o f weak black liquor solids (wt% on water-free basis)  38  2.10  Typical inorganic salt composition of black liquor  39  2.11  Elemental composition o f softwood black liquor solids  40  3.1  Henry's constants for hydrogen sulphide in water  54  3.2  Henry's constants for hydrogen sulphide in various salt solutions  55  3.3  Henry's constants for methyl mercaptan in water  55  3.4  Henry's constants for methyl mercaptan in various salt solutions  55  3.5  Henry's constants for dimethyl sulphide in water  56  3.6  Henry's constants for dimethyl sulphide in various salt solutions  56  3.7  Henry's constants for dimethyl disulphide in water  57  3.8  Henry's constants for dimethyl disulphide in various salt solutions  57  3.9  Constants for vapour pressure equation 3.21  58  3.10  U . S . E P A Emissions Factors for Chemical W o o d Pulping  67  5.1  Sodium salt composition used for preparing salt solutions  78  5.2  Dimethyl sulphide solutions used for phase equilibria testing  79  6.1  Methanol(I) in water(j) parameters for N R T L equation  106  6.2  Vapour-liquid equilibrium activity coefficients for D M S solutions tested  Ill  6.3  p H , total dissolved solids, ash, and sodium content o f solutions tested  114  6.4  Conductivities o f alkali lignin mixtures, sodium salt solutions, and black liquor . . . .  115  6.5  Regressed Henry's constants for dimethyl sulphide in solutions tested  121  2  vi  6.6  Regressed N R T L equation parameters for DMS(i)-water(j) system  124  6.7  D M S ( i ) in waterfj) parameters for N R T L equation from other sources  126  6.8  Regressed e N R T L equation parameters for DMS(i)-water(j)-black liquor sodium salts(ca) system  129  6.9  DMS-black liquor activity coefficients  130  6.10  Regressed e N R T L equation parameters for H2S-, M M - and DMDS(i)-water(j)-sodium salts (ca) system  . 132  6.11  M i l l test results for September 16, 2005  134  6.12  M i l l test results for September 21, 2005  134  6.13  M i l l test results for September 22, 2005  135  6.14  M i l l test results for September 28, 2005  135  6.15  M i l l test results for September 29, 2005  135  6.16  M i l l test results for September 30, 2005  136  6.17  M i l l test results for November 22, 2005  136  6.18  M i l l test results for November 23, 2005  137  6.19  M i l l test results for November 24, 2005  137  6.20  M i l l test results for November 30, 2005  138  6.21  M i l l test results for December 1,2005  138  6.22  M i l l test results for December 2, 2005  139  6.23  Equipment dimensions and operating conditions  141  6.24  Root mean square error ( R M S E ) o f V L E model vent vapour concentration  6.25 6.26  prediction  154  V L E model correction factor for systematic error  155  Brown stock washing D M S emission factors  163  6.27  Vapour sample testing data for November 23, 24, 30, and December 1, 2005  168  6.28  Liquid sample testing data for November 23, 24, 30, and December 1, 2005  169  6.29  M O P S historian data for November 23, 24, 30, and December 1,2005  171  6.30  Predicted effect on Howe Sound brown stock washing D M S emissions as a result o f operational or equipment changes  176  vii  L i s t of Figures  2.1  Organic T R S formation as a function o f time for kraft pulping o f softwood (spruce) at 170°C and a sulphidity level of 30.5%  2.2  Organic T R S formation as a function o f sulphidity for kraft pulping of softwood (spruce) at 170°C for 4 hours  2.3  10  11  Organic T R S formation as a function o f H-factor for kraft pulping o f softwood (loblolly pine) at 170°C  12  3.1  Relative volatility o f common kraft mill contaminants  45  3.2  Dissociation o f hydrogen sulphide and methyl mercaptan  50  3.3  Effect on activity coefficient o f methanol due to the presence o f dissolved inorganic and organic matter in black liquor  3.4  Comparison o f methanol vent stack model predictions with m i l l measurements for various process equipment  3.5  64  Comparison o f G E M S prediction versus m i l l data for M i l l E for methanol concentration in the vapour phase  3.6  63  65  Comparison o f G E M S prediction versus mill data for M i l l E for T R S concentration in the vapour phase  66  5.1  Typical gas chromatograph output  73  5.2  Time for a 1 ppm (mol) solution o f D M S in 10 ml o f water in a 24.1 m l sample vial at 90°C to reach equilibrium  5.3  81  Howe Sound m i l l brown stock washing area overview showing liquid sample (LS) and vapour sample (VS) point locations  5.4  85  Gas sampling equipment, including phosphoric acid impinger, Teflon tubing, 3-way valves, vacuum pump and Tedlar bag  87  5.5  Typical sample point (blow tank vent) being tested using the velometer  88  5.6  Typical liquid standard D M S calibration curve at the testing temperature o f 80°C . . .  91  5.7  Degradation o f T R S liquid standard held at 20°C and at an initial concentration of30ppm(mol)  5.8  92  Degradation o f T R S gas standard held at 80°C and at an initial concentration of 5 ppm (mol)  93 viii  5.9  V L E module used to predict emissions o f volatile compounds  5.10  Summary o f V L E module calculation block non-linear equations that require  98  simultaneous solution using a Newton-Raphson or equivalent technique  102  5.11  V L E Module vapour and liquid by-passes  103  6.1  Vacuum drum washer filtrate tank vent stack measured methanol concentration compared to predicted concentration based on outlet filtrate concentration  6.2  Decker washer hood vent stack measured methanol concentration compared to predicted concentration based on inlet wash liquor concentration  6.3  112  Temperature effect on DMS-water activity coefficient at various sodium salts concentrations (solutions 6, 7, and 8)  6.7  112  Temperature effect on DMS-water activity coefficient at various total dissolved solids concentrations in black liquor (solutions 11 and 12)  6.8  116  Activity coefficient at 90°C o f alkali lignin mixtures, sodium salt solutions and black liquor, as a function o f sodium concentration  6.10  119  Sodium concentration effect on DMS-water activity coefficient for sodium salts and black liquor at 50°C  6.13  118  Sodium concentration effect on DMS-water activity coefficient for sodium salts and black liquor at 20°C  6.12  117  Activity coefficient at 90°C (up to 0.5 wt% sodium) o f alkali lignin mixtures, sodium salt solutions and black liquor, as a function o f sodium concentration  6.11  113  Conductivity o f alkali lignin mixtures, sodium salts solutions, and black liquor as a function o f sodium concentration  6.9  110  Temperature effect on DMS-water activity coefficient at various alkali lignin concentrations (solutions 4 and 5)  6.6  109  Weak black liquor tanks vent stack measured methanol concentration compared to predicted concentration based on liquor outlet concentration  6.5  108  Diffusion washer vent stack measured methanol concentration compared to predicted concentration based on inlet wash liquor concentration  6.4  107  119  Sodium concentration effect on DMS-water activity coefficient for sodium salts and black liquor at 70°C  120  ix  6.14  Sodium concentration effect on DMS-water activity coefficient for sodium salts and black liquor at 90°C  120  6.15  Henry's constant for D M S in water as a function o f temperature  122  6.16  Henry's constant for D M S in water as a function o f sodium salts concentration at 40°C and 70°C  6.17  123  DMS-water activity coefficient experimental data and N R T L equation best fit (R = 0.95)  125  2  6.18  Activity coefficients determined from Olsson and Zacchi (2001) N R T L parameters, U N I F A C parameters and best fit to experimental data and holding a^ and a^ constant at zero (R = 0.26)  127  2  6.19  DMS-water-sodium salts activity coefficient experimental data and e N R T L equation best fit (R = 0.95)  129  2  6.20  Comparison of activity coefficient determined from e N R T L equation to black liquor experimental data (solutions 9 to 13)  6.21  131  Activity coefficients determined from the e N R T L equation for the T R S compounds at 80°C  133  6.22  Decker washer at the Howe Sound pulp mill  143  6.23  Time required for D M S phase equilibrium to be established in a black liquor sample heldat80°C  145  6.24  Sensitivity analysis for prediction o f D M S vapour phase concentration  148  6.25  Measured versus predicted D M S concentrations for decker washer filtrate tank N C G vent  6.26  149  Measured versus predicted D M S concentrations for 2  nd  stage diffusion washer  N C G vent  150  6.27  Measured versus predicted D M S concentrations for blow tank N C G vent  151  6.28  Measured versus predicted D M S concentrations for decker washer hood N C G vent . 152  6.29  Measured versus predicted D M D S concentrations for decker washer filtrate tank N C G vent  6.30  153  Comparison between decker washer filtrate tank measured D M S vapour concentration and predicted equilibrium value using the V L E model, and predicted value corrected for systematic error x  156  6.31  Comparison between blow tank measured D M S vapour concentration and predicted equilibrium value using the V L E model, and predicted value corrected for systematic error  6.32  157  Comparison between diffusion washer filtrate tanks measured D M S vapour concentration and predicted equilibrium value using the V L E model, and predicted value corrected for systematic error  6.33  158  Comparison between decker washer hood measured D M S vapour concentration and predicted equilibrium value using the V L E model, and predicted value corrected for systematic error  6.34  159  Total measured H S emissions (left axis) compared to predicted emissions 2  using emission factor (right axis) for brown stock washing process (kg o f sulphur per day) 6.35  161  Total measured organic T R S ( M M , D M S and D M D S ) emissions (left axis) compared to predicted emissions using emission factor (right axis) for brown stock washing process (kg o f sulphur per day)  6.36  Decker filtrate tank emissions based on measured data and predicted using V L E correlations and emission factors  6.37  162  164  Comparison between decker washer filtrate tank measured D M S vapour concentration and predicted equilibrium value using the V L E model, and predicted value using emission factor  6.38  165  Base-case heat and mass balance for the brown stock washing area o f the Howe Sound m i l l  173  6.39  Detailed view o f a blow tank C A D S i m V L E module heat and mass balance  174  6.40  Base-case D M S mass balance for the brown stock washing system of the Howe Sound m i l l ( D M S in kg/day as sulphur)  xi  175  Nomenclature  -  Activity o f component i  a, c  -  Components (anion, cation only, respectively)  a, b  -  N R T L equation parameters (temperature dependency for r)  BPR  K  Boiling point rise  C  -  Ionic charge (absolute value)  C1...C5  -  Extended Antoine vapour pressure equation parameters  ca  -  Salt (composed o f anion, a, and cation, c)  C  -  Specific heat  Co  wt%  Stock consistency  f  kPa  Fugacity  F  mol/s  Feed, inlet flow  G  -  N R T L equation parameter  H  J/mol  Enthalpy  J/mol  Enthalpy o f solution  -  Components (any species, molecular and ionic)  (mol/mol)/MPa  Henry's law constant  Ka  mol/m  A c i d dissociation constant  K  -  Distribution coefficient .  L  mol/s  Liquid, outlet flow  m, m '  -  Components (molecular species only)  n  -  Number o f components  0  -  Standard state  P  kPa  Absolute pressure, vapour pressure  psat  kPa  Saturation or vapour pressure  pH  -  -log[H ]  pKa  -  -log(Ka)  R = 8.314  kPa m / m o l / K  Universal gas constant  S  -  Weight percent solids in a liquid  sat  _  Saturation state  P  A  k  s o l  H  H  3  +  3  xii  T  K  Temperature  'psat  K  Saturation temperature  TDS  wt%  Total Dissolved Solids  V  mol/m  V  mol/s  Vapour, outlet flow  X  -  Liquid phase mole fraction  X  -  Effective liquid phase mole fraction  -  M o l e fraction undissociated  y  -  Vapour phase mole fraction  z  -  Feed flow mole fraction  a  -  Relative volatility / N R T L equation parameter  Y  -  Liquid phase activity coefficient  <f>  -  Vapour phase fugacity coefficient  r  -  N R T L equation parameter  3  Molar volume o f liquid  Xlll  Glossary  AA  Active A l k a l i  AAQC  Ambient A i r Quality Criteria. Ontario government policy.  AAQS  Ambient A i r Quality Standards. Canada government policy.  ACGIH  American Conference of Government Industrial Hygienists.  AA  Active A l k a l i . Concentration o f N a O H plus N a S , expressed as N a 0 .  ADTP  A i r Dry Tonne Pulp  AIHA  American Industrial Hygiene Association.  BADT  Best Available Demonstrated Technology. Alberta government policy.  BDTD  Bone Dry Tonne Per Day  BOD  Biochemical Oxygen Demand.  CADSim  Modeling and simulation steady-state and dynamic software package supplied by  2  2  Aurel Systems o f Burnaby, B . C . Designed specifically for the pulp and paper industry.  CAS  Chemical Abstracts Service. Compilers o f a database o f chemical substance information. A C A S registry number is assigned to a substance when it enters the database. They are assigned in sequential order to unique, new substances identified by C A S scientists.  xiv  CCME  Canadian Council o f the Ministers o f the Environment.  CCOHS  Canadian Centre for Occupational Health and Safety.  CEPA  Canadian Environmental Protection Act.  Chip B i n  N C G liberated from the chip bin. Typically dealt with separately from C N C G and  NCG  D N C G as it is a transitional source that can be below the L E L or above the U E L .  Cluster Rule  U . S . E P A regulations promulgated in 1998 and with full compliance due by 2006. To regulate the release o f H A P to the environment. For the pulp and paper industry, the controlling documents include M A C T I for non-combustion sources and M A C T II for combustion sources.  CNCG  Concentrated Noncondensible Gases.  Also referred to a L V H C N C G .  Malodorous gases collected in a kraft pulp mill that theoretically w i l l be above the U E L . Typically consists o f gases collected from the black liquor evaporator and from the digester relief gas condenser.  Co  Consistency. For example, this may refer to the consistency o f the stock in the product from the digester. Often referred to as percent consistency or % C o .  CWS  Canada-Wide Standards.  DF  Dilution Factor. A term used to quantify washing o f pulp stock. Equals the mass of wash waster over bone-dry mass o f pulp.  DR  Displacement Ratio. A term used to quantify washing o f pulp stock. Equals the mass o f dissolved solids removed from stock over the maximum possible amount available to be removed.  xv  DMS  Dimethyl sulphide. ( C H ) S . A component o f T R S . Also referred to as methyl 3  2  sulphide, D M S and R S R .  DMDS  Dimethyl disulphide. ( C H ) S . A component o f T R S . A l s o referred to as methyl 3  2  2  disulphide, D M D S , and R S S R .  DNCG  Dilute Noncondensible Gases. Also referred to a H V L C N C G . Malodorous gases collected that w i l l theoretically be below the L E L . Typically consists o f gases collected from tankage and washers.  DS  Dissolved Solids. For example, this may refer to the dissolved inorganic or organic matter in black liquor. Often referred to as percent D S or % D S .  EA  Effective A l k a l i  eNRTL  Electrolyte N R T L  EOS  Equation o f State.  EPA  Environmental Protection Agency. U . S . government organization.  EPEA  Environmental Protection and Enhancement Act. Alberta government policy.  ERPG  Emergency Response Planning Guidelines.  ESP  Electrostatic Precipitator. Particulate capture device typically used on combustion vent sources such as recovery boilers.  GC  Gas Chromatograph.  HBL  Heavy Black Liquor xvi  H-factor  A single physical variable that represents the net delignification effect o f both cooking time and temperature during the kraft pulping process.  HS  Hydrogen sulphide. A component o f T R S .  HAP  Hazardous A i r Pollutants. Consists of 188 contaminants, to define air emissions  2  for regulation o f industry by the E P A through the Cluster Rule. H A P is a general grouping o f chemicals that have been identified as causing serious illness, including cancer.  HSGC  HVLC  Headspace gas chromatographic.  High Volume L o w Concentration N C G . A l s o called D N C G .  ICP  Inductively Coupled Plasma  IPST  Institute o f Paper Science and Technology. U . S . organization located in Atlanta, Georgia.  LC50  Concentration o f toxin that w i l l result in a 50% mortality rate in a set exposure time.  LEL  Lower Explosive Limit. The concentration limit below which there are insufficient combustibles to sustain combustion.  LLE  Liquid-Liquid Equilibrium.  LVHC  L o w Volume High Concentration N C G . A l s o called C N C G .  MACT  M a x i m u m Available Control Technology.  xvii  MeOH  Methanol.  Methanol  A l s o known as methyl alcohol, wood alcohol or M e O H . Formed, mainly in the digester, primarily from alkaline hydrolysis o f 4 - 0 methyl glucuronic acid residues in hemicelluloses and to a smaller extent from demethylation o f lignin. A V O C and included in the definition o f H A P . It is used as a surrogate for H A P to determine Cluster Rule compliance.  p,m / p,g  One one-millionth of a metre / gram.  MM  Methyl mercaptan. C H S H . A component o f T R S . A l s o referred to as M M , 3  M e S H , R S H , and methanethiol.  MOE  Ministry o f the Environment. Canadian government ministry.  MOPS  M i l l w i d e Optimization System. Operating data historian system.  mS  1000 m S = 1 Siemen  MSA  Mean Spherical Approximation.  NAAQO  National Ambient A i r Quality Objectives.  NAC  National Advisory Committee.  NCASI  National Council for A i r and Stream Improvement. U . S . pulp and paper industry research organization.  NCG  Noncondensible Gases. A general term for Kraft m i l l odorous gases liberated from non-combustion process equipment in the m i l l . Composed o f T R S , V O C (methanol, terpenes, etc.), air, and water vapour. Subcategories include C N C G ,  xviii  D N C G and Chip B i n N C G . N C G sources are often collected into one or several systems for disposal by chemical modification or incineration.  NIST  National Institute o f Standards and Technology. U . S . federal agency.  NO  Nitrous Oxides. Typically formed during combustion. Mainly nitrous oxide and  x  nitrous dioxide with negligible nitrous oxide. Smog and acid rain causing air emission.  NPRI  National Pollution Release Inventory. Canadian federal government program which requires all industrial facilities to report their emissions to air, land and water.  NRTL  Non-Random Two-Liquid. Activity coefficient model.  OSHA  Occupational Safety and Health Administration. U . S . Government organization.  Paprican  Pulp and Paper Research Institute o f Canada.  Paptac  Pulp and Paper Technical Association o f Canada.  PM  Particulate matter.  PM  2 5  Particulate matter below 2.5 p m aerodynamic diameter.  PM  1 0  Particulate matter below 10 p m aerodynamic diameter.  POI  Point o f Impingement.  Ontario government policy.  ppb / ppm  Parts per billion / million, typically on volume basis when discussing gases.  xix  PvMSE  Root Mean Squared Error  RSC  Reduced sulphur compound.  RSH  Methyl mercaptan  RSR  Dimethyl sulphide  RSSR  Dimethyl disulphide  RTO  Regenerative Thermal Oxidizer. Used to treat thermally oxidize N C G .  SBLOx  Strong Black Liquor Oxidation.  SOG  Stripper O f f Gases. Foul gases liberated from a foul condensate steam stripping system. Consists mainly o f methanol, water vapour and N C G .  SO  x  Sulphur Oxides. Mainly sulphur dioxide and sulphur trioxide. Smog and acid rain causing air emission.  STFI  Swedish Pulp and Paper Research Institute. Located in Stockholm, Sweden.  Sulphidity  The percentage ratio o f N a S to active alkali, expressed as N a 0 .  Sweep air  A i r deliberately drawn into process equipment to "sweep" volatile compounds  2  2  into the N C G collection system. Through stripping action, sweep air can increase emissions o f volatile compounds. Undesired air entering is referred to as tramp air..  Tappi  Technical Association o f the Pulp and Paper Industry. U . S . industry organization.  xx  TDS  Total Dissolved Solids. For example, this may refer to the inorganic and organic matter in black liquor. Often referred to as percent T D S or % T D S .  Tramp air  Unwanted air drawn into process equipment through openings such as leaking flanges, open manholes covers and poorly sealed overflows or inspection hatches. Tramp air w i l l increase the volumetric flow o f N C G collected from the equipment. Through stripping action, tramp air can increase emissions o f volatile compounds. Also referred to as sweep air i f deliberately introduced to the process equipment.  TRS  Total Reduced Sulphur. A general term used to describe Kraft mill odorous bivalent sulphur compounds.  Typically defined as including hydrogen sulphide,  methyl mercaptan, dimethyl sulphide and dimethyl disulphide. Other compounds found in lower concentrations include dimethyl trisulphide, dimethyl tetrasulphide, ethyl sulphide, ethyl disulphide, ethyl methyl disulphide, 2-furfuryl methyl sulphide, and allyl methyl sulphide.  TTN  Technology Transfer Network. Operated by the U . S . E P A .  Turpentine  Sulphate turpentine is a volatile o i l present in wood and liberated during the Kraft pulping process. It is highly combustible.  UEL  Upper Explosive Limit. The concentration limit above which there is insufficient oxygen to sustain combustion.  UNIFAC  U N I Q U A C Functional-group Activity Coefficient. A group contribution method that combines the solution o f functional groups concept and the U N I Q U A C model for thermodynamic design o f highly non-ideal multi-component systems.  UNIQUAC  Universal Quasi-Chemical Activity Coefficient.  xxi  VLE  Vapour-Liquid Equilibrium.  VOC  Volatile Organic Carbon compounds.  WBL  Weak Black Liquor  WBLOx  Weak Black Liquor Oxidation.  WCB  Workers Compensation Board.  WGAQOG  Working Group on A i r Quality Objectives and Guidelines.  WHO  World Health Organization.  xxii  Acknowledgments  This work could not have been completed without a lot o f help and support from many people. First and foremost I would like to thank the members o f my supervisory committee, Drs. Richard Branion, Sheldon Duff, Dusko Posarac and Brian Blackwell for their guidance, support and encouragement. Thank you to the fellow students in my group, Nicole Bennett, Charles Liao and John Ruffel, not only for assistance and encouragement, but for providing good company during those long tedious days in the lab. A n d special thanks to Steve Helle for his advice and assistance with lab procedures; it would have taken a lot longer without someone who knew their way around a G C . Thank you to the Natural Sciences and Engineering Research Council o f Canada who partly funded this research v i a a Industrial Postgraduate Scholarship. Thank you to Bruce Der and A . H . Lundberg Systems Limited for providing time and support for completing this work, and for financial support as the industrial sponsor o f the scholarship. Thank you to Howe Sound Pulp and Paper for providing lab space, equipment, assistance in collecting samples, and access to all data required for this work. In particular, Gerry Pageau for coordinating the m i l l aspects o f this work and co-authoring a paper, and George Zhang, who provided assistance in collection and testing o f samples. Thank you to Paprican for the loan o f testing equipment and advice on procedures. Thank you to Larry Wasik and Aurel Systems Limited for providing copies o f C A D S i m Plus to the University o f British Columbia for research purposes. Thank you to my M o m and Dad for everything. M y Dad passed away in 2002 just before I began the P h D program, but he and my M o m were instrumental in putting me on the path that led to this challenge and their influence during my early years instilled in me the focus and patience required to complete it. They always said I would become an engineer; they were right. A n d finally a very special thank you to Susie, who stood by me in solidarity these last five years. I w i l l endeavour to support her as much as she did me as she works to complete her own doctorate.  xxiii  Dedication  To my Dad, Birger Wolder Jensen  xxiv  Chapter I: Introduction  Chapter 1 Introduction  Kraft pulp mills have historically been associated with foul odour.  Many o f us may  remember the obnoxious odour that was apparent whenever you passed near apulp m i l l , with it often being noticeable from 10 or 20 kilometres away. For a decade from the early 1960's, a significant amount o f research was conducted on the origin o f this foul odour. M u c h o f the impetus for the research was to lower the overall odour effects of a kraft mill, which were found to be caused mainly by reduced sulphur compounds generated as a by-product of the kraft pulping process. The odorous sulphur compounds originate from combustion sources such as the recovery boiler and lime kiln, and from non-combustion sources such as the digester, brown stock washing, and black liquor processing equipment, the latter being the focus o f this research. Emissions for non-combustion sources include the smog and odour-causing volatile organic compounds ( V O C s ) and the odorous total reduced sulphur (TRS) compounds.  These sulphur gases are the main  component o f what give a kraft m i l l its distinctive odour, which has been described as being like rotten eggs or rotting cabbage, but is typically just called "that pulp m i l l " smell. In the late 1960's, pulp mills began to install noncondensible gas ( N C G ) systems, to reduce the impact o f non-combustion emissions (Sarkanen et al., 1970). These were simple end-of-pipe treatment systems, consisting o f collection piping and a fan, designed to collect the vents from the two or three lowest volumetric sources containing the highest concentration o f odour-causing emissions and deliver them to treatment: usually alkaline scrubbing or incineration. During the last decade a number o f mills, typically newly-constructed mills or those undergoing major expansions, installed a second, much larger, odour control system. High volume N C G systems collect vents from up to thirty sources containing lower, but still significant concentrations, o f the odour causing sulphur compounds. The gases are delivered to treatment, typically incineration in an existing mill boiler. Before beginning this doctorate, the author worked for over ten years for A . H . Lundberg Systems Limited ( A . H . Lundberg), designing kraft mill N C G systems. Section 2.6 and Appendix B contain descriptions o f the design o f N C G systems, and the extent that they exist in kraft mills; many of these details are not available in the open literature. These descriptions are primarily based 1  Chapter 1: Introduction  on the author's personal experience, so they are un-referenced. Installation of N C G systems was often driven by. complaints from the general population, usually those living in the vicinity o f the mill. A s ambient odour concentrations were reduced, the residents adapted to the new conditions, with a resulting strong intolerance for a return to the higher concentrations. Efficient operation o f these systems became important because even a short period of venting these N C G s would often draw a litany o f complaints from the nearby residents. The human nose can detect the odorous sulphur compounds at concentrations o f a few parts per billion. Thus, a reduction o f odour to undetectable concentrations in the vicinity o f a mill is probably not achievable. Nonetheless, incremental reduction has been an ongoing focus over the years. Today, there is a wide range o f installed odour control systems, with some mills, often in isolated areas, having none whatsoever, while others, usually in more populated areas, have elaborate systems that collect and treat numerous odorous vent sources. Over time, the focus o f kraft pulp mill air emissions has gradually shifted from basic "nuisance" odour reduction to include a wide variety o f hazardous air pollutants with potentially serious effects to human heath. Historically there have not been any consistent requirements between Canadian provinces or between U . S . states to control odour levels; thus, the installation of N C G systems has been highly location specific. This is changing in the U . S . with the introduction o f new blanket environmental regulations, referred to as the Cluster Rule (U.S. E P A , 1998), that standardize requirements for reduction in air emissions for all U . S . kraft mills. In Canada, community complaints still appear to be the main driving force behind odour reduction, with each mill under more or less pressure depending on its vicinity to a population centre. In a recent Paprican survey o f 24 Canadian mills, 21 mills reported present or recent problems with odorous T R S emissions, with 15 o f these expressing a need for additional information or research in the field (Allen, 1998a). Research continues to better understand kraft mill odour, including this work attempting to model emissions from process systems within the mill. Other areas o f research include modelling emissions from effluent treatment systems (Crawford et al., 2006) and dispersion modelling to better predict ambient air quality near pulp mills (O'Conner and Ledoux, 2002; Freeburn and Redmond, 1998; Jarvensivu et al., 1997). Collection and treatment o f non-combustion sources can be capital intensive, with the need 2  Chapter 1: Introduction  to install N C G collection systems, scrubbers, incineration systems, and tall stacks. These systems can also have significant associated operating costs such as loss of cooking chemicals, consumption of scrubbing chemicals, additional requirements for power, steam, water and fossil fuel, maintenance issues, and lost pulp production due to downtime caused by outages o f these systems. More cost effective methods to reduce odorous emissions may be found either through operational or equipment changes to reduce the formation o f odorous compounds, or through modifications to the design and/or operation of the vent source equipment operation to reduce the quantity of odorous gas released to atmosphere. B y providing a method to model the release of T R S compounds from process equipment, the design of N C G systems could be optimized and the capital and operating costs could be minimized. One method to predict emissions is the use o f simulation software to construct heat and mass balances o f the process. Balances can be constructed using commercially available simulation software packages such as W i n G E M S (Pacific Simulation) and C A D S i m Plus (Aurel Systems), which are widely used in the North American pulp and paper industry. Often, the mill heat and mass balance capabilities o f commercially available software are limited to the liquid and solid phases, mainly because these cover the majority o f the pulping process. The objective o f this work is to extend these balances to include N C G emissions from process equipment and tankage. Emissions can be modelled by incorporating an emissions module, based on vapour-liquid equilibrium ( V L E ) , into the balances. These enhanced heat and mass balance calculations could then be used to optimize the design and operation of N C G systems and to improve emissions reporting. To this end, two testing programs were completed. Analytical testing was conducted in the lab to determine phase equilibria behaviour o f T R S compounds in kraft pulp mill process liquids. A mill sampling and testing program was conducted at the Howe Sound Pulp and Paper Limited Partnership (Howe Sound) m i l l located in Port Mellon, British Columbia, to determine the concentration o f T R S compounds in vapour and liquid streams in the brown stock washing area. This data was used to test and validate a V L E emissions model. To demonstrate an industrial application of this model, a base-case heat and mass balance of the brown stock washing area of the Howe Sound mill was constructed, and the V L E emissions module was incorporated to model N C G emissions. 3  Chapter 2: Background Chapter 2 Background  2.1  Kraft Pulp M i l l Non-Combustion Source T R S Emissions  A i r emissions from kraft pulp mills are often classified into one o f two categories, combustion and non-combustion sources. Combustion sources include the recovery boiler, lime kiln and o i l - , natural gas- and wood-waste-fired power boilers. Non-combustion source emissions include vents from the digester, brown stock washing, evaporators, and tankage for unwashed stock, black liquor and foul condensate. Non-combustion source emissions o f concern include the odorous total reduced sulphur (TRS) compounds, also referred to as reduced sulphur compounds (RSCs), along with the smog and odour causing volatile organic compounds ( V O C s ) . The T R S compounds encountered in the highest concentrations include hydrogen sulphide (H S) along with the organic compounds, methyl 2  mercaptan ( C H S H or M M ) , dimethyl sulphide ( ( C H ) S or D M S ) , and dimethyl disulphide 3  3  2  ( ( C H ) S or D M D S ) (Niemala, 2001; Cook and Hoy, 2003). 3  2  2  These four compounds have historically been used by researchers when discussing T R S in kraft mills; this has generally been accepted as a fairly accurate simplification. Niemala (2001) and Cook and Hoy (2003) identify other T R S compounds besides the four typically studied, although these are usually found in much lower concentrations. These include dimethyl trisulphide, ethyl sulphide, ethyl disulphide, methyl propenyl sulphide, ethyl methyl disulphide, allyl methyl sulphide, allyl methyl disulphide and a previously unidentified disulphide o f the form C H S (or isomer). 3  g  2  O f the numerous V O C s present, methanol typically makes up the largest fraction, followed by acetone and methyl ethyl ketone (Zhu et al., 1999a). Other emissions include wood extractives such as turpentine, chemicals formed during the pulping process, such as ammonia, and chemicals formed during the bleaching process, such as chloroform. Most kraft pulp mills have installed some form of odour control system to collect and treat non-combustion source T R S emissions. These systems are commonly referred to as noncondensible gas ( N C G ) collection and treatment systems. N C G is a general term used by the industry for those gases released from non-combustion process equipment and tankage around a kraft pulp mill during 4  Chapter 2: Background  normal production. The design o f these systems, discussed in detail in Section 2.6, has historically focussed on reduction o f the main odour contributors, the T R S compounds, which are generated in undesired side reactions in the kraft pulping process (Yoon et al., 2003).  2.2  T R S Formation  The formation o f the organic sulphur compounds occurs mainly in the digester. The kraft pulping process consists of "cooking" wood chips in white liquor, a solution o f sodium hydroxide and sodium sulphide in water, in a digester at about 170°C for three to four hours, using a batch or continuous process.  The hydroxide ion and hydrosulphide ion (formed from the hydrolysis o f  sodium sulphide) in the white liquor attack and dissolve the lignin, the "glue" which holds the cellulose fibres together in the wood. The digester product, called brown stock, consists of a mixture of pulp stock and black liquor. The black liquor is composed o f the residual pulping chemicals, dissolved lignin, extractives, and unwanted reaction products.  The main undesirable reaction  products include methanol and the organic T R S compounds. The pulp stock is separated from black liquor in the brown stock washing process, with the pulp stock directed to bleaching, and the black liquor directed to the recovery process, where it is converted back to white liquor. A series of papers on the topic o f T R S formation in kraft digesters was published from the mid 1960's to the early 1970's in Tappi Journal by groups based at the University o f Washington and the University o f Maine (McKean et al., 1965; 1967; 1968: Douglass and Price, 1966; 1968; Douglass et al., 1969; Sarkanen et al., 1970; Wilson and Hrutfiord, 1971; Tsuchiya and Johanson, 1972; Wilson et al., 1972). These groups carried out a series of batch micro-kraft cooks using a 7.5 m L stainless steel digester charged with 1.0 gram o f wood and 4.0 m L o f cooking liquor at temperatures ranging from 150 to 180°C. A t the completion of the cook, the contents were acidified and vapour samples were taken and analysed using a gas chromatograph (GC). Their results, along with those from other researchers, will be discussed below. A t about the same time, Andersson and Bergstrom (1969; 1970) heading up a group at the Royal Institute o f Technology in Stockholm Sweden, published data on the same topic. They also used one gram o f wood and a liquor charge at a 4:1 ratio in 10 m L glass ampoules at a cooking temperature o f 70 to 170°C. The organic T R S compounds were extracted into carbon tetrachloride 5  Chapter 2: Background  and analysed using a G C . Their results agreed quite closely with those from the American groups. In the experiments conducted by all of these groups, the amount o f wood used was very small, and there is some question about how representative the samples would have been, especially when compared to the much larger wood chips used as feed in the industrial process. There were also questions about scale-up and applicability to the continuous process. A couple o f decades later, a group based mainly at the Institute o f Paper Science and Technology (IPST) in Atlanta published another series o f papers on the same topic (Zhu et al., 1999a; 1999b; 2000b; 2001; 2002; Yoon et al., 2003). Their initial work focussed on methanol formation, while their latter work focussed on T R S formation. They used 50 grams o f oven dried wood (mainly loblolly pine) at a 4:1 liquor charge with 18% active alkali on wood and cooking liquor sulphidities ranging from 0 to 30%. Cooking times were varied but cooking temperatures were held at 170°C. The concentrations o f methanol and T R S were measured using an indirect headspace G C method (Chai et al., 1998; 2000). They used a simple linear regression method to determine the relationship between variables and to determine the parameters affecting T R S formation. These parameters were expressed in terms o f the H-factor, a pulping expression that combines cooking time and temperature into one variable (Yoon et al., 2003). A l l of the research conducted on T R S formation was done using a batch process. Continuous digesters are designed as pseudo plug-flow type reactors, and operate under cooking time and temperature conditions, similar to those used for batch digesters; thus, the data for batch digesters were also expected to be relevant to this process. The conclusions reached by these researchers on the mechanism and rate o f T R S formation are summarized in Sections 2.2.1 to 2.2.3.  2.2.1  H y d r o g e n Sulphide F o r m a t i o n  O f the T R S compounds studied, hydrogen sulphide is unique in that it is not an organic compound and it is not formed as a reaction product. The potential for the presence o f hydrogen sulphide exists due to its equilibrium with the hydrosulphide ion. The first step in this process is the hydrolysis o f sodium sulphide to sodium hydrosulphide: Na S+H 0 2  >NaHS+ N a O H  2  6  (2.1)  Chapter 2: Background  The sodium hydrosulphide dissociates in the liquor according to the equilibrium: NaHS<  >Na + H S " +  (2.2)  The hydrosulphide ions in the liquor exist in equilibrium with hydrogen sulphide: HS" + H 0 <  >H S+OH~  2  2  (2.3)  Due to the alkaline conditions o f the kraft pulping process, this equilibrium lies almost completely to the left. Equilibrium conditions will be discussed in detail in Section 3.1.3.1. In strongly alkaline conditions, the hydrosulphide ion can further dissociate to the sulphide ion: >S + H 0  HS" + O H " <  2.2.2  =  2  (2.4)  Organic T R S Formation  Methyl mercaptan and dimethyl sulphide are produced through a series o f reactions in the digester, and also to a lesser extent in other process equipment. Dimethyl disulphide is produced by the oxidation of methyl mercaptan, mainly downstream of the digester where the oxygen content is higher (Douglass and Price, 1966). The rates of formation of methyl mercaptan and dimethyl sulphide are a function o f sulphide and methoxyl concentration and degree o f delignification, along with the related factors, cooking time, temperature, and p H (Andersson and Bergstrom, 1969). The reactions that form these two compounds w i l l only proceed to a measurable degree above about 140°C; thus, the digester, which typically operates at about 170°C, provides ideal conditions for the formation of methyl mercaptan and dimethyl sulphide (McKean et al., 1968). The mechanism for T R S formation has been studied quite extensively and is well understood, with a good overview provided by the University o f Washington group (Sarkanen et al. 1970). Methyl mercaptan is formed by the reaction with a lignin methoxyl group and the sulphide and hydrosulphide ions: lignin • O C H  3  +S  >CH S~ + lignin • O "  =  3  lignin O C H 3 + S H "  >CH SH+ liginin-O" 3  7  (2.5) (2.6)  Chapter 2: Background  The mercaptan is weakly acidic and is soluble in the strongly alkaline kraft liquor, so the two reaction products exist in equilibrium (Shih et al. 1967b): CH SH + OH" <  >CH,S" + H 0  3  2  (2.7)  With the mercaptide ion present, dimethyl sulphide is formed by a sequential reaction with a lignin methoxyl group: lignin - O C H + C H S " 3  > C H S C H + lignin - 0~  3  3  3  (2.8)  Initially, the mercaptan is formed at a constant rate as the sulphide and hydrosulphide ions are responsible for the initial attack on the lignin methoxyl group. A s the concentration o f the resulting mercaptide ion builds up, it attacks the methoxyl group producing dimethyl sulphide and as the reaction proceeds, the mercaptide ion is eventually consumed as fast as it is formed. A t this point in the cook, reported to be at about the three hour mark (Douglass and Price, 1966), the mercaptan concentration w i l l level off while the dimethyl sulphide concentration steadily increases. Dimethyl disulphide, the last T R S compound o f interest, is formed by the oxidation o f the mercaptide ion (Cooper, 1974):  1  2CH S" + - 0 3  +H 0  2  >CH SSCH + 20H"  2  3  3  (2.9)  This last reaction does not occur to any significant extent in the digester, compared to the formation o f methyl mercaptan and dimethyl sulphide. Douglass and Price (1966) speculated that this likely results from the lack o f oxygen in the cooking zone o f the digester due to it being consumed in other reactions before the digester contents reach 140°C. Even though there is some oxygen present in the digester feed from residual air carried through with the wood chips, the hydrosulphide ion w i l l readily consume this oxygen through oxidation to thiosulphate, then onto sulphite, and eventually to sulphate (Cooper, 1974): 2HS" + 2 0 S 0;+0 2  2  >S 0; + H 0  2  2  + 20H"  >2SO: + H 0  2so;; + o — + 2 s o ; 2  8  (2.10)  2  2  (2.11)  (2.12)  Chapter 2: Background  These reactions occur at lower temperatures and consume essentially all of the oxygen before any methyl mercaptan, required for dimethyl disulphide formation, is formed.  A n y dimethyl  disulphide that is found in the system is likely formed in processing equipment downstream o f the digester.  2.2.3  Kinetics of O r g a n i c T R S F o r m a t i o n  Douglass and Price (1966) studied organic T R S formation for two types of softwood, spruce and pine, and two types o f hardwood, birch and maple, at cooking times o f 1, 2, 3, and 4 hours, cooking temperatures o f 150, 160, 170 and 180°C, and initial cooking liquor sulphidities o f 14.7, 22.2 and 30.5% on an active alkali ( A A ) basis. Active alkali is defined as the concentration o f N a O H plus N a S and sulphidity is defined as the percentage ratio o f N a S to active alkali (all 2  2  expressed as N a 0 ) . 2  They reported that an increase in the cooking temperature, cooking time and  sulphidity w i l l increase the formation o f methyl mercaptan and dimethyl sulphide. They also found that more organic T R S compounds are produced when pulping hardwoods rather than softwoods, presumably due to the presence of additional labile methoxyl groups that demethylated rapidly at the beginning of the cook. Their data for spruce at 170°C, converted to a sulphur basis, are summarized in Table 2.1. Table 2.1: Total organic T R S formed during kraft pulping o f softwood (spruce) at a cooking temperature o f 170"C for 1,2,3, and 4 hour cooks (kg S/tonne dry wood) (Douglass and Price, 1966) Sulphidity  Methyl Mercaptan  Dimethyl Sulphide  Dimethyl Disulphide  %on AA  1 hr  2hr  3 hr  4hr  1 hr  2hr  3 hr  4hr  1 hr  2hr  3 hr  4hr  14.7%  0.07  0.14  0.21  0.28  0.03  0.09  0.15  0.24  0.00  0.01  0.01  0.00  22.2%  0.15  0.33  0.47  0.47  0.04  0.12  0.22  0.32  0.01  0.01  0.01  0.03  30.5%  0.28  0.49  0.49  0.68  0.05  0.17  0.27  0.38  0.00  0.01  0.02  0.03  9  Chapter 2: Background  The methyl mercaptan concentration increases as a consequence of Reactions (2.5) and (2.6). After some methyl mercaptan has formed, the dimethyl sulphide concentration w i l l begin to increase by Reaction (2.7). Ultimately, a steady state condition may be reached, at which point the mercaptan is formed and depleted at equal rates and its concentration remains constant ( M c K e a n et al., 1967). The rate of dimethyl sulphide formation w i l l gradually increase, approaching a constant rate at steady state. Due to a lack of oxygen in the digester, formation o f dimethyl disulphide from the Reaction (2.9) is negligible. In Figure 2.1, formation o f the organic T R S compounds is plotted as a function of cooking time. The mercaptan curve should be convex approaching a horizontal line, the dimethyl sulphide curve should to be concave approaching a straight line, and the sum of both of these species should increase in a linear manner (McKean et al., 1967).  1.50 -i  Time (hours) Figure 2.1: Organic T R S formation as a function o f time for kraft pulping of softwood (spruce) at 170°C and a sulphidity level of 30.5% (drawn from data from Douglass and Price, 1966)  The predicted trends appear to be born out in the plotted data. In Figure 2.2, formation o f the organic T R S compounds is plotted as a function o f the sulphidity o f the initial cooking liquor. Linear trends are observed for increasing organic T R S formation with increasing sulphidity.  10  Chapter 2: Background  1.50  r  Sulphidity (%) Figure 2 . 2 : Organic T R S formation as a function o f sulphidity for kraft pulping o f softwood (spruce) at 170° C for 4 hours (drawn from data from Douglass and Price, 1966)  The rate of organic T R S formation is also proportional to the methoxyl content in the system. The lignin methoxyl group is typically very stable and Sarkanen et al. (1970) report that only up to 5% is converted to organic T R S in a typical cook. The increase in T R S formation based on the methoxyl concentration is mainly noticed in the practice of recycling black liquor to the digester. When a batch digester is charged, some black liquor is usually added, along with the white liquor and wood chips. For continuous digesters using the "Lo-Solids" cooking process, black liquor is also recycled to the feed stream. This modified cooking process is used at the Howe Sound mill where testing for this work was conducted. Depending on the amount o f black liquor introduced at the start o f the cook, the methoxyl concentration associated with dissolved lignin in the cooking liquor can be as much as doubled (McKean et al., 1967). This additional methoxyl group is then available to react with the hydrosulphide ion, with a corresponding increase in the formation o f organic T R S .  11  Chapter 2: Background  Y o o n et al. (2003) reported similar results. They presented their data versus H-factor rather than time, thus encompassing the time and temperature factors in one variable, as illustrated in Figure 2.3. The H-factor is a single physical variable that represents the net effect o f both cooking time and temperature during kraft pulping.  340  680  1020  1360  1700  H-factor  F i g u r e 2.3: Organic T R S formation as a function o f H-factor for kraft pulping o f softwood (loblolly pine) at 170°C (Yoon et al., 2003)  The quantity of organic T R S formed increases with increasing cooking temperature, cooking time, sulphide concentration, and methoxyl concentration (increasing black liquor recycle to the digester). For typical digester operating conditions (170°C, 30 % sulphidity, 4 hours, softwood), the formation o f organic T R S ranges from about 1 to 2 kg per tonne o f dry wood (on a sulphur basis), based on the results of all research papers reviewed by the American and Swedish groups. Stated another way, about 2.5 to 5% o f the total sulphur charge is converted to the organic sulphur compounds in the digester. M c K e a n et al. (1967) reported that pulping o f hardwood w i l l result in the formation o f about 30% more T R S than a softwood cook.  12  Chapter 2: Background  2.2.4  T R S F o r m a t i o n in B l a c k L i q u o r Evaporators  Other than the digester, the only other equipment in a mill where the temperature is high enough for the organic T R S formation reactions to proceed, is the black liquor multiple effect evaporator set. The T R S compounds are volatile and thus are almost completely stripped from the black liquor in the first few effects in the evaporator set. Weak black liquor is usually introduced to the back end o f the evaporator set where high vacuums result in boiling at temperatures as low as 70°C. The liquor is then pumped up through each effect to the first effect where the high pressure steam is introduced. A s expected, the effects at the back end of the evaporator set, processing fresh liquor, have the highest concentrations of T R S in the vapour, while the vapour from the middle effects contains almost no T R S . Compared to previous effects, recent mill testing has revealed that there is typically a spike in T R S concentration in the vapour from the first effect or concentrator o f the evaporator set (Jaakkola et al., 1998; Klarin-Henricson, 2004). The liquor solids concentration can surpass 60% in these effects and, due to the boiling point rise, the liquor is processed at a temperature up around 140°C. These conditions are favourable to T R S formation; this spike is attributed to T R S generated in the black liquor in these effects. Although the amount of T R S generated in the evaporator has not been quantified, preliminary results by Klarin-Henricson (2004) indicate that it is minor when compared to T R S generation in the digester.  A s discussed in Section 2.6, the N C G from  concentrated sources, including the black liquor evaporators and concentrators, is typically collected and treated, so quantifying the amount formed in this equipment has not been an industry priority.  2.3  T R S Properties  Table 2.2 lists some common properties o f the T R S compounds; these data were extracted from the C H E M I N F O database available on the Canadian Centre for Occupational Health and Safety website ( C C O H S ) , and from Y a w s ' Handbook of Thermodynamic and Physical Properties o f Chemical Compounds (Yaws, 2006).  13  Chapter 2: Background  T a b l e 2 . 2 : Physical properties o f selected T R S compounds ( C C O H S ; Yaws, 2006) Compound  Hydrogen Sulphide  Methyl Mercaptan  Dimethyl Sulphide  Dimethyl Disulphide  C A S Registry Number  2148875  74-93-1  75-18-3  624-92-0  Structural formula  H-S-H  CH -S-H  CH3-S-CH3  CH3-S-S-CH3  Molecular weight  34.082  48.108  62.134  94.199  Melting point (°C)  -85.5  -123  -83.2  -84.7  Boiling point (°C)  -60.3  5.95  37.3  109.7  Vapour pressure (kPa)  1840 at 21 °C  205 a t 2 1 ° C  56 at 20°C  3.81 a t 2 5 ° C  Vapour specific gravity (compared to air)  1.19  1.66  2.14  3.25  0.99 at -60°C  0.867 at 20°C  0.848 at 20°C  1.063 at 20°C  Solubility in water (g/L)  4.0 at 20°C  23.3 a t 2 0 ° C  6.3 at 20°C  2.5 a t 2 0 ° C  p K a Value a t 2 5 ° C  pKa, = 6.97 p K a = 12.9  p K a = 10.3  does not dissociate  does not dissociate  Critical temp. (°C)  100.4  196.8  230  333  Critical pressure (kPa)  9010  7235  5530  5360  L E L (% by volume in air)  4  3.9  2.2  1.1  U E L (% by volume in air)  46  21.8  19.7  16  Flame speed (m/s)  0.5  0.55  not available  not available  Auto ignition temp. (°C)  260  300  206  >300  Liquid density (g/mL)  3  2  A l l of the T R S compounds have low solubilities in water, and relatively high vapour pressures compared to water. Hydrogen sulphide and methyl mercaptan exist as gases at room temperature, although both will dissociate in alkaline solutions, as shown in Reactions (2.3) and (2.7); in dissociated form at ambient temperature and pressure, they exert negligible vapour pressure. The p H effect is discussed in Section 3.1.3.1. Dimethyl sulphide and dimethyl disulphide exist as liquids at room temperature, although the former exist as a gas at the normal operating temperatures of the kraft pulping process. A l l o f the T R S compounds are flammable and can sustain combustion at a concentration of only a few percent in air and all have relatively low auto-ignition temperatures, 14  Chapter 2: Background  so they are dangerous to handle. A s well as the dangers due to possible fire and explosion, all are toxic with significant adverse health effects.  2.4  T R S H e a l t h Effects  Concern over emissions from kraft pulp mills has historically focused on the nuisance odour they cause in the surrounding community. To counter this, pulp companies began to install odour control systems to collect T R S laden gases to reduce the impact o f emissions to a tolerable level, one that does not cause annoyance to the surrounding population. Odour levels are very difficult to quantify; thus, they are commonly described using these subjective terms. In this discussion, a "nuisance" level is considered synonymous with a level causing "annoyance" or no longer considered "tolerable"; these terms are used interchangeably.  When combined with the term  "threshold", measured on a quantitative scale of "parts per billion volume" or "ppbv," this is defined as the level above which there w i l l be complaints from a significant number of citizens. This level can vary; it is often defined by a local authority for the purposes of regulation. A s an example, California specifies it at the level where 40% o f the population is expected to be annoyed by odour (Shusterman, 1992b). Defining threshold levels is difficult. For example some people may have a more acute sense of smell, a raised sensitivity to the sulphide compounds, a deadened sense of smell through smoking, or a higher tolerance to odour through repeated exposure as an employee at a m i l l .  Another  complicating factor is that a person's threshold level can change depending on the odour level. For example, at a higher concentration, a person's sense o f smell may be deadened, and when the odour level is reduced, their sense of smell returns, and their perceived nuisance threshold level is reduced. T R S compounds are extremely noxious with a low threshold o f odour detectability (Table 2.3). The extreme sensitivity of the human nose to these compounds may be due to the evolutionary process, as trace amounts of these compounds are emitted by decaying protein, serving as a warning signal to toxins present in food that has gone bad (Shusterman, 1992a).  15  Chapter 2: Background  Table 2.3: T R S health ef fects data ( C C O H S ; A C G I H ; Ruth, 986; Tanseyetal., 1981) Hydrogen Sulphide  Methyl Mercaptan  Dimethyl Sulphide  Dimethyl Disulphide  colourless gas  colourless gas  colourless liquid  pale yellow liquid  rotten eggs  rotten cabbage  w i l d radish, cabbage like  disagreeable  1 - 130  1 -41  1 -20  0.8-3.6  Occupational 8-hour exposure limit (ppmv)  10  0.5  Not set by the ACGIH  Not set by the ACGIH  Rat 4-hour inhalation L C 5 0 (ppmv)  444  675  40250  805  Compound  State at room temperature Odour  Odour Threshold (ppbv)  T R S is toxic at high concentrations and has been responsible for a number o f injuries and deaths in pulp and paper mills, mainly in confined space incidents. In a number o f cases, multiple deaths have occurred when rescuers have also succumbed when entering a confined space without respiratory protection while attempting to save an unconscious coworker ( C C O H S ) . The most abundant data available are for H S and thus it is often used as a surrogate when discussing the 2  health effects o f T R S . This seems to be a reasonable simplification as other T R S compounds have similar health effects but appear to be toxic to a lesser degree, based on L C 5 0 studies conducted on rats (Table 2.3).  These studies determined the maximum concentration to which rats could be  exposed for 4 hours that would result in 50% mortality (Tansey et al., 1981). The human nose can detect H S in the range o f a few parts per billion on a volume basis 2  (ppbv). Exposure up to 10 parts per million (ppmv) w i l l affect sensory perception and w i l l cause irritation o f the eyes and throat. The American Conference o f Governmental Industrial Hygienists ( A C G I H ) has established exposure limits for H S o f 15 ppmv for 15 minutes and 10 ppmv for 8 2  hours ( A C G I H ) . These have been adopted by most provincial authorities in Canada, including the Workers Compensation Board ( W C B ) o f British Columbia.  16  Chapter 2: Background  Loss o f the ability to smell H S begins at 50 ppmv and at this concentration there w i l l be 2  severe nose, throat and lung irritation. H S w i l l cause damage to olfactory senses at 250 ppmv, so 2  the presence of the gas can no longer be sensed. Exposure to 250 to 800 ppmv H S w i l l cause severe 2  sickness, permanent damage to the respiratory system and mucous membranes, unconsciousness and then death in 4 to 8 hours. Exposure for 15 minutes at 1000 ppmv can be fatal ( C C O H S ) . Some sources in a kraft m i l l , such as the digester and evaporator vents, typically contain upwards o f 100,000 ppmv T R S (Burgess, 1992; U . S . E P A , 1976). Some local vent sources within the mill are thus extremely toxic. These sources are collected and treated at almost all mills. A t those few mills where these concentrated sources are not treated, the actual vents are piped to a high point in the mill and atmospheric dispersion is used to reduce their concentration to "safe" levels. A number o f studies have been conducted on the effects of pulp mill emissions on the health of the population in nearby communities. The National Council for A i r and Stream Improvement ( N C A S I ) has compiled a number o f these into one report (Tatum, 2001). Even though one o f the studies reports "a higher incidence o f symptoms of eye and upper respiratory tract infection" in children living near a pulp mill in the South Karelia area o f Finland (Marttila et al., 1994), N C A S I states that the results are statistically inconclusive. They conclude that "none o f the kraft pulp m i l l community health studies described here provides any conclusive evidence that the emissions o f a modern pulp mill pose any serious health risk to the residents o f surrounding communities." N C A S I also conducted their own fairly extensive study on the health effects o f T R S and concluded that "although high concentrations o f H S are acutely toxic, exposure to low (less than 2  20 ppmv) concentrations o f H S is not generally associated with significant health effects" (Tatum, 2  1995). The key word here is "significant," as some people had "various physical complaints o f a more subjective nature, such as headaches, nasal congestion, fatigue and eye and throat irritation." The "mechanism(s) ...is uncertain", with some research suggesting "that such symptoms may be psychologically-based responses to the perception of unpleasant odors," while others have suggested that "odorant chemicals are capable of triggering neurological events leading to the development o f physiologically-mediated symptoms." If N C A S I , a research organization mainly funded by the pulp and paper industry, appears to downplay the health impact of pulp mills on the community, then these views are balanced by those expressed by Neil Carman, a clean air director for the Sierra Club. He stated, in a news release on 17  Chapter 2: Background  the Sierra Club website (Sierra), that "public health scientists now recognize that hydrogen sulphide is a potent neurotoxin, and that chronic exposure to even low ambient levels causes irreversible damage to the brain and central nervous system." Because the evidence is inconclusive regarding the effects o f T R S at the very dilute concentrations found in ambient air near pulp mills, the focus has historically been on the nuisance factor o f these odours in the surrounding community. This appears to be a reasonable approach, since reducing the T R S concentrations to a tolerable level, i.e., to the 10s of ppbv, would likely also be a concentration well below that which most scientists and health officers would be concerned about the adverse health effects.  2.4.1  T R S O d o u r and H e a l t h T h r e s h o l d Levels  Thresholds are a difficult thing to quantify, given their subjective nature. The first threshold is the concentration at which most people can detect an odour, the second is when most people can identify the substance causing the odour, the third is when this odour becomes a nuisance and the fourth threshold is when the substance adversely affects health.  A l l o f these thresholds can have  wide ranges, even overlapping, depending on the substance and local circumstances. Since most is known about hydrogen sulphide and since it can make up a significant fraction o f T R S , it is often used as a surrogate for T R S when discussing threshold levels. The range of interest appears to be about 1 ppbv, at which point these odours can be detected, to 10,000 ppbv, the maximum 8-hour exposure level specified by the A C G I H (Table 2.3). This is presumably the concentration above which adverse heath effects would become apparent, although it is in many ways meaningless since many workers would refuse to work in those conditions. M i l l s in Canada typically set their H S alarms in work areas at around 2500 ppbv, at which point people 2  must evacuate the area. Even approaching this concentration, the odour is significant and would generate numerous complaints among workers. I have observed that Canadian mill workers would not enter a work area i f the odour concentration, as measured on a handheld H S detector, was above 2  about 500 ppbv, and even near this level they would be reluctant. concentrations are summarized in Table 2.4.  18  Various H S threshold 2  Chapter 2: Background  Table 2.4: H>S threshold concentrations ppbv H S 2  1  Threshold Odour detection lower limit  4.5  Odour recognition lower limit World Health Organization ( W H O ) : "odour nuisance"  5 5 - 10  Typical ambient near mill with L V H C N C G and H V L C N C G collection systems  10-40  Canadian provincial Ambient A i r Quality Objectives ( A A Q O s )  30 30-80 100+  California objective: "assumes only 40% o f people annoyed" Typical ambient near mill with only L V H C N C G collection system Typical ambient near mill with no N C G collection system  100  American Industrial Hygienist Ass.: "transient adverse health effects"  110  W H O : "health hazard"  500  Typical maximum workplace concentration tolerated in a pulp m i l l  2500  Typical alarm setting for ambient detectors in pulp mills  10000  W C B and O S H A maximum 8-hr exposure limit  The highest ambient T R S concentrations can usually be found in the m i l l production areas, but mill workers acclimatize to these odour levels. Leach and Chung (1982) collected a total o f 1645 gas samples from four locations within eight B . C . pulp mills. O f the areas tested, they found the highest T R S concentrations around the digester, and o f the T R S compounds, they found dimethyl sulphide in the highest concentrations. The normal range for dimethyl sulphide was measured at 0.5 to 6.0 ppmv, with a peak o f 64 ppmv. The normal range for total T R S was 1.0 to 8.3 ppmv, with a peak of 73 ppmv. The Leach and Chung study is over two decades old and much progress has been made in odour reduction within mills, but it does give some idea to what extent people w i l l acclimatize to an unpleasant working environment. There is certainly an acceptance among m i l l workers and others dependant on the mill for their livelihood that they must put up with a certain level o f odour as part o f a means to earn a living. The presence of a mill brings prosperity to the area and provides jobs; thus, the odour in and around the mill is tolerated. 19  Chapter 2: Background  The actual ambient air concentrations in the geographical area surrounding the mill can vary widely depending on the actual amount of contaminants released and the dispersion characteristics. The dispersion w i l l depend upon many factors such as the number, location and height of stacks, the wind direction and velocity, topography such as valleys and hills, and climate conditions causing such things as inversions. Older mills with only rudimentary odour collection systems may create T R S concentrations up to 100 ppbv at distance o f 1 to 2 kilometers from the m i l l (O'Conner and Ledoux, 2002). A similar sized mill with a more complete odour collection system may create ambient T R S concentrations o f only 5 ppbv under similar circumstances (Jarvensivu et al., 1997; Freeburn and Redmond, 1998). It may be impossible to eliminate odour completely from kraft pulp mills, but well operated mills using the latest technology can get close.  2.4.2  O d o u r Detection Threshold  Odour detection thresholds for T R S compounds are given in Table 2.3. The odour detection for hydrogen sulphide ranges from 1 to 130 ppbv, with this variance depending on the olfactory sensitivity o f the observer.' For example, a smoker living in a pulp mill town w i l l likely not detect the odour until it reaches a much higher concentration than a trapper living in the northern wilderness. Prolonged exposure to low concentrations may cause olfactory fatigue. A s well, the sense o f smell may be damaged from short term exposure to higher concentrations. It is not known to what extent the different T R S substances may be cumulative when it comes to odour detection. It seems likely that the mixed compound odour threshold would be near 1.0 ppbv i f each o f the four T R S substances was at 0.25 ppbv level, but no research on this topic could be found in the literature.  2.4.3  O d o u r Identification Threshold  Odour identification levels are typically somewhat higher than detection levels. For example a recognition threshold o f 4.5 ppbv is given by the same source referenced for detection levels o f 1  20  Chapter 2: Background  to 130 ppbv in Table 2.3. That said, this threshold does not hold much importance to this issue as most people don't care what it is they smell, only that they know it smells bad.  2.4.4  Nuisance O d o u r T h r e s h o l d  The World Health Organization ( W H O ) has specified guidelines for half-hour exposure o f 5 ppbv for "odour nuisance" for H S (Shusterman, 1992b). They have obviously set this level on the 2  basis that i f you can smell it, then it is a nuisance. California has established an Ambient A i r Quality Standard ( A A Q S ) for H S that is "based on the endpoint of odour annoyance" (Shusterman, 1992b). 2  They state that this standard, 30 ppbv on a one hour average, is set at approximately four times the population-mean odour threshold for hydrogen sulphide. Their assumption in establishing this standard was that approximately 40% of the population is expected to be annoyed at this odour level. What complicates defining a nuisance threshold is that not only is it different between people (eg. smokers and non-smokers), but it can be different for each person based on the initial conditions. For a person in a pristine environment exposed to an increasing odour, their threshold is likely to be much lower than someone acclimatized to a high concentration that is lowered. This can result from a desensitizing effect o f the odour substance, either by simply getting used to it, or a physiological effect where the sense of smell is temporarily or permanently damaged. There are also varying responses to reduction in odour, with the nuisance threshold level often a moving target.  For a community member in a pulp mill town, lowering the odour  concentration may result in them becoming more sensitive to the odour, and thus their threshold level is lowered as the concentration is lowered. A t mills which have installed odour control systems, a short term venting incident will often result in numerous complaints, whereas previously the local population tolerated long term higher concentrations. The nuisance threshold can be related to the next level since there is evidence that odour alone can have adverse health effects.  Shusterman (1992a) o f the E P A stated that "noxious  environmental odours may trigger symptoms by a variety o f physiologic mechanisms, including exacerbation o f underlying medical conditions, innate odour aversions, aversive conditioning phenomena, stress-induced illness, and possible pheromonal reactions."  21  Chapter 2: Background 2.4.5  Health Effects Threshold  W H O has specified guidelines for 24-hour exposure o f 110 ppbv for "health hazard" (Shusterman, 1992b).  The Emergency Response Planning Guidelines (ERPGs) issued by the  American Industrial Hygiene Association ( A I H A ) in 2001 specify three levels for exposure to H S . 2  The lowest level, E R P G - 1 , is specified at 100 ppbv, and is defined as "the maximum airborne concentration below which it is believed that nearly all individuals could be exposed for up to 1 hour without experiencing other than mild transient adverse health effects or perceiving a clearly defined, objectionable odour" ( C C O H S ) . The U . S . Occupational Safety and Health Administration ( O S H A ) and the Workers Compensation Board ( W C B ) o f B . C . have set a maximum average 8-hour occupational exposure level o f 10000 ppbv ( C C O H S ) .  The two orders o f magnitude difference between the levels  specified by W H O and A I H A for maximum ambient conditions and the exposure level set by O S H A and W C B for the workplace is eye-opening. This highlights the lack of scientific data available regarding the health effects o f long term exposure to hydrogen sulphide and exposes the somewhat arbitrary nature o f these limits.  2.4.6  W h a t to M a k e o f T h e s e T h r e s h o l d L e v e l s ?  Odour problems generate a significant fraction of the publicly-initiated complaints received by the polluter and air pollution control authorities. Given the predominantly subjective nature o f associated health complaints, Shusterman (1992b) stated that "given our current state of knowledge, any differential regulatory response to environmental odour pollution, which is based upon the distinction between community annoyance reactions and health effects, is a matter o f legal - not scientific - interpretation." He appears to be saying that given the inconclusive evidence of adverse health effects at the dilute concentrations in question, regulations for emissions should be set based on annoyance levels within the community rather than on perceived health effects. Based upon the above data, we can comfortably reduce our range o f discussion for the ambient air concentration o f T R S near pulp mills from 4 orders o f magnitude (1 to 10000 ppbv) to two orders (1 to 100 ppbv). It is obvious that ambient concentrations above 100 ppbv, i.e. a mill 22  Chapter 2: Background  with no odour control system or one that frequently vents their system to atmosphere, w i l l generate numerous complaints, while ambient concentrations around 5 ppbv, i.e., a m i l l with a complete well operated system, will generate very few complaints (Jarvensivu et al., 1997; Freeburn and Redmond, 1998; O'Conner and Ledoux, 2002). The goal is to define the range o f the nuisance threshold within this two orders o f magnitude range; it appears that this is the range o f discussion for most regulators.  2.5  Kraft Pulp M i l l Environmental Regulations  The most stringent environmental regulations with respect to pulp and paper making facilities are in North America and Europe, although what is defined as pollutants, how much is allowed to be released, and how they are regulated, vary greatly, not only from country to country, but between states, provinces, and even districts and regions. Some regulators refer to parts per billion on a volume basis (ppbv), while others refer to pg/m . For H S , the most commonly regulated compound, 3  2  1 p g / m o f H S in air equals 0.717 ppbv at standard conditions o f 25°C and 101.325 kPa. 3  2  2.5.1  E n v i r o n m e n t a l Guidelines in C a n a d a  Both provincial and federal statutes govern environmental legislation in Canada. Provinces exercise proprietary rights over the resources and therefore have the right to legislate on all aspects of water and air use and contamination. In general, each mill is regulated on an operating permit issued by the local region and these requirements differ greatly not only from province to province, but from mill to mill within provinces. Federally, the release of contaminants to the environment is regulated by the Health Act, the Fisheries A c t and the Canadian Environmental Protection Act ( C E P A ) .  National Ambient A i r  Quality Objectives ( N A A Q O ) are maximum contaminant concentrations set with the goal o f protecting public health, the environment, or aesthetic properties o f the environment.  These  concentrations are set by the National Advisory Committee ( N A C ) Working Group on A i r Quality Objectives and Guidelines ( W G A Q O G ) , a group comprising representatives o f federal, provincial and territorial departments o f environment and health. 23  Chapter 2: Background  Historically, there has been a three-tiered structure for defining air quality objectives, maximum desirable (tier 1), maximum acceptable (tier 2) and maximum tolerable (tier 3). The first tier was defined as ambient air quality for residential areas, the second tier for industrial locations and the third tier as an unacceptable level requiring action. The listing for hydrogen sulphide under N A A Q O specifies tier 2 limits o f 15 p.g/m for a 1 hour average and 5 p.g/m for a daily average. 3  3  These figures were extracted from the document "The Table o f National Ambient A i r Quality Objectives and Guidelines", undated, available on the federal government website (Canada Government). The three-tiered structure is being phased out in favour o f a single tiered system used by most countries. In 1998, the Canadian Council of Ministers of the Environment ( C C M E ) signed the CanadaWide Accord on Environmental Harmonization and its sub-agreement on Canada-Wide Standards ( C W S ) . These standards are intended to be achievable targets that will reduce environmental risks within a specific time-frame.  It is not clear why two, apparently similar, standards have been  developed, but the C C M E website states that "air pollutants that have been identified by governments as needing to be managed will be targeted for either N A A Q O or C W S development, not both." Thus, as would be expected since it is already listed under N A A Q O , hydrogen sulphide is not listed under the C W S document "Canadian Environmental Quality Guidelines," updated 2002, available on the C C M E website ( C C M E ) . The numerous Canadian objectives and standards and the provincial guidelines discussed below are not legally binding. Emissions to the environment are enforced through permits issued by the provincial regional authority authorizing companies to discharge contaminants into the air. The objectives and guidelines only become legally binding i f they are written into the individual mill operating permit. Federal air quality documents refer only to H S , with no mention o f any o f the 2  organic T R S compounds. This is also true for provincial documentation, with the exception o f Ontario.  24  Chapter 2: Background  2.5.1.1 B r i t i s h C o l u m b i a  In British Columbia, emissions to land, water and air are regulated under the provisions o f the Environmental Management Act. A s part o f this act, each mill is regulated on an operating permit issued by the local region.  These permits may specify maximum T R S , N O , S O and x  x  particulate emissions from designated equipment or identified stacks. Since there are no uniform provincial guidelines for collection and treatment of kraft pulp mill air emissions, there is a huge diversity in type and scope of collection and treatment systems installed at B . C . mills. The installed systems range from one mill having no collection and treatment whatsoever, to another mill collecting N C G from about twenty sources. Geographical location, weather conditions, proximity to populated areas, vintage o f the mill and political factors have an influence on the extent o f the emissions control systems installed in a particular mill. Some provinces, including B . C . , specify general ambient air quality objectives in the vicinity of pulp mills, although, as previously mentioned, these are not legally binding. B . C . air quality objectives and standards also use a three-tiered system (level A , B , and C ) roughly corresponding to the Canadian tiered objectives. A t the industrial " B " level, pulp and paper mills in B . C . capable of demonstrating that the H S concentration in ambient air does not exceed 28 p g / m on a one hour 3  2  average and 6 pg/m on a daily average at monitored stations (whose location are undefined), are 3  considered to be in compliance. These figures are extracted from the document " A i r Quality Objectives and Standards," undated, available on the provincial government website (British Columbia Government).  2.5.1.2 A l b e r t a  Alberta's ambient air quality guidelines are established under Section 14 o f the Environmental Protection and Enhancement A c t ( E P E A ) ; all documentation is available on the provincial website (Alberta Government). The purpose o f this act is to ensure that emissions are minimized through the use o f Best Available Demonstrated Technology ( B A D T ) and that residual emissions are dispersed so that the guidelines are met. Alberta has graduated to the one tier system and mills are judged to be in compliance i f the H S concentration in ambient air did not exceed 14 2  25  Chapter 2: Background  pg/m on a one hour average and 4 | i g / m on a daily average at monitored stations as specified in 3  3  the document "Alberta A i r Quality Guidelines," dated February 2000. Alberta also has an additional guideline for "static" H S , defined as a maximum one month accumulated loading of 0.10 mg S 0 2  3  equivalent per day per 100 c m land area.. 2  2.5.1.3 O n t a r i o  Ontario has similar guidelines to B . C . and Alberta, but with more detail as they also refer to the organic T R S compounds. The enabling legislation is Regulation 346 o f the Environmental Protection Act, which specifies maximum ambient Point of Impingement (POI) limits and Ambient A i r Quality Criteria ( A A Q C ) for over 350 substances.  These are detailed in the document  "Summary of Point o f Impingement Standards, Point o f Impingement Guidelines and Ambient A i r Quality Criteria ( A A Q C s ) " dated September 2001, available on the provincial website (Ontario Government). A A Q C standards can also be set for 10 minute, daily and annual averages, but for T R S , it has only been set for the 1 hour average listed in Table 2.5.  Table 2.5: Ontario POI and A A Q C limits (Ontario Government) Hydrogen Sulphide  Methyl Mercaptan  Dimethyl Sulphide  Dimethyl Disulphide  POI Vi hour limit (pg/m )  30  20  30  40  AAQC 1 hour limit (p.g/m )  30  20  30  40  Compound  3  3  The POI standards are those used for compliance monitoring of industrial facilities. The POI limits are typically derived by mathematical scaling, from A A Q C s which represent human health or environmental effects-based values. The POI monitoring locations are not specified in the guidelines; instead, they are determined on a mill to mill basis for each operating permit issued by the local authorities. Typically, the location for these criteria w i l l be defined as the property limit, but in cases where the mill is located in more populated areas, the monitors may be placed in a "sensitive" location such as at an 26  Chapter 2: Background  elementary school or hospital.  The location o f the monitoring stations and the prevailing wind  direction have a great influence on whether the POI limits are met. A recent study by the Sierra club reported that for air pollution violations in Ontario during 2001 (the latest statistics available), kraft pulp mills held at least the top six slots (the list included only six) with the highest having 90 violations for that year alone (MacDonald and DeMarco, 2004).  2.5.1.4 Q u e b e c  Quebec pulp mills are regulated under schedule III of the "Reglement sur les fabriques de pates et papiers Q-2, r.12.1," available on the provincial website (Quebec Government). This legislation is legally binding and is much more detailed than the regulations for the other provinces, with emission limits specified for individual process equipment. The legislation states that all mechanically vented emissions from cooking systems, evaporation systems, condensate stripping systems and brown stock washing systems that have concentrations higher than 10 ppmv T R S must be collected and treated. The result of this requirement is a large variability in installed systems and the effectiveness of these systems between mills. For example, tank vents do not require collection unless they are "mechanically" vented, presumably using a fan. A s well, a mill with an open hood and a large ventilation fan on a brown stock washer drawing in large volumes o f tramp air can stay below the limit while another mill with a sealed hood and a lower vent volume w i l l have to install a collection and treatment system. This may be the case in spite of the fact that the first m i l l , all else being equal, emits more T R S on a weight per time basis due to the stripping effect on the volatile substances. Quebec also has an air quality objective stating that the ambient air quality should not exceed 10 ppbv T R S at the mill property limit.  2.5.1.5 O t h e r P r o v i n c e s  The other provinces have similar policies to those discussed for B . C . , Alberta, Ontario and Quebec, although with some variance. There appears to be a move to standardizing the provincial guidelines based on the Canadian objectives; this was one of the driving forces behind the formation of the C C M E . Most provincial ministries appear to be adopting the approach o f stipulating T R S 27  Chapter 2: Background  emission levels at the mill property limit or other monitored stations and allowing each company to install facilities that best meet the guidelines.  2.5.1.6 C a n a d i a n N a t i o n a l P o l l u t a n t R e l e a s e I n v e n t o r y ( N P R I )  Federally, under C E P A , the National Pollutant Release Inventory (NPRI) was established in 1992. This program is a legislated, nation-wide, publicly-accessible inventory of pollutants released to the environment. It was created to provide Canadians with information on pollutants released from facilities in their communities. It is meant to assist governments to identify priorities for action, encourage industries to take proactive measures to reduce releases, allow for tracking o f progress in reducing releases and support regulatory initiatives. This program requires all industrial facilities to report their emissions to air, land and water, i f the reportable substances used or produced onsite exceed given threshold limits in quantity or concentration. The latest "Guide for Reporting to the N P R I " is dated 2005 and is available on the Environment Canada website (Canada Government). This document lists over 300 substances that require reporting, including hydrogen sulphide, but not the organic T R S compounds. N P R I states that facilities are allowed to calculate their reportable releases in either o f four ways, listed in order of preference (Allen, 2002): (i) direct measurement, (ii) mass balance calculations, (iii) emissions factors, or (iv) engineering estimates. The last option is not defined, but is presumably based on an expert consultant's experience.  2.5.2  E n v i r o n m e n t a l Guidelines in the  U.S.A.  The U . S . Environmental Protection Agency ( E P A ) uses the term Hazardous A i r Pollutants ( H A P ) , which includes 188 contaminants, to define emissions for regulation of pulp and paper mills. H A P is a general grouping o f chemicals that have been identified as causing serious illness, including cancer.  The regulations associated with H A P are typically referred to as the "Cluster  Rule," regulated under the Maximum Achievable Control Technology ( M A C T ) emissions standards document, available on the E P A website (U.S. E P A , 1998). Non-combustion sources, which are regulated under M A C T Part I, were promulgated in 28  Chapter 2: Background  A p r i l 1998 at which point a three and eight year countdown began for achieving these standards. The portion covering combustion sources such as the recovery boiler, smelt dissolving tank, lime kiln, and power boiler, are regulated under a separate document referred to as M A C T Part 2, which was promulgated in October 2005, at which time a three year countdown for compliance began. The E P A lists the following as the H A P compounds emitted in the highest quantities on a mass basis in a typical kraft m i l l : • Methanol  • Methylene chloride  • Methyl ethyl ketone  • Phenol  • Propionaldehyde  • 1,2,4-Trichlorobenzene  • o-Xylene  • Acrolein  • Acetaldehyde  • o-Cresol  • Carbon tetrachloride  • Chloroform  • Cumene  • Formaldehyde  Some o f these substances may be in higher or lower concentrations at some mills depending on the specific process. For example, chloroform emissions from a mill using a chlorine-free bleaching process would probably be insignificant. Volatile Organic Compound ( V O C ) emissions, which are linked to smog formation through chemical reaction with nitrogen oxides ( N O ) , are another group x  which are of particular concern. These compounds, by definition, are highly volatile, so escape into the atmosphere easily. Many V O C s , but not all, are listed as H A P . Recent research aimed towards Cluster Rule compliance has focussed on methanol since it typically makes up a large fraction o f H A P and has thus been designated as a surrogate compound. Although methanol may make a good surrogate for the H A P compounds, it is not a good surrogate for the T R S compounds due to their much higher relative volatilities, as discussed in Section 3.1. A number of volatile substances emitted in relatively high quantities, such as the terpenes, are not included in H A P . Presumably, this is because they are wood extractives, and thus considered a "natural" emission rather than a manufactured chemical release.  Most o f the turpentine  compounds can easily be condensed and are a potentially valuable by-product, either as a fuel or for sale to a refining plant; therefore, many mills practice turpentine recovery. Not only are terpenes highly volatile, but in the liquid phase they can be very toxic and can cause upsets in the effluent treatment system i f released in large quantities. None o f the T R S compounds are among those defined as H A P , even though they are obviously hazardous, as discussed in Section 2.4. 29  It is not clear why these compounds were  Chapter 2: Background  excluded from the national regulations, but it may have been a political decision as T R S release was already being regulated through local state operating permits.  Although the Cluster Rule  requirements do not pertain directly to T R S , a correlation can be made with reduction in H A P to reduction in T R S , since the targeted emission sources that are high in H A P are also typically high in T R S ( N C A S I , 1994a; 1994b; 1996; 2002b). That said, there may soon be a direct link because hydrogen sulphide may eventually be classified a H A P . The E P A is presently being lobbied by "130 public health and environmental organizations and community groups," including the Sierra Club, to "formally list hydrogen sulfide as a hazardous air pollutant," as reported on their website (Sierra). This has renewed interest in research in the area of hydrogen sulphide release, particularly from effluent treatment lagoons, l n the U . S . , the National Council for A i r and Stream Improvement ( N C A S I ) , in 2003, began an ongoing program o f study on this topic (Cook and Hoy, 2003; Crawford et al., 2006). There has also been some pressure on the E P A to include the organic T R S compounds in H A P , but the consensus seems to be that this will occur in the longer term, at least 10 years down the road. More details are provided in Appendix A regarding the Cluster Rule M A C T Part 1. These details have been extracted and summarized from the hundreds o f pages that make up the actual Cluster Rule document. There has been speculation about the potential for U.S. companies to seek a requirement for Canadian competitors to meet the Cluster Rules (Vice, 1998). T w o concerns were expressed: (a) a trade barrier in the form o f a border tax on products crossing into the U . S . or; (b) Canadian companies unable to secure cross border contracts until they meet the same environmental criteria as U . S . mills. To date, there is little evidence to suggest that this may be the case, but once U . S . mills complete their upgrades, there may be political pressure for Canadian mills to follow.  2.5.3  Environmental Guidelines in Rest of W o r l d  There are many kraft mills besides those in North America, with the largest number located in Brazil, China, Indonesia and the Scandinavia countries. The latter are generally perceived to have some o f the strictest standards and regulations. In Finland, a new amendment to the A i r Pollution A c t came into force in A p r i l 1996 30  Chapter 2: Background  (Hynninen, 1999). Kraft pulp mills must ensure that ambient air quality in the vicinity o f the m i l l does not exceed 10 p g / W T R S (as sulphur) as the second highest daily value of one month, meaning that a mill is allowed to exceed this limit for one day per month. It also requires that total gaseous sulphur emissions from pulping processes be less than 2 kg/t (as S 0 ) for new and rebuilt mills. The 2  amendment also has limits for carbon monoxide, nitrogen dioxide, sulphur dioxide, total suspended particulate and respiratory particulate ( P M ) , all in terms o f pg/m ambient air quality. 3  ]0  In Sweden, no general standards are applied at present (Hynninen, 1999).  Instead, the  authorities grant a specific environmental discharge permit to each m i l l . Typical restrictions include maximum annual average gaseous sulphur emissions of 0.5 kg/t (as sulphur), a minimum availability of odour control systems o f 99% (venting o f odorous gases limited to 1% o f time that the mill process is operating), maximum H S concentration in the recovery boiler stack o f 10 mg/m (normal 3  2  dry gas, maximum o f 5% of time exceedance allowed per month), as well as limitations on nitrogen oxides, sulphur oxides and particulate from the recovery boiler, lime kiln, power boilers, etc.  2.6  N C G Collection and Treatment Systems  In most countries, in order to meet air quality requirements, it is necessary to collect noncondensible gases ( N C G ) from various emission sources into one or several systems for disposal by chemical modification or incineration. A s discussed in the previous section, environmental regulations governing kraft pulp mills are highly dependent on the local regulatory authority; thus, worldwide there is a huge variability in the extent o f installed N C G systems. This can range from no odour control system whatsoever, to very elaborate systems collecting up to thirty vent sources (Pinkerton, 1999; Bruce and V a n der Vooren, 2003; A . H . Lundberg). N C G is a general term used by the industry for those gases released from non-combustion process equipment and tankage in a kraft pulp mill during normal production.  The use o f  "noncondensible" is applied somewhat inaccurately, since, of all the major components o f N C G , nitrogen and oxygen are the only two that fit the definition. Noncondensibles are defined as being above their critical temperature.  The critical temperature o f a material is the temperature above  which distinct liquid and gas phases do not exist. A s the critical temperature is approached, the properties of the gas and liquid phases become the same. The critical pressure is the vapor pressure 31  Chapter 2:  Background  at the critical temperature. Above the critical temperature, there is only one phase. The noncondensible components o f N C G often enter the system as "tramp" air through openings in tanks and equipment hoods. The other components o f N C G , including water vapour, methanol, turpentine, and the T R S compounds are vapours that have been volatilized from brown stock, black liquor, or foul condensate in the process. For safety reasons, because most o f the volatile components are also flammable, to avoid handling of explosive gas mixtures, it is common practice to segregate the vent sources into so called Concentrated NonCondensible Gases ( C N C G ) , also referred to as L o w Volume High Concentration ( L V H C ) N C G , and Dilute NonCondensible Gases ( D N C G ) , also referred to as High Volume L o w Concentration ( H V L C ) N C G collection systems (Burgess, 1992). In such an arrangement, the combustible components of the N C G are generally to be found in concentrations above the Upper Explosive Limit ( U E L ) in the C N C G system and below the Lower Explosive Limit ( L E L ) in the D N C G system (Table 2.2). The lack o f oxygen in C N C G , typically as low as 8% by volume, also contributes to maintaining the mixture above the U E L . In Table 2.6, Burgess (1992) provides a typical analysis for C N C G combined from various sources. He states that composition w i l l vary widely from system to system, and occasionally within the same system.  Table 2.6:  Typical combined C N C G composition (Burgess, 1992) % by volume  Compound Hydrogen sulphide  1.7  Methyl mercaptan  2.1  Dimethyl sulphide  2.1  Dimethyl disulphide  1.7  Turpentine  0.1  Methanol  0.2  Water vapour  6  Nitrogen  77.2  Oxygen  8.9  32  Chapter 2: Background  This variability in concentration is illustrated by the U . S . E P A (1976), who provide typical concentration ranges for C N C G and D N C G sources shown in Table 2.7.  Table 2.7: U . S . E P A typical T R S emissions for C N C G and D N C G sources (ppmv) (U.S. E P A , 1976) Hydrogen Sulphide  Methyl Mercaptan  Dimethyl Sulphide  Dimethyl Disulphide  Batch digester blow gases  0 - 1000  0 - 10,000  100-45,000  10-10,000  Batch digester relief gases  0 - 2000  10-5,000  100-60,000  100-60,000  Continuous digester  10-300  500- 10,000  1500 - 7,500  500 - 6,000  600 - 9000  300 - 3,000  500 - 5,000  10- 10,000  Drum washer hood  0-5  0-5  0 - 15  0-3  Washer seal tank  0-2  10-50  10-700  1 - 150  Black liquor oxidation  0-10  0-25  10-500  2-85  Source  CNCG  Evaporator DNCG  When companies are considering the installation o f N C G systems, they w i l l sometimes do sampling and testing o f vent sources to assist in the design process. This data, often considered sensitive, is typically not published in the open literature. Often, the testing is conducted by an industry research organization such as N C A S I or Paprican. These organizations publish technical reports which are only available to member companies and to some educational organizations. In one such report, N C A S I compiled T R S emissions data from all testing they had conducted during the preceding decade ( N C A S I , 2002). The emission figures in Table 2.8 are averaged from up to 24 mills.  33  Chapter 2: Background  N C A S I measured and averaged T R S emissions for C N C G and D N C G sources (ppmv) ( N C A S I , 2002b) ,  T a b l e 2.8:  Source  H S 2  MM  DMS  DMDS  avg.  avg.  avg.  avg.  avg.  range  Batch digester blow gases  3702  54100  35971  632  95000  64 to 683000  Batch digester relief gases  452  4678  4481  456  10500  10500 to 10600  Continuous digester  122  4128  2072  935  8200  26 to 34000  Evaporator  65281  69766  32874  2321  173000  17 to 719000  Combined C N C G  17639  42282  20292  1493  83200  1730 to 701000  Drum washer hood (open)  1  2  12  3  21  2 to 84  Drum washer hood (sealed)  2  8  209  20  260  Oto 1950  0.4  1  371  58  490  4 to 3340  Weak black liquor storage  9  7  134  18  190  9 to 650  Strong black liquor storage  340  2259  1085  370  4430  9 to 22600  7  7  14  19  66  7 to 180  32  9  178  16  250  81 to 440  T R S as S  CNCG  DNCG  Unbleached pulp storage  Black liquor oxidation  Combined D N C G  34  Chapter 2: Background  In general, the averaged concentration data presented by N C A S I falls into the concentration ranges specified by the U . S . E P A . There are a few inconsistencies. The U . S . E P A ranges for dimethyl disulphide appear high and their concentration ranges for all species for evaporators appears low. The N C A S I data for combined C N C G sources also agree quite well with the typical C N C G concentrations given by Burgess (Table 2.6) although, again, with dimethyl disulphide too high. C N C G sources w i l l always include the two highest emitters, the digester and the evaporator, and sometimes the blow tank, turpentine recovery system, foul condensate tank and foul condensate stripping system. A C N C G system collects the highest emitters into a relatively small system, with this system collecting roughly 80% of the odorous substances emitted from non-combustion sources. Without a C N C G system, the ambient air T R S concentration near a m i l l w i l l typically be in the 100s of ppbv; all but two mills in Canada have these systems installed. A mill with a C N C G system w i l l typically have ambient air conditions near the mill in the range o f 30 to 80 ppbv T R S (O'Conner and Ledoux, 2002), although this depends greatly on vent stack heights and local climatic conditions. Typical D N C G sources include the continuous digester chip bin, diffusion washer, brown stock washer, decker washer, knotter hood, screen hood, black liquor oxidizer, soap skimmer, sewer vent and tankage such as the filtrate, stock, knot, screen feed, screen rejects, refiner feed, black liquor, spill, soap, tall oil, precipitator mix and chemical ash mix tanks. These systems collect the numerous lower concentration emitters into a relatively large system and, combined with a C N C G system, w i l l typically reduce ambient air conditions around a mill to less than 10 ppbv T R S (Freeburn and Redmond, 1998; Jarvensivu et al., 1997). Appendix B includes a more in-depth discussion o f C N C G and D N C G collection and treatment system design and operation. In the U.S., partial compliance with the new Cluster Rule, required as o f A p r i l 2001, was typically achieved with the installation o f C N C G and foul condensate collection and treatment systems. Full compliance, which was required as o f A p r i l 2006, typically required installation o f a D N C G system. The extent of installed D N C G systems at Canadian mills is highly dependent on mill location, with the main dependency being political, i.e., in which province the mill is located. For example, Alberta has strict H S ambient air quality standards (presumably originating from flaring 2  at oil refineries and sour gas processing but covering all industrial facilities); thus, all pulp mills in 35  Chapter 2: Background  Alberta have extensive C N C G and D N C G collection systems. This contrasts with the only kraft pulp mill in Manitoba which has no N C G systems whatsoever. In Ontario, all mills installed C N C G systems in the 1970s, but only two mills operate D N C G collection systems, these having been only recently constructed. Within each province, each m i l l is issued an operating permit by the local regional authority. Due to pressure from local citizens and town councils, mills located near urban centres often have more extensive odour control systems.  This may not be only a result o f a larger population  generating more complaints,, but also differing social demographics. In large urban centres, there may be a higher population o f people with little invested in the mill (i.e., those that do not depend on the mill for their livelihood), environmental activists, or those with political influence. Local climate and topography have a large influence on permitting and thus on N C G system design. Climate has an impact, mainly in the form o f prevailing wind direction. M a n y mills are located downwind o f the local community, a pattern repeated so often that one suspects the owners deliberately located them in this way. Even though this may seem preferable, when the wind direction does change and blow into the community, more complaints may be triggered because the severe change in ambient air quality is often more noticeable than a constant odour. Climate issues also include inversions where dispersion into the upper atmosphere is inhibited and the odorous compounds are pushed down towards the ground. Topography has a significant effect; hills and mountains or ocean or river currents can affect local air flow and atmospheric dispersion patterns. Another factor influencing the operating permit of a mill is its vintage. Older mills w i l l often have a "grandfathered" operating permit; they are allowed to exceed provincial objectives because the mill was constructed under previous laxer standards. More recently-constructed mills have been required to engineer for D N C G systems during planning stages, often as a result o f community consultation processes, before they receive their development permit. The last Canadian mills to be constructed or go through major rebuilds, in the late 80s and early 90s, are located in Castlegar, Kamloops, and Port M e l l o n in British Columbia, Boyle and Peace River in Alberta and Windsor in Quebec. A l l these mills have extensive D N C G systems. There does not appear to be an accepted methodology in the industry for estimating T R S emissions. Designers of N C G systems typically rely on limited field testing, and in the absence o f this, in-house engineering estimates based on previous systems installed at similar mills (Burgess, 36  Chapter 2: Background  1992; A . H . Lundberg). A more accurate, yet relatively inexpensive method of predicting emissions is to use simulation software to construct mass balances across the equipment, and validate and tune this model using mill testing data. One method to predict vent emissions using simulation software is to incorporate an emissions module based on the vapour-liquid equilibria of the target contaminant in kraft mill liquid process streams.  2.7  K r a f t M i l l Process Streams  T R S can be found in many mill process streams including black liquor and foul condensates. Foul condensates originate from condensing vapour from the digester extraction black liquor flash tanks and from the black liquor evaporators., Foul condensates consist mostly o f water, but are referred to as foul because they also contain odorous compounds such as turpentine, methanol and T R S . Foul condensates only contain dissolved solids when there is carryover of liquor droplets with the vapour to the condensing surface.  Black liquor contains many different dissolved solids,  including many salts.  2.7.1  Black Liquor Composition  Wash water is used counter-currently in the brown stock washing process.  The total  dissolved solids in the wash water increases as it passes through each washing stage. The filtrate from the final wash stage is combined with the black liquor from the digester and sent to the evaporators. The total dissolved solids in weak black liquor is typically in the region o f 15 wt%, but can reach as high as 20 wt%. Table 2.9 shows a typical analysis for softwood black liquor from three mills (Grace et al., 1989), on a water-free basis.  37  Chapter 2: Background  Table 2.9: Components o f weak black liquor solids (wt% on water-free basis) (Grace et al., 1989) Component  Mill A  Mill B  Mill C  Lignin  28.9  30.7  31.1  Hemicellulose and sugars  1.14  0.11  1.3  Extractives  6.69  2.53  5.7  not measured  not measured  18.8  Acetic acid  3.52  2.08  5.2  Formic acid  4.48  2.7  3.1  Other organic acids  5.5  2.22  0  Unknown organic compounds  19  29.5  5.8  Inorganic salts  18.6  18.5  20.3  Organically combined N a  10.1  10.3  8.7  Unknown inorganic compounds  2.08  1.35  0  Saccharinic acids  The saccharinic acids were not measured for M i l l A and B ; these would be included in either "other organic acids," or "unknown organic compounds." Lignin is a natural branched polymeric macromolecule, present in most species o f plants. In wood, lignin consists o f a three dimensional, cross-linked network comprised mainly o f phenylpropane units connected by ether linkages or carbon-carbon bonds (Ohman, 2006). The lignin structure also contains methoxyl and phenolic hydroxyl groups. During kraft pulping, the alkali and sulphide attack the lignin and polysaccharides in wood, reducing their molecular size and dissolving them.  The degradation of lignin is due mainly to the cleavage o f ether linkages between the  phenylpropane units. Most o f the alkali used in pulping is consumed in neutralizing the acidic phenolic groups on the lignin and its degradation products, the organic acids formed from the polysaccharides, and the resin acids. Post degradation, the lignin fragments, referred to as alkali lignin, diffuse out into the black liquor, dissolved as sodium phenolates. The other dissolved organic matter in black liquor consists the sodium salts of the polysaccharinic acids, resin acids and fatty acids.  38  Chapter 2: Background  The phenolic hydroxyl groups of alkali lignin are characterized by p K ' s of 9.4 to 10.8. When the black liquor p H is in this range, alkali lignin w i l l precipitate. Because o f the heterogeneous nature o f alkali lignin, this effect comes on gradually, proceeding from a slow thickening at higher p H values, to actual precipitation at lower values (Grace et al., 1989). During kraft cooking, some sulphur becomes irreversibly bound to the dissolved lignin, decreasing the overall hydrosulphide concentration in the cooking liquor. M c K e a n et al. (1968) found that the sulphur lost to lignin to be a maximum o f 0.4%, while at the same time stating that others estimate the loss to vary from almost negligible up to 3%. Ideally, the total hydrosulphide concentration through the cook w i l l only decrease by the reactions to organic T R S plus the amount lost to the lignin, i.e., the sum o f 2.5 to 5% and 0 to 3%, for a total loss o f 2.5 to 8%. In practice, the amount o f hydrosulphide lost during the cook and in downstream processing equipment is typically in the range of 30 to 40% due to oxidation reactions to thiosulphate, sulphite and sulphate (Grace et al., 1989). A typical breakdown o f the inorganic salts in black liquor is shown in Table 2.10 (Grace et al., 1989). The concentrations o f sodium salts in kraft liquors are often given in terms of N a 0 . To 2  convert these to actual concentrations, multiply by their molecular weight and then divide by the molecular weight o f N a 0 . For example, to convert N a S from g/L as N a 0 to g/L, multiply by 78 2  2  2  and divide by 62.  Table 2.10: Typical inorganic salt composition o f black liquor (Grace et al., 1989) wt% (median)  g/L as N a 0  g/L as N a 0  g/L as itself  (range)  (median)  (median)  NaOH  1.0-4.5  1.4  1.8  4.6  Na S  1.6-5.6  4.2  5.3  13.4  Chemical  2  2  2  Na C0 2  3  5.0-12  7.8  13.3  33.7  Na S0 2  3  0.4-3.8  2  4.1  10.3  Na S0  4  0.5-6.0  2.8  6.4  16.2  1.8-5.1  3.4  8.7  21.9  2  Na S 0 2  2  3  39  Chapter 2: Background  The elemental composition o f the black liquor is also o f interest. Table 2.11 shows the typical values o f the elemental composition o f virgin black liquor derived from  softwood  (Vakilainen, 1999).  Table 2 . 1 1 : Elemental composition o f softwood black liquor solids (Vakilainen, 1999) Element  Typical amount (wt%)  Typical range (wt%)  Carbon  35  32 to 37  Hydrogen  3.6  3.2 to 3.7  Nitrogen  0.1  0.06 to 0.12  Oxygen  33.9  33 to 36  Sodium  19  18 to 22  Potassium  2.2  1.5 to 2.5  Sulphur  5.5  4 to 7  Chlorine  0.5  0.1 to 0.8  Inert matter  0.2  0.1 to 0.3  A s w i l l be discussed in Chapter 3, the presence o f the dissolved inorganic solids has a significant impact on the vapour-liquid equilibrium o f the T R S compounds.  40  Chapter 3: Literature Review Chapter 3 Literature Review  3.1  T R SPhase Equilibria Behaviour  Emissions o f T R S are contingent on the inter-phase mass transfer between the liquid (e.g. black liquor) and the vapour (e.g. N C G vent). In this case, a flux of the T R S compounds w i l l begin with a transfer from the liquid to the vapour, but as more T R S enters the vapour phase, with a consequent increase in concentration within the vapour, the rate at which T R S returns to the liquid increases, until eventually the rate at which it enters the vapour is exactly equal to that which it leaves. A t the same time, through the mechanism o f diffusion, the concentrations throughout each phase become uniform and a state o f dynamic equilibrium is said to exist. If the flux between phases is not limiting, the release o f volatile substances from process equipment in a kraft pulp mill can be modelled based on their vapour-liquid equilibria. Thermodynamic models to describe vapour-liquid equilibria are well established and detailed descriptions can be found in many reference sources (Balzhiser et al., 1972; Perry's, 1997). The description below is a condensed version for the specific case of a low pressure water-based system.  3.1.1  Vapour-Liquid Equilibrium  For a system to be in thermodynamic equilibrium, it will be at a state o f maximum entropy, or lowest possible Gibbs free energy. Classical thermodynamics can provide relationships based on Gibbs energy and chemical potentials, but these are defined in relationship to internal energy and entropy, both quantities for which absolute values are unknown. Models, based on what is known as molecular thermodynamics, have been created to relate these variables to one  another.  Homogenous systems at internal equilibrium can be modelled using these macroscopic properties expressed as functions o f temperature, pressure and composition. One of these macroscopic properties is called fugacity, f, which represents the tendency o f a component to leave a phase (Jugare in Latin means escape). Phase equilibrium exists at a given temperature, T, and pressure, P, when each component shows the same chemical potential in the 41  Chapter 3: Literature Review  vapour and liquid phases.  From this criterion it can be deduced that the fugacities o f each  component are equal in each phase when equilibrium prevails: f, (T,P,y,)= f, (T,P,x,) v  f  v f  L  (3.1)  is the fugacity and y is the mole fraction o f component i in the vapour phase, and f^ and x  represent the same for the liquid phase.  Since many real mixtures are not ideal solutions, a  thermodynamic variable called "activity" was introduced to facilitate calculations. The activity, a, of component i is defined as: a, = | r  (3-2)  The fugacity, fj , is the fugacity o f component i at the standard state, 0. The most commonly used 0  standard state, and the one used here, is the pure component at the same temperature, pressure and phase as the mixture.  Two further thermodynamic variables based on the activity were also  introduced, the vapour phase fugacity coefficient, 0„ and the liquid phase activity coefficient, y„ defined by the following equations:  These coefficients are used to relate fugacity to measurable quantities such as temperature, pressure, molar volume and composition. They are a measure of the deviation o f the fugacity from its standard state. The most computationally straightforward and thermodynamically consistent method for calculating phase equilibria is to choose an equation o f state (EOS), such as the ideal gas law, to calculate the fugacity o f the vapour phase. A t higher pressures, a cubic E O S , such as the PengRobinson equation or Soave-Redlich-Kwong equation, should be used, but near atmospheric pressure, as is the case for this work, it is reasonable to assume that gases form ideal mixtures. The  42  Chapter 3: Literature Review  vapour standard state is pure gas at the temperature and pressure of the mixture. If the ideal gas law is used, the vapour phase fugacity coefficient is set to unity: f, = ^ y , f , ' ° = y , P v  (3-5)  v  Although good for hydrocarbon systems, equations o f state have proved inadequate for modelling solutions with strong interactions in the liquid phase, such as aqueous mixtures o f polar compounds. The phase equilibria of dilute aqueous solutions are therefore treated differently from those o f dilute organic systems, due to water's  unique structure  and  hydrogen-bonding  characteristics. For aqueous systems, liquid phase behaviour can be described using the activity coefficients and a liquid standard state o f the pure liquid at the temperature and pressure o f the mixture: ,(P-P, ') s a  f  L  f  Pj  Sat  = Yhfi*  = KXiPrexp  RT  (3.6)  is the saturation or vapour pressure and v is the molar volume, of species i at temperature, T.  The exponent term, referred to as the Poynting correction, accounts for the pressure induced deviation o f fugacity from its saturated state. A t low pressures, including this work at or near atmospheric pressure, this factor approaches unity and can be taken as 1.0. A t equilibrium, when the vapour and liquid phase fugacities are equal, it follows that the controlling equation for vapour-liquid equilibrium is: y P=y x P i  i  i  i  (3.7)  This equation relates the partial pressure of the compound in the vapour phase to the vapour pressure exerted by the compound in the liquid phase at the system temperature. Since ideal behaviour is assumed for the vapour phase, the compound vapour pressure is simply the product o f the vapour phase mole fraction, y, o f compound i , and the total pressure, P. The pressure exerted by the compound in the liquid phase is the product of the liquid phase mole fraction, x, o f compound i , and the saturated state vapour pressure, Pj , "corrected" by the activity coefficient, Y J . This approach Sat  presumes knowledge of the vapour pressure o f each species at the temperature o f interest. Correlations for the vapour pressure o f all o f the T R S compounds are given in Section 3.1.5.  43  Chapter 3: Literature Review In an ideal system, the activity coefficient is unity, and the above equation reduces to Raoult's law.  In most real situations the activity coefficient deviates significantly from unity due to  interactions between molecules in multi-component systems. Equation (3.7) also reduces to Raoult's law at the extreme limit where compound i approaches 100% concentration and the total pressure equals the vapour pressure o f this compound. A t the other extreme, where the concentration o f compound i approaches zero, this equation can be simplified to Henry's law: y.p=-j^ K  (3.8)  H i  Henry's law states that the concentration o f a solute gas in solution is directly proportional to the partial pressure of that gas above the solution, related by the Henry's constant, k . The Hi  accuracy of Henry's law increases as the liquid phase concentration o f the solute decreases; thus, it is often used to describe the solubility o f gases such as nitrogen and oxygen, which almost always exist in very low concentrations in the liquid phase o f water-based systems. Henry's law can also be used to describe any substance at very low concentration, typically in the range of parts per million, often referred to as the condition o f "infinite dilution." The distribution coefficient, K , is defined as the ratio between the vapour and liquid mole fractions for each component: K  (3.9)  = —  {  This term defines the volatility o f an individual substance. The relative volatility, a, o f a substance, is defined as the ratio between the vapour and liquid molar fractions for the solute compared to the solvent. For an aqueous system, the former is referred to as the contaminant and the latter as water:  «i-wa,er  =  ~ ^  = water  ~  ( * water  X.  44  water  3  -  1  0  )  Chapter 3: Literature Review  The relative volatility of an aqueous system defines the relative ease with which the contaminant can be stripped from water, with the temperature dependency for common kraft mill contaminants shown graphically by Blackwell et al. (1980) in Figure 3.1.  50  85  120  155  190  T E M P E R A T U R E , °F  F i g u r e 3.1: Relative volatility o f common kraft mill contaminants (Blackwell et al., 1980)  3.1.2  A c t i v i t y Coefficient M o d e l s  The activity coefficient, V j , for substance i in a solution can be estimated using a number o f correlations such as the Wilson equation developed by Wilson (1964), the non-random two-liquid ( N R T L ) equation developed by Renon and Prausnitz (1968) and the universal quasi-chemical 45  , Chapter 3: Literature Review  ( U N I Q U A C ) equation developed by Abrams and Prausnitz (1975).  These models are able to  represent, with a reasonable number o f adjustable binary parameters, the phase equilibria o f highly non-ideal non-electrolyte systems. Experimental measurements must be carried out to determine these binary parameters; unfortunately, available data are limited. Lohmann and Gmehling (2001) state that there are about half a million binary systems o f interest to the chemical industry and V L E data for less than 6000 have been published. If experimental data are unavailable, group contribution methods can be used to predict the activity coefficient.  The U N I Q U A C functional-group activity coefficient ( U N I F A C ) model,  developed by Fredenslund et al. (1975) and the newer Modified U N I F A C (Dortmund) model developed by Weidlich and Gmehling (1987) combine the solution o f a functional group concept and the U N I Q U A C model. The group contribution method is based on the concept that a molecule consists of different functional groups, such as C H , O H , or C H , and that the thermodynamic 3  properties of a solution can be correlated in terms of these functional groups. The advantage of this method is that a very large number o f mixtures can be described by a relatively small number o f functional groups. The disadvantage, when compared to the other models, is that the parameters are not fitted from actual experimental data for the molecular solutions, so accuracy may be sacrificed. The addition o f salts can alter the phase equilibria behaviour o f systems containing one or more solvents. These effects include changing the vapour pressure for single solvent electrolyte systems and alteration o f relative volatilities for mixed solvent electrolyte systems.  Many  correlations have been proposed to describe the effect o f salts on the vapour pressure o f mixed solvent electrolyte systems. Good overviews of empirical and semi-empirical equations that can be used for industrial applications are provided by Renon (1986), Leohe and Donohue (1997) and Anderko et al. (2002). In general, these models contain several contributions that determine the excess Gibbs free energy including: a short-range term represented by models developed for non-electrolyte systems, such as the N R T L equation discussed above; a long-range term represented by an equation based on Debye-Huckel or mean spherical approximation ( M S A ) theories; and an equation based on the Born model for the electrostatic contribution to ion solvation (Chen and Song, 2004). The most well established electrolyte model is the electrolyte N R T L ( e N R T L ) equation developed by M o c k et al. (1986).  This model extends the N R T L equation to include electrolytes 46  Chapter 3: Literature Review  through the addition o f solvent-salt binary parameters; therefore it builds on the extensive databank of solvent-solvent parameters available for the N R T L model.  The e N R T L equation is the  recommended option when using Aspen Plus (Aspentech), one of the simulation software packages used to model the results of this work.. The e N R T L equation is based on the idea that for relatively dilute electrolyte solutions, the interactions between the ions and the solvent can be represented locally and then generalized to the entire solution; thus, a long-range Debye-Huckel term and a Born term are not required. M o c k et al. (1986) found that this approach reproduces experimental activity coefficients very well for dilute and moderately concentrated (up to 3 M ) solutions o f strong electrolytes.  A n updated and  comprehensive overview o f the e N R T L model was given by Chen and Song (2004). In this latest work, a Debye-Huckel term and a Born term were included to extend the accuracy o f the e N R T L model to the entire concentration range. The e N R T L equation, incorporating adjustable binary parameters, AT and r, is expressed as follows:  ZX Hr )=~ m  J  J  Ix  G  jm  G km  k  X  jm  ZX  •G  m  mm  Z  m  X  k  k  'GknV , V  '  a  £ X  k  •G  k m  . • r . km  S x - G km' k k  IXk'G c  k  mm  kc.ac  Zx -G  - Gkc.ac  k  k i  kc.ac  (3.11)  kc.ac  k  Zx -G k  ^  \p  a '  ma.ca  47  r  mc.ca  Z X  kaxa  k  -G  ka,ca  k a c i  Chapter 3: Literature Review  For the e N R T L equation, the subscript m includes any solvent species, while the subscript c and a refer to the cation and the anion, respectively, of any ionic species. The subscripts i , j and k are defined as any species including both solvent and ionic. For molecular species, Xj = x while for j5  ionic species, Xj = C^x,, where Cj is the absolute value of the charge number o f ion i . The parameter G is determined from the energy parameter, r, and the non-randomness factor, a. G ^ e x p ^ - r , , )  (3.12)  If the temperature is varied, r c a n be modelled using the adjustable parameters a and b:  ^  =  a  ,i + Y  ( - ) 3  13  It should be noted that in the absence of electrolytes, the e N R T L equation reduces to the N R T L equation, i.e., the first two terms o f Equation (3.11). Binary parameters for the N R T L equation are available from reference books and published articles for some solvent pairs, although, as discussed in Section 3.1.4, there are limited data for the T R S compounds in water. The data that do exist for T R S compounds suggest that the activity coefficients are large, ranging from about 20 for hydrogen sulphide up to about 1000 for dimethyl disulphide in water at 80°C (Blackwell et al., 1980); thus, they are said to have positive deviations from Raoult's law.  Because the T R S  compounds have relatively high vapour pressures and large activity coefficients, they are considered highly volatile; i.e., a relatively low concentration in the liquid phase w i l l be in equilibrium with a relatively high concentration in the vapour phase.  For example, based on Figure 3.1, for a H S 2  water solution at 80°C under a sealed air space at atmospheric pressure, 1 ppm o f H S in water w i l l 2  be in equilibrium with about 1500 ppm H S in the vapour phase. 2  3.1.3  Factors Affecting T R S Systems  For a system including T R S in water there are a number o f factors affecting V L E including: (i) p H effects, e.g., dissociation of hydrogen sulphide and methyl mercaptan in alkaline black liquor solutions, (ii) "binding" of these substances with metal and lignin ions in the liquor, (iii) the presence of electrolytes which alter phase equilibria, e.g., salting-in and salting-out effects o f the pulping chemicals, (iv) reactions, e.g., oxidation o f methyl mercaptan, (v) local physical constraints, e.g., 48  Chapter 3: Literature Review  incomplete mixing or stratification in tankage, (vi) "tramp air" ingress, and (vii) insufficient time to reach equilibrium.  3.1.3.1 p H E f f e c t s o n V L E  In electrolyte systems, molecular species can remain undissociated, or dissociate partly or completely in solution. This phenomena is important to the determination of V L E since, near ambient temperature and pressure, the vapour pressure o f ionic liquids is negligible, and only the undissociated fraction contributes to the vapour pressure (Earle et al., 2006).  O f the T R S  compounds, hydrogen sulphide and methyl mercaptan are weakly acidic and w i l l dissociate to the hydrosulphide and mercaptide ion, respectively (Shih et al., 1967a, 1967b). The equilibria formed by the ionization o f hydrogen sulphide and methyl mercaptan are strongly dependent on the p H o f the solution and only slightly affected by temperature. The vapour pressure o f hydrogen sulphide is a function of p H because of the successive ionizations of hydrogen sulphide to the hydrosulphide and sulphide anions, which result in a decrease in the concentration o f the undissociated hydrogen sulphide, and thus a decrease in its vapour pressure: H S< 2  K a  '  >H + HS"< +  K a ;  >2H +S° +  (3.14)  The extent o f the dissociation is quantified by the acid dissociation constant, K a . For example, for the dissociation o f hydrogen sulphide, K a , = [H ][HS"]/[H S]. +  2  The hydrosulphide anion is an active cooking chemical that is formed when sodium sulphide hydrolyzes to hydrosulphide, which in turn dissociates, along with sodium hydroxide, to the sodium cation and the hydrosulphide and hydroxyl anions: Na S+ H 0< 2  2  >NaHS + NaOH<——>2Na + H S " + O H " +  (3.15)  Shih et al. (1967a) showed that the vapour pressure o f hydrogen sulphide over its aqueous solution at various p H values is dependent on the concentration o f undissociated hydrogen sulphide present in the solution. The fraction o f hydrogen sulphide that exerts a vapour pressure, i.e., the fraction undissociated, x , can be expressed as: ±  H ] + K a , [ H ]+ K a , K a +  2  +  49  2  Chapter 3: Literature Review  p H is defined as -log[H ] and p K a as -log(Ka). From these relationships, the concentration +  of the hydrogen ion, [FT], can be determined from the measured p H , and the value for K a can be determined from the p K a values given in Table 2.2. Shih et al. (1967b) also found that methyl mercaptan w i l l ionize according to the following equilibrium: CH SH( 3  K a  >CH S~ + F T 3  (3.17)  The undissociated fraction o f methyl mercaptan can be expressed as: [H ] +  + X M M  = [H ] K a +  (  3  1  8  )  +  Based on the p K a values given in Table 2.2, above a p H o f 9, very little undissociated hydrogen sulphide w i l l exist, and above a p H of 12, very little undissociated methyl mercaptan w i l l exist. This effect is represented graphically in Figure 3.2.  Maintaining a high level o f residual alkali in kraft pulping w i l l maintain high p H which increases the dissociated fraction o f hydrogen sulphide and methyl mercaptan and decreases their vapour 50  Chapter 3: Literature Review  pressure. The other organic T R S compounds, dimethyl sulphide and dimethyl disulphide, do not dissociate, therefore their vapour pressures are not a function o f p H .  3.1.3.2 I n o r g a n i c D i s s o l v e d S o l i d s E f f e c t s o n V L E  Electrolyte chemistry includes the dissociation effects discussed above and also the so-called "salt effects," where partial or complete dissociation o f salts in solution alters the vapour pressure of the volatile components. This is commonly referred to as the "salting-in" or "salting-out" o f a volatile species. When salt is added to a solvent mixture, a resulting increase in the relative volatility of one o f the species is referred to as a salting-out o f this component, while salting-in refers to the opposite effect. A s discussed in Section 3.1.2, this effect can be modelled by extending the activity coefficient N R T L equation to the e N R T L equation. A s described in Section 2.7, kraft black liquor contains many salts, including sodium hydroxide, sulphide, carbonate, sulphite, sulphate, and thiosulphate, along with others in smaller concentrations (Table 2.10).  The total dissolved solids in black liquor include about 20 wt%  inorganic salts (Table 2.9). Zhu et al. (2000) found that for typical softwood black liquor more than 95 wt% of the total dissolved inorganic materials (excluding organically bound sodium and sulphur) is sodium salts. Data found in the literature describing the effect o f dissolved salts on the phase equilibrium o f the T R S compounds are included in Tables 3.1 to 3.8.  3.1.3.3 O r g a n i c D i s s o l v e d S o l i d s E f f e c t s o n V L E  The total dissolved solids in black liquor include about 80 wt% organic material, with about 30 wt% lignin (sodium free basis) included in this fraction (Table 2.9). Dissolved alkali lignin in black liquor consists mainly o f sodium phenolates, so the total alkali lignin fraction, including the "organically combined sodium" fraction is about 40 wt % o f the total dissolved solids in black liquor. The balance of the organic material consists of hemicellulose, sugars, extractives, acids, and numerous other unidentified organics. N o information could be found in the literature describing the effect o f dissolved organic substances on the equilibria of any o f the T R S compounds.  51  Chapter 3: Literature Review 3.1.3.4 O t h e r E f f e c t s o n V L E  A n under-reported phenomenon is "binding" of reduced sulphur compounds with metal or lignin ions in kraft liquor or condensate. Since only the unbound fraction of these compounds would contribute to the vapour pressure, this has a direct impact on phase equilibria. This phenomenon is mentioned in the literature (Wardencki, 1998), and although this effect has not been quantified, it is expected to be significant only at very low sulphide concentrations. The final effects to be considered are the deviations from equilibrium due to incomplete mixing, stratification in the liquid phase, tramp air ingress, or insufficient residence time to reach equilibrium. These potential effects w i l l be different for each type o f process system or tankage in a kraft mill and w i l l depend on the configuration and residence time for the particular equipment. These effects w i l l be accounted for as part o f the modelling process, which is discussed in greater detail in Chapter 6.  3.1.4  H e n r y ' s Constant a n d Activity Coefficients for T R S  A n extensive search o f the literature was conducted to find information relating to the vapour-liquid equilibria of the T R S compounds in water, black liquor, and salt solutions. In almost all cases, these data were reported as a Henry's constant. For the most part, only sources containing original data are cited; i.e., Henry's constants or activity coefficients regressed from data generated by others were ignored when the original work could be found in the literature. Hydrogen sulphide is a common compound found in o i l and gas processing, effluent treatment, composting, and in food preparation (or spoilage such as from rotten eggs); thus, it is not surprising that a number of researchers have studied the properties o f aqueous H S systems. Less 2  data are available for the organic T R S compounds, but some do exist as a result o f research for specific issues. In atmospheric research, recent models o f the global sulphur cycle point to a significant flux o f sulphur from the oceans to the atmosphere and it has been proposed that dimethyl sulphide may provide the source for such a flux (Dacey et al. 1984). Knowledge o f vapour-liquid equilibrium for dimethyl sulphide in salt water is helpful in study o f this phenomenon; this has provided the impetus to study the effects o f salt on the phase equilibria o f a DMS-water system. 52  Chapter 3: Literature Review Przyjazny et al. (1983) reported Henry's constant for the three organic T R S compounds over a temperature range o f 25 to 70°C at various concentrations o f N a C l and N a S 0 . 2  4  Dacey et al.  (1984) reported Henry's constant for D M S over a temperature range o f -0.8 to 32.4°C for distilled water, " 5 5 % seawater" and "Sargasso seawater." Barrett et al. (1988) reported Henry's constants for H S over a temperature range o f 25 to 95°C at various N a C l concentrations. Carroll and Mather 2  (1989) reported Henry's constants for H S over a temperature range of 0 to 90°C, while Suleimenov 2  and Krupp (1994) reported them for 20 to 90°C. De Bruyn et al. (1995) reported Henry's constants for H S , M M and D M S over a temperature range o f 5 to 25°C. Wong and Wang (1997) reported 2  Henry's constants for D M S over a temperature range o f 18 to 44°C but for an unspecified "seawater" concentration. Tormund (1997) reported Henry's constants for all o f the T R S compounds over a temperature range o f 40 to 80°C for N a concentrations o f 0.3 M and 3.0 M , but did not report for +  a salt-free system. Two sources not based on original work, instead composed o f large databanks o f compiled sources, were considered. The Aspen Plus version 11.2 (Aspentech) databank contains Henry's constant temperature dependent parameters for only one system, H S in water for -0.15 to 59.5°C. 2  Yaws et al. (2003) compiled Henry's law constants for many sulphur compounds in water from multiple sources including the C R C Handbook o f Chemistry and Physics and his own Y a w s ' Handbook of Thermodynamic and Physical Properties; data are provided for M M and D M S , but only at 25°C. Only Olsson and Zacchi (2001) have reported N R T L parameters for calculating activity coefficients, but they regressed their parameters based on data generated by others, with the exception of D M D S , for which they conducted some lab work. Unfortunately, they did not supply the experimental data on which they based their results. Nonetheless, a system approaching infinite dilution was assumed and these parameters were converted to a Henry's constant so that their data could be compared to others. Very little V L E data could be found for volatiles in black liquor. Z h u and Chai (1999) and Zhu et al.(2000a) published results for the phase partitioning in black liquor for methanol, but not for the T R S compounds. This data was used for simulation work for Cluster Rule compliance, with this discussed in more detail in Section 3.2.2. Olsson et al. (2000) published results for 15 common V O C s found in black liquor, including the T R S compounds. Unfortunately their results were limited 53  Chapter 3: Literature Review  to only two samples and were based on testing T R S concentrations after the "aging" effect had stopped; aging can significantly alter results. For example, the concentration of dimethyl disulphide in one o f their black liquor samples increased from 26 to 127 mg/kg over a few hours, with a resulting decrease from 225 to 120 mg/kg for methyl mercaptans. This aging effect is described in more detail in Section 3.4. The reported Henry's constant values in Tables 3.1 to 3.8 have all been converted to the same units o f (mol/mol)/MPa, to facilitate comparisons. Henry's constant is typically presented at 25°C, but some researchers have provided temperature dependency data. The enthalpy of solution, - A H , s o l  is the enthalpy change associated with the process when a component enters solution.  The  temperature dependance of Henry's constant can be expressed in the following form (Sanders, 1999): -dn(k )  A  H  d(l/T)  s o l  H  (3.19)  R  Integrating from 298 K , the temperature dependency o f Henry's constant is given by: k„ = k- exp^ 8K  A  S 0 l  H7l  R  VT  1  (3.20)  298  Henry's constants at 298 K , and the temperature dependency constants, - A H / R , for all literature sol  sources are summarized in Tables 3.1 to 3.8.  T a b l e 3.1:  Henry's constants for hydrogen sulp lide in water 1, 298K H  -A „,H/R  (mol/mol)/MPa  (K)  Barrett et al. (1988)  0.018  Carroll and Mather (1989)  pH  Temperature range (°C)  2550  1.5 to 2.5  25 to 95  0.019  2110  not specified  Oto 90  Suleimenov and Krupp (1994)  0.01.9  1820  not specified  20 to 90  De Bruyn et al. (1995)  0.014  2080  <6.0  5 to 25  Aspen Databank 11. .2  0.019  2160  not specified  -0.15 to 59.5  Olsson and Zacchi (2001)  0.016  1330  not specified  not specified  Source  K  S  54  Chapter 3: Literature Review T a b l e 3.2:  Henry's constants for hydrogen sulp lide in various salt solutions 1,  Source  298K  -A ,H/R S 0  Salt content  Temperature range (°C)  (mol/mol)/MPa  (K)  Barrett et al. (1988)  0.015  2520  1 mol/kg N a C l  25 to 95  Barrett et al. (1988)  0.013  2460  2 mol/kg N a C l  25 to 95  Barrett et al. (1988)  0.012  2440  3 mol/kg N a C l  25 to 95  Barrett et al. (1988)  0.010  2390  4 mol/kg N a C l  25 to 95  Barrett et al. (1988)  0.009  2370  5 mol/kg N a C l  25 to 95  Tormund (1997)  0.025  2200  0.3 M N a  40 to 80  Tormund(1997)  0.026  2530  3.0MNa  Table 3.3:  +  40 to 80  +  Henry's constants for methyl mercaptan in water  Source  K  298K  -A  H/R (K)  s o l  (mol/mol)/MPa  pH  Temperature range (°C)  Przyjazny et al. (1983)  0.070  3420  not specified  25 to 70  De Bruyn et al. (1995)  0.036  2800  <9.0  5 to 25  Yaws et al. (2003)  0.044  -  not specified  25  Olsson and Zacchi (2001)  0.051  1630  not specified  not specified  Table  3 . 4 : Henry's constants for methyl mercaptan in various salt solutions  Source  u  298K  Salt content  Temperature range (°C)  2400  0.70 M N a C l  25 to 70  0.063  3490  0.30 M N a  40 to 80  0.030  2580  3.0MNa  K  H  -A  s o l  H/R  (mol/mol)/MPa  (K)  Przyjazny et al. (1983)  0.058  Tormund (1997) Tormund (1997)  55  +  +  40 to 80  Chapter 3: Literature Review  Table 3 . 5 : Henry's constants for dimethyl sulphide in water Source  1,  298K  -A  s o l  H/R  Temperature range (°C)  (mol/mol)/MPa  (K)  Przyjazny et al. (1983)  0.100  4080  25 to 70  Dacey et al. (1984)  0.099  3490  -0.8 to 32.4  De Bruyn et al. (1995)  0.085  3070  5 to 25  Yaws et al. (2003)  0.099  -  25  Straver et al. (2005)  0.088  -  25  Olsson and Zacchi (2001)  0.026  1620  not specified  Table 3 . 6 : Henry's constants for dimethyl sulphide in various salt solutions Source  K  298K  -A ,H/R (K)  Salt content  (mol/mol)/MPa  Temperature range (°C)  Przyjazny et al. (1983)  0.078  3880  0.7 M N a C l  25 to 70  Przyjazny et al. (1983)  0.087  4160  0.33 M N a S 0  Przyjazny et al. (1983)  0.062  4230  0.66 M N a S 0  Przyjazny et al. (1983)  0.044  3740  1.00MNa SO  Przyjazny et al. (1983)  0.032  3510  1.33 M N a S 0  Dacey et al. (1984)  0.094  3250  10.5 ppt CT  0.2 to 28  Dacey et al. (1984)  0.085  3490  19.1 ppt C l "  Oto 29.1  Wong and Wang (1997)  0.077  4300  "seawater"  18 to 44  Tormund(1997)  0.071  3480  0.3 M N a  40 to 80  Tormund(1997)  0.045  3130  3.0MNa  S 0  56  2  4  2  2  2  +  +  4  25 to 70 25 to 70 25 to 70  4  4  25 to 70  40 to 80  Chapter 3: Literature Review  Table 3 . 7 : Henry's constants for dimethyl disulphide in water Source  K  298K  -A ,H/R (K)  Temperature range (°C)  (mol/mol)/MPa Przyjazny et al. (1983)  0.162  4130  25 to 70  Olsson and Zacchi (2001)  0.046  2480  not specified  S 0  Table 3 . 8 : Henry's constants for dimethyl disul ?hide in various salt solutions Source  K  298K  -A  Salt content  Temperature range (°C)  4020  0.70 M N a C l  25 to 70  0.147  4110  0.33 M N a S 0  4  25 to 70  Przyjazny et al. (1983)  0.098  4470  0.66 M N a S 0  4  25 to 70  Przyjazny et al. (1983)  0.074  4620  1.00 M N a S 0  4  25 to 70  Przyjazny et al. (1983)  0.064  4090  1.33 M N a S 0  4  25 to 70  Tormund (1997)  0.102  3480  0.30 M N a  Tormund(1997)  0.065  3690  3.0MNa  S 0 |  H /R  (mol/mol)/MPa  (K)  Przyjazny et al. (1983)  0.117  Przyjazny et al. (1983)  2  2  2  2  +  +  40 to 80 40 to 80  From inspection o f the data presented in the tables above, it is clear that the addition o f salt to a water system containing any o f the T R S compounds w i l l increase the relative volatility o f the T R S compound with respect to water (salting-out o f T R S ) . The data from Olsson and Zacchi (2001) do not agree very well with other sources. Their focus was on modelling of these compounds for foul condensate steam stripping systems; thus, they were concerned with distillation of these compounds at much higher concentrations, well outside the valid range for Henry's law. They may have regressed their activity coefficient parameters from experimental data only at higher concentrations without considering the accuracy at the infinite dilution extreme. O f the five parameters used to fit the N R T L equation, they held three o f them constant (ay and a^ were set to zero, and a was set to 0.3) for their data regression. It is not clear why they did this, but, as discussed in Chapter 6, when fitting experimental data from this work, a good fit could not be achieved when holding these same parameters constant.  57  Chapter 3: Literature Review 3.1.5  T R SV a p o u r Pressure  The vapour pressure o f a pure compound can be estimated using the extended Antoine's equation o f the form (Perry's, 1997): C2 l n f P i " ^ C l j + ~y- + C 3 i -ln(T)+ C 4 , - T 8  (3.21)  C 5 i  Parameters for this equation for the T R S compounds and methanol are available in reference books, with the values given in Table 3.9 taken from Perry's (1997). One exception to this is dimethyl disulphide which was taken from the National Institute o f Standards and Technology website (NIST); these parameters were given for a slightly different equation, so data generated from this correlation was regressed to determine the best fit parameters for Equation (3.21) and these are given in Table 3.9.  T a b l e 3.9:  Constants for vapour pressure Equation (3.21) (Perry's, 1997; NIST)  Compound  CI  C2  C3  C4  C5  Temperature range ( K )  H S  85.584  -3839.9  -11.199  0.018848  1  187 to 373  MM  54.15  -4337.7  -4.8127  4.5000e-17  6  150 to 469  DMS  83.485  -5711.7  -9.4999  9.8449e-06  2  174 to 503  DMDS  4.573  -3841.4  3.2245  -0.00574  1  273 to 401  Methanol  81.768  -6876.0  -8.7078  7.1926e-06  2 •  175 to 512  2  3.2  M o d e l l i n g of the K r a f t P u l p i n g Process  Since the advent of computer technology, modelling o f the kraft process using computer simulation has become popular with many researchers and engineers in the industry. Modelling o f industrial facilities can be used for many purposes including process optimization, sensitivity analysis, development o f process control strategies, training and environmental reporting. Optimization in kraft pulp mills is often focussed on maximizing pulp yield and quality and energy efficiency. Efforts toward closure (e.g., recovery and re-use of hot contaminated process water) for 58  Chapter 3: Literature Review  energy savings and minimizing environmental impact have increased the complexity o f the process. With closure, solving heat and mass balances becomes more o f a challenge because recycling o f recovered waste streams back into the process increases the complexity of the iterative nature of the solution. Commercial simulation packages provide powerful tools that allow for analysis o f very complex systems with minimal effort. Use of simulation software in the pulp industry to study environmental impact has recently become more popular, mainly due to the continuing improvements in computer hardware and software. Also driving this are new regulations and emissions reporting requirements: in the U . S . , the Cluster Rule, and in Canada, the N P R I , both discussed in detail in Section 2.5.  Increased  computing power, combined with user friendly commercially available software packages, provides the means, and the more stringent environmental reporting and regulations provides the impetus. After the initial investment to design and test the model, computer simulation could potentially be as inexpensive as the application o f emissions factors, while providing much more accurate estimates o f actual emissions. The first requirement o f modelling the release o f contaminants to the atmosphere is understanding how the contaminants enter the process or how they are generated within the system. The organic T R S compounds are mainly generated within the digester and there are a number o f research papers which were discussed in Section 2.2 that provide details for estimating the amount formed. The second requirement is to understand how these compounds behave in equilibrium within the system. With this information, it is possible to estimate how the target contaminants move between each individual process unit and where they w i l l leave the system. T R S generation and release modules can then be integrated into a general heat and mass balance to produce an overall T R S emissions model. The T R S model can be used to generate a "base-case" heat and mass balance based on the existing process. The base-case model can be used to predict changes in emissions for changes to the operation or changes to any process equipment. The model can be used to determine the most effective and cost-efficient way to reduce emissions, either through modification to the equipment, changes to operation, or through installation o f collection and treatment systems.  59  Chapter 3: Literature Review  3.2.1  C o m p u t e r Software M o d e l l i n g Tools  There are many software tools that can be used for modelling, with the most common being spreadsheet programs such as Lotus 123 or M S Excel.  These are extensively used for their  simplicity and flexibility. They often provide all the computing power and functions required to prepare heat and mass balances o f simple processes. The drawbacks to spreadsheets include their lack o f an integral thermodynamic properties database and their limitations for presentation. M S Excel can be linked to M S V i s i o , a flowsheet drawing program, for presentation purposes, but more powerful simulators combine these features. The next step up are the commercially available general simulation programs such as Aspen Plus (Aspentech). These are very powerful programs which are relatively simple to use; they typically operate on an input screen user interface. These packages incorporate a back to front approach when compared to spreadsheets; i.e., with these packages the flowsheet drawing is typically completed first and the specifications for each stream are added later. This process is more intuitive and allows for greater ease of programming for more complex systems. They are designed to deal with processes that require iterative solutions, something that can be done on a spreadsheet but with greater difficulty. Typical features available with most commercial simulation packages include built-in properties databases, integrated thermodynamic mathematical models designed to represent the actual behaviour o f many different fluid mixtures, integrated mathematical models for standard equipment such as heat exchangers and distillation columns, and dynamic capabilities. A number of modelling software packages are available that were originally developed for specific industries such as Aspen Plus, H Y S Y S , Chemcad and P R O S I M ; these were all originally aimed at the oil and gas industry. In general, these include a database and modules that are tailored to their particular specific industry requirements. The pulp and paper industry has a number o f unique requirements for process simulation. Typically, the simulation packages include industry-specific modules such as digesters, washers, screens, etc., and a properties database that includes the chemicals used in kraft pulping. They should also include other substances where the properties must be estimated, such as for fibre, lignin, dissolved solids, black liquor, etc. Many o f these substances are not molar definable compounds, 60  Chapter 3: Literature Review  and their exact composition is unknown; thus, they w i l l not be found in any standard substances database. This lack of specific compound information leads to the significant feature o f all pulp industry simulation packages, that they are typically done on a weight rather than molar basis. The most common pulp mill modelling packages include I D E A S  (IC&S), Pulpmac (Pulpmac),  W i n G E M S (Pacsim) and C A D S I M Plus (Aurel); details can be found on their respective websites. I D E A S was developed by the H . A . Simons Consulting group in Vancouver, B . C . , but was recently sold to the Andritz group based in Austria. I D E A S was used by H . A . Simons (later A M E C ) as a marketing device and a design tool for their own engineers in a construction or consulting role, while Andritz appears to be marketing the software package as a tool for researchers and m i l l personnel. Pulpmac was developed by the consulting group Papermac A B in Sweden. Both I D E A S and Pulpmac are based on the Extend Player platform, a commercially available software programming package supplied by Imagine That! (Imagine). Extend Player is a generic simulation platform that can be extended by programming modules to create a package for a specific requirement. W i n G E M S is a Fortran-based program which was developed at the University o f Idaho in the early 1970's. W i n G E M S is now being marketed by Pacific Simulation o f Moscow, Idaho, a subsidiary of Metso Automation. The software was developed for the pulp and paper industry and is used, as its name implies, for general energy and material balance systems ( G E M S ) . C A D S i m was originally conceived in the 1980's by the H . A . Simons process simulation group, beginning as a graphical interface, essentially a computer-aided design ( C A D ) flowsheet drawing, integrated with M A S S B A L , one of the original simulation software packages. Because o f limitations integrating the two, H . A . Simons moved onto I D E A S development and an offshoot company, Aurel Systems o f Burnaby, B . C . , moved on to develop C A D S i m Plus, based on the C programming language. C A D S i m Plus and W i n G E M S presently appear to be the dominant players in the North America pulping industry.  3.2.2  Previous W o r k M o d e l l i n g N o n - C o m b u s t i o n T R S Emissions  The most extensive work to date on modelling kraft pulp mill non-combustion sources was done by a group led by Yongxiang G u and L o u Edwards o f the University o f Idaho. They used the 61  Chapter 3: Literature Review  computer simulation software package, W i n G E M S , which was originally developed by their group. For this work, they recently expanded its capability with the addition o f methanol generation and release modules. They presented this work in series of four papers titled "Cluster Rule Compliance Tools" (Gu et al., 2001). The work focussed on methanol, since this is specified as a surrogate to determine compliance with the Cluster Rule for H A P emissions (U.S. E P A , 1998). This modelling work was supported by experimental work conducted at the Institute of Paper Science and Technology (IPST) in Atlanta led by Jun Y o n g Zhu. This group conducted research on methanol formation ((Zhu et al, 1999a; 1999b; 2000b; 2001) and methanol vapour-liquid equilibrium (Zhu and Chai,1999; Zhu et al., 2000a). They also did some work on T R S formation (Zhu et al., 2002; Yoon et al., 2003), although not on T R S vapour-liquid equilibria. In addition to the experimental work done at IPST, G u et al. (2001) conducted experiments to determine the effect o f alkali lignin on methanol equilibrium. They added an unspecified "commercial kraft lignin" to a solution containing 800 mg/L methanol. They found that the addition of this alkali lignin had a relatively minor effect compared to the dissolved salts, with a mixture o f 10 wt% alkali lignin increasing the relative volatility o f methanol by about 15%. In fact the effect was so minor that the seven data points below 7 wt% actually showed the opposite effect, with the six data points between 7 and 12 wt% just pulling their linear fitted equation up to a slightly positive effect on the relative volatility. They also conducted equilibrium experiments with dissolved salts, preparing solutions containing either N a S 0 , N a S 0 or N a C l . They used the data from all o f these salt solutions to 2  4  2  2  3  develop an empirical correlation. They found that these dissolved salts had a relatively large effect, with a solution o f 10 wt% salts increasing the relative volatility o f methanol by about 60%. Figure 3.3 illustrates the order o f magnitude effect on methanol vapour-liquid equilibrium that could be expected from the solids content of weak black liquor. The "total solids" line is the graphical representation o f a purely empirical correlation developed by G u et al., (2001), from laboratory tests on weak black liquor. For example, they determined that the 15 wt% solids content of a typical weak black liquor would increase the activity coefficient o f methanol by about 50%).  62  Chapter 3: Literature Review  weight %  Figure 3 . 3 : Effect on activity coefficient o f methanol due to the presence o f dissolved inorganic and organic matter in black liquor (drawn from data from G u et al., 2001)  The "inorganics" line in Figure 3.3 represents their empirical correlation based on the data generated from the sodium salt solutions, while the "organics" line represents their empirical correlation for an alkali lignin mixture.  One o f the questions raised was whether this latter  correlation could be extended for the entire organics content since some o f these substances likely w i l l not have the same effect as alkali lignin. In fact, the extractives, being sparingly soluble in water, may have the opposite effect, suppressing the methanol activity coefficient through surfactant or other effects, but due to the great complexity o f the black liquor mixture, simplifications had to be made to allow a model to be applied. For the next stage o f their Cluster Rules work, G u et al. (2001) incorporated an emissions module into W i n G E M S . The module uses the N R T L equation to calculate the binary methanolwater activity coefficient. This value is then adjusted using the empirical correlations described above to account for the shift due to the dissolved solids. The application o f this module is limited to a system with no temperature change, i.e., the liquid and vapour outlet temperatures equal the 63 ;  Chapter 3: Literature Review  liquid inlet temperature. With this limitation in place, calculations can be simplified by assuming the outlet liquid flow equals the inlet liquid flow; i.e., the outlet vapour flow is very small compared to the liquid flow. The emissions module could then be programmed in such a way that the mass, energy and phase equilibria equations could be solved directly; otherwise the solution includes multiple non-linear equations, for which an iterative process would be required. This module can only be used for equipment where there is negligible temperature change across the system and where the vent flow is very low compared to the liquid flow, such as a storage tank. It can not be used to model process equipment such as a liquor flash tank, where there is a temperature change, and thus flashing of the liquid. For the final stage, they used mill measurements taken from a single fibre-line o f a southern softwood kraft mill to test their model. A l l air samples were collected and analysed by N C A S I and the liquor samples collected by N C A S I were delivered to IPST for testing. For this m i l l , they found they could predict methanol emissions reasonably accurately; their results for various process equipment are summarized in Figure 3.4.  1600  12,200  12,200  1400  • Mill Measurement  •a 1200  1a. ao c  H Model, Eq.(l)  1000 800 600 400  -H  200 Brn Atm Diffuser  0 Blow Tank 2  0 Atm Diffuser 2  Decker D Tower Seal Tank 0  D Seal Tank 0  Eo Seal Tank  F i g u r e 3 . 4 : Comparison o f methanol vent stack model predictions with m i l l measurements for various process equipment (Gu et al., 2001)  64  Chapter 3: Literature Review  In the period from 1993 to 1997, process simulation studies for V O C emissions using W i n G E M S were completed for all the Mead mills in the U . S . (Venkatesh et al., 1997; Venkatesh, 1999; Venkatesh et al., 2000). Models were developed for a total o f eight mills, referred to as M i l l A to H . Modelling was done with the aim o f determining the most cost effective option for Cluster Rule compliance. The predictions made by these models were verified by comparing with sampling and testing results for the specific m i l l . They began by preparing a base-case model o f existing operation and then developed alternative operating scenarios, including potential modifications to existing equipment, to determine compliance. For one Mead mill ( M i l l E), Venkatesh (1999) reported data for T R S , although no details were provided on which T R S compounds were tested. N o details were given regarding what correlations and what parameter values were used to model the phase equilibria. Figure 3.5 and 3.6 are scatter diagrams for M i l l E testing data versus predicted values for methanol and T R S .  950 -  900  850 -  800 -  CO  Q  —  750 -  700 -  650 650  700  750  800  850  900  950  G E M S Prediction F i g u r e 3 . 5 : Comparison o f G E M S prediction versus mill data for M i l l E for methanol concentration in the vapour phase (Venkatesh, 1999)  65  Chapter 3: Literature Review  G E M S Prediction F i g u r e 3 . 6 : Comparison o f G E M S prediction versus mill data for M i l l E for T R S concentration in the vapour phase (Venkatesh, 1 9 9 9 ) N o details were provided for the sampling location for the points on these scatter diagrams, only that they are for selected process streams at current conditions. The T R S predictions vary by as much as three times too high or too low; Venkatesh  (1999)  states that some scatter in the T R S data was  attributed to sampling issues.  3.3  T R S Emissions Factors  A n emissions factor is a representative value that attempts to relate the quantity of a pollutant released to atmosphere with an activity associated with the release o f the pollutant. These factors are often expressed as the weight o f a pollutant divided by a unit weight or volume o f product produced. For example, the estimate o f reduced sulphur emissions for kraft pulping equipment is expressed as kg sulphur emissions per tonne pulp produced. The N P R I reporting program directs Canadian facilities to use emissions factors developed by the U . S . Environmental Protection Agency ( E P A ) through their Technology Transfer Network (TTN). Emissions factors for a kraft pulping brown stock washer shown in Table 3.10 were extracted from Table 10.2-1 o f "Compilation o f A i r  66  Chapter 3: Literature Review  Pollutant Emission Factors, Volume 1: Stationary Point and Area Sources, A P 42, Fifth Edition," available on the E P A Technology Transfer Network website (TTN).  Table 3 . 1 0 : U . S . E P A Emissions Factors for Chemical Wood Pulping. S refers to kg of pollutants released as sulphur ( R S H = methyl mercaptan, R S R = dimethyl sulphide, R S S R = dimethyl disulphide), and M g refers to millions o f grams (i.e. tonne) o f air-dried unbleached pulp ( T T N ) m  H S (S ) kg/Mg  R S H , R S R , R S S R (S ) kg/Mg  Digester relief and blow tank  0.02  0.6  Brown stock washer  0.01  0.2  Location  m  2  m  These emissions factors are based on the use o f contaminated condensate for brown stock washing; i f fresh water is used, then the emissions factors are reduced by a factor of four. Emissions factors are also provided for other equipment such as the multiple-effect evaporators, recovery boilers, smelt dissolving tanks and lime kilns. These emissions factors, last updated in September 1990, are based on a mill where the pulp from a batch digester is directed to a blow tank and then to a washing line. There are no details given on the type of washing equipment, but the typical equipment used in that era was a series o f vacuum drum type washers. A more modern mill configuration, such as that used at the Howe Sound mill where testing for this research was completed, consists of a continuous digester, with the pulp from the digester passing through a two-stage atmospheric diffusion washer before entering the blow tank. The stock is then processed through a vacuum drum type washer, called a decker washer, before going to the oxygen delignification system. It is questionable how valid the above emissions factors are for a mill with a continuous digester and more modern washing equipment, but lacking other emission factor options, these are still in common use. Between 1996 and 2003, the Swedish Pulp and Paper Institute (STFI) led a U S $ 1 3 M program called the "Eco-Cyclic Pulp M i l l . " This project brought together a number o f research organizations and universities to study the possibilities and limitations o f sustainable eco-balanced production o f kraft pulp. A n overview o f the project was presented by Peter Axegard, who headed the program (Axegard, et al., 2001). This work was completed and published in July 2003 as a 260 page report, one section of which provides information for a "reference m i l l " (Ledung, et al., 2002). 67  Chapter 3: Literature Review  The reference mill is a hypothetical pulp m i l l for the production o f fully bleached market kraft pulp, consisting o f sub-processes, each of which represents existing best available technology. It includes the latest in emissions control technology including C N C G and D N C G collection systems. The reference data are provided in the form o f design or emissions factors. The basis for all calculations for the reference mill are 11 , with this term defined as 1 air-dry metric ton o f pulp. 90  The factor specified for "sulphur to air" is 0.2 kg S/t . 90  3.4  T R S S a m p l i n g and Testing Considerations  It is well documented that T R S samples are unstable and that analytical testing is a challenging proposition since these sulphides have absorptive, adsorptive, photo-oxidative, and metal catalytic oxidative features (Wardencki, 1998). O f the degradation reactions, oxidation is the main concern. Hydrogen sulphide and methyl mercaptan w i l l dissociate at high p H , such as in black liquor, to the non-volatile hydrosulphide and mercaptide ions, respectively (Reactions (2.3) and (2.7)). The hydrosulphide ion can oxidize to thiosulphate (Reaction (2.10)), while the mercaptide ion can oxidize to dimethyl disulphide (Reaction (2.9)). Once formed, dimethyl disulphide does not oxidize to any significant extent, but it w i l l undergo hydrolytic disproportionation under the influence of hydrosulphide and hydroxide ions (Bentvelsen et al., 1975). The complex mechanism is believed to involve an initial nucleophilic displacement o f the sulphide bond. Following this rate limiting step, a series o f reactions lead ultimately to formation o f non-volatile methane sulphinic acid and regeneration o f some methyl mercaptan: 3CH SSCH  HS"  2CH SSCH 3  >2CH SO~ + 4 C H S  (3.22)  >CH SO;" + 3 C H S  (3.23)  3  3  OH"  3  68  3  3  Chapter 3: Literature Review  The mercaptan formed in these reactions can then oxidize back to dimethyl disulphide: 1 2CH S" + - 0 3  +H 0  2  >CH SSCH + 20H"  2  3  3  (2.9)  Given enough time, essentially all o f the methyl mercaptan and dimethyl disulphide w i l l convert to methane sulphinic acid ( N C A S I , 2000). These oxidation reactions are the basis for common commercial processes referred to as oxidation systems (Bentvelzen et al., 1976). For example, air or oxygen is reacted with black liquor in weak or strong black liquor oxidation systems ( W B L O x or S B L O x ) to convert the T R S compounds to non-volatile forms, to prevent venting o f these odorous gases to atmosphere in downstream process equipment. The extent o f these oxidation reactions is limited by the quantity o f oxygen in the liquor samples.  Dimethyl sulphide appears to be slightly more stable, but it also degrades over time.  M c K e a n et al. (1965) state that dimethyl sulphide may disproportionate under the influence o f hydroxide ions to form methyl mercaptan and methanol, although they found the extent o f this reaction to be negligible: CH SCH 3  3  + OH"  »CH S" + C H O H 3  3  (3.24)  Another possible reaction, in the presence o f hydroxide ions, is that methyl mercaptan may disproportionate into dimethyl sulphide and hydrogen sulphide: 2CH SH  0H  3  "  )CH SCH + H S 3  3  2  (3.25)  M c K e a n et al. (1965) found this reaction to have a slow but significant rate, while Douglass and Price (1966) found this reaction to be negligible. For black liquor, due to the alkaline conditions, the p H is typically above 11.5 (Grace et al., 1989) and the concentrations of hydrogen sulphide and methyl mercaptan w i l l theoretically be near zero (Figure 3.2). Since methyl mercaptan is expected to be below a measurable level, the loss o f the mercaptide ion through oxidation is not a direct concern, but the generation o f dimethyl disulphide from this oxidation reaction (Equation (2.9)) can compromise results i f it is formed after the sample is collected. To avoid this, during collection and storage, care should be taken to avoid introducing oxygen to black liquor samples.  69  Chapter 3: Literature Review  Sulphides w i l l strongly adsorb to glass, although glass surfaces can be deactivated to minimize this effect ( N C A S I , 2002). N C A S I states that deactivation should only be required for glassware that comes into contact with fluids containing sulphides at a concentration less than 50 pg/L ( ~28 ppb) as sulphur. A l l o f these effects discussed above are time dependent; thus, to minimize degradation effects, for the testing programs, the samples should be tested as soon as possible after preparation or collection.  70  Chapter 4: Research Objectives  Chapter 4 Research Objectives  The general objective of this work was to develop and test a method to predict emissions o f T R S compounds from kraft pulp mill non-combustion sources based on modelling using vapourliquid equilibrium correlations. To determine i f this was possible, phase equilibria behaviour for the T R S compounds must be known, and operating data from a kraft pulp mill must be available to test the model. The specific objectives o f this research were:  1.  To develop a V L E emissions model that accounts for the effects o f the dissolved solids in kraft black liquor.  2.  To conduct phase equilibria testing to determine activity coefficients that represent the V L E of the T R S compounds in kraft black liquor.  3.  To identify a method to describe the effects o f kraft black liquor composition and temperature on the V L E o f the T R S compounds and to find the best fit for this correlation using the phase equilibria testing data.  4.  To conduct a T R S sampling and testing program at a kraft pulp m i l l .  5.  To test the V L E emissions model using the results o f the mill testing program.  6.  To demonstrate a practical use for the V L E emissions model by constructing a base-case heat and mass balance based on the mill testing data and then modifying this simulation to evaluate the effect on T R S emissions from potential process modifications.  Descriptions o f the material and methods, required to complete the objectives concerned with sampling and analytical testing, are given in Chapter 5, with results and discussion in Chapter 6.  71  Chapter 5: Materials and Methods Chapter 5 Materials and Methods  To support the development o f a V L E model used to predict T R S emissions from kraft pulp mills, two testing programs were conducted. The mill testing, conducted at the Howe Sound mill located in Port Mellon, British Columbia, was conducted first; the results are tabulated in Section 6.4. During mill testing, it was found that over 90% of the sulphur in the vent gases from the brown stock washing area was in the form o f D M S . Based on this, the decision was made to use D M S as a surrogate for modelling o f T R S emissions and all subsequent testing focussed on this compound. Phase equilibria testing was done in a lab environment to investigate vapour-liquid equilibrium behaviour o f D M S in various solutions, including black liquor. For both testing programs, a gas chromatograph was used to measure concentrations of the T R S compounds.  5.1  GasChromatographic Equipment  A Varian 3800 gas chromatograph ( G C ) fitted with an 1177 split/splitless injector and a pulsed flame photometric detector (PFPD) was used for testing.  A P F P D has the unique  characteristic o f high selectivity o f sulphur compounds compared to hydrocarbons (10 :1). The 5  detector was operated in sulphur mode, which is highly specific to the sulphides tested and provided a detection limit o f about 0.1 ppm (mol). A s described in Section 2.7, black liquor is a complex mixture o f hundreds o f compounds, including many hydrocarbons and sulphides. A P F P D , when compared to the more common flame ionization detector (FID), w i l l provide distinct sulphide signal peaks with little interference from the hydrocarbon peaks, thus providing a more accurate result. The G C was fitted with an A T - 5 column, 30 m long and 0.53 mm diameter, with a 5.00 p m film thickness (Alltech), which provided good separation o f sulphur compounds. Helium at 2.5 m L / m i n was used as the carrier gas. The P F P D hydrogen flow and two air flows were set to 13, 18 and 10 m L / m i n respectively, the gate delay to 4.0 msec, the gate width to 3.0 msec, the trigger level to 200 m V , and the photomultiplier voltage to 550 V . Figure 5.1 shows the typical G C output for a gas sample, in this case the gas standard used to prepare the calibration curves.  72  Chapter 5: Materials and Methods  mvol DMDS 300  200 H2S MM  DMS  100  1  2  3  4  5  6  7  mm  Figure 5.1: Typical gas chromatograph output  The square root o f the P F P D signal (the area under the peak) provides a linear relationship to the quantity o f sulphur injected. For example, the concentration o f each sulphide in the gas standard is equal at nominal 50 ppm (mol) each, but the area under the peak for D M D S is four times larger due to the presence of 2 moles o f sulphur per mole o f compound (a disulphide), whereas the others have 1 mole o f sulphur per mole o f compound. Borosilicate sample vials (Cole-Parmer), fitted with blue Teflon and silicone septa and polypropylene caps, certified for volatile organic analysis, nominally 20 m L in volume, but measured at 24.1 m L , were used for the testing techniques described below, including preparation o f liquid standards. Gas samples were collected into 1 litre Tedlar bags (Mandel, P10 5, 7" x 7") fitted with dual on-off / septum valves. These bags were also used for preparing dilutions of the gas standard. Tedlar bags are widely used at kraft pulp mills for collecting T R S samples because they have very low permeability and are inert and solvent resistant. They are recommended for many U . S . E P A sampling methods and are specifically required by Environment Canada (1992) for use in their T R S reference method E P S l / R M / 6 , which was used here for the mill testing program.  73  Chapter 5: Materials and Methods 5.2  Phase Equilibria Testing  A s discussed in Section 3.1.4, available data from the literature describing the V L E o f D M S in water are limited, especially when effects due to temperature and dissolved solids, such as those in kraft black liquor, are taken into account. The addition o f dissolved solids, and in particular electrolytes such as the sodium salts found in black liquor, is known to alter the phase equilibrium behaviour of the system. Phase equilibria testing was done to attempt to quantify the effect on V L E of the presence o f the dissolved inorganic and organic substances found in black liquor. The first purpose of phase equilibria testing was to determine Henry's constants and activity coefficients for a binary solution o f D M S in water over a temperature range that covered typical operating temperatures for the brown stock washing area o f a kraft m i l l , i.e., 70 to 90°C. The range of study was expanded to cover 25°C to allow comparison o f results to the previously published results. To cover this range, and to provide enough data points to fit correlations used for modelling, all solutions were studied at 20, 50, 70 and 90°C. The second purpose was to quantify the effects on the V L E when organic or inorganic matter such as that contained in black liquor is added to a DMS-water solution. This was done by preparing artificial liquor solutions with some of the dissolved substances found in the highest concentrations in black liquor, including sodium salts and alkali lignin. These were tested, along with black liquor samples collected from the m i l l . The data from the artificial liquor solutions could then compared to the black liquor results to see i f any conclusions could be drawn as to what substances in black liquor contributed to the altering o f D M S phase equilibrium.  5.2.1  Phase Equilibria Testing Method  Headspace gas chromatographic ( H S G C ) methods give a direct quantitative analysis o f the vapour o f a liquid sample matrix and are therefore commonly used for vapour-liquid equilibria studies (Zhu and Chai, 2005). The traditional H S G C method requires quantitative determination o f the solute concentration both in the vapour and liquid phases through direct measurement. This has the drawback o f requiring preparation of both liquid and gas standards with calibration procedures, all o f which introduce potential errors into the experimental measurements. This method also has 74  Chapter 5: Materials and Methods  the drawback of requiring direct injection of the liquid sample, in this case black liquor, into the G C . Black liquor is an aqueous mixture o f many compounds and direct injection introduces complex matrices. Black liquor is also viscous and corrosive which can plug or damage the G C column. Chai and Z h u (1998) developed an indirect headspace method that avoids these potential issues. A t no time is the absolute concentration o f T R S quantified in either the vapour or liquid phase, and only vapour samples are injected into the G C . The method consists o f injecting a known volume o f liquid sample into a sealed sample vial, and injecting a known, but lesser volume, o f liquid sample into a second vial. These are then gently shaken until they come to equilibrium. A n equal volume of headspace sample is then withdrawn from each vial and injected into the G C . From the vial volume data, along with the G C output, the "dimensionless" Henry's constant, H , can be c  determined:  (5.1)  C and C, are the concentration o f the solute ( D M S ) in the gas and liquid phases, V , and V , are the g  liquid sample injection volume and the vial empty volume, A is the G C signal output (the area under the curve representing the mass o f D M S injected), and the superscripts 1 and 2 refer to the first and second sample vials. Even though the Henry's constant used here is referred to as dimensionless, this is not strictly true; the actual units are in the form o f molar volume in the gas phase over molar volume in the liquid phase. From the dimensionless Henry's constant, the Henry's constant referred to in Equation (3.8), as well as the activity coefficient referred to in Equation (3.6), can be calculated. Although other solutes, such as methanol, can influence the V L E o f D M S , they are typically in such low concentrations that the effect would be expected to be negligible. Nevertheless, as described in Section 5.2.3, to negate any possible effect, volatile solutes were stripped from the black liquor samples. A known amount o f D M S was then reintroduced to the sample to be tested. For best accuracy with a system involving a highly volatile substance such as D M S with a  75  Chapter 5: Materials and Methods  relatively large H (ranging from about 0.05 to 0.5 in the temperature range 20°C to 90°C), a volume c  ratio of about 30 was recommended; thus, 10 m L o f sample was injected into vial 1, and 0.3 m L was injected into vial 2.  5.2.2  Recovery of A l k a l i L i g n i n F r o m Black L i q u o r  Two sources o f alkali lignin powder were used for phase equilibria testing, one purchased from Sigma-Aldrich and the second recovered from black liquor collected at the Howe Sound m i l l . The alkali lignin was recovered from two litres of l  s l  stage diffusion washer filtrate liquor, collected  on September 22,2006, when the mill was pulping 100% Hemlock. A method described by Ohman (2006) was used to precipitate lignin from the black liquor. The liquor was placed in a 3 litre flask, held at 80°C and continuously stirred on a combination hotplate / mixer. The solution was sparged with carbon dioxide from a gas cylinder via VA" tubing and a porous stone until it reached a p H o f 9. A t this p H , a large fraction o f the lignin is expected to have precipitated. The recovered alkali lignin was filtered (Whatman N o . l filter paper). It was then washed with a 0.005 M (pH = 2) solution o f sulphuric acid, followed by a wash with distilled water, with this washing sequence repeated. The alkali lignin, resembling a light brown paste, was dried overnight in an oven at 105°C. The dried lignin, in the form of crumbly chunks, was pulverized into a fine powder using a mortar and pestle and stored in a sealed jar. Approximately 35 grams of alkali lignin were recovered.  5.2.3  Phase Equilibria Sample Solution Preparation  A sample solution o f D M S in water was prepared in a 1000 m L flask (referred to as solution 1). The flask was filled to 1000 m L with distilled water and sealed with a cap fitted with a septum. The headspace was purged for 10 minutes using 250 mL/minute of nitrogen gas. A n approximately 1000 ppm (mol) solution of D M S in distilled water was prepared using liquid D M S (Sigma-Aldrich, >99%). One m L o f this solution was injected into the 1000 m L flask to create a test solution o f approximately one ppm (mol) D M S . A s mentioned earlier, the exact concentration does not need to be known for the analytical technique used, only that the solution be in the infinite dilution range. 76  Chapter 5: Materials and Methods  Several more D M S solutions were prepared, each of these spiked with organic and inorganic substances found in the highest concentrations in black liquor. These substances include alkali lignin, which typically makes up about 40 wt% o f total dissolved solids, and sodium salts which typically make up about 20 % (Table 2.9). Weighed amounts of these substances were added to the flask before it was brought to volume with distilled water. Two alkali lignin mixtures o f 3 and 6 wt% were prepared by adding 30 g and 60 g o f the Sigma-Aldrich alkali lignin to distilled water (solutions 4 and 5). This range was chosen to represent typical black liquor lignin concentrations found in the brown stock washing area o f a mill. The source and purity of this lignin could only be partly confirmed. The supplier's data sheet stated that it was isolated from a commercial pulp mill using Norway spruce as the wood source; it may contain ash (3-7%); it can form a 10% aqueous slurry at a p H o f 6 to 7; and it is soluble in aqueous alkali solutions above a p H o f 11. The pHs o f the 3 and 6 wt% alkali lignin mixtures were measured at 8.7 and 9.1 respectively. Although these mixtures had the appearance o f a dissolved solution (no turbidity and no settling of suspended solids, even days later), they are possibly slurries, but for simplicity o f terminology, they w i l l be referred to as solutions. Another 3 wt% lignin mixture was prepared using the lignin isolated from black liquor collected at the Howe Sound pulp mill (solution 3). When preparing a mixture from the recovered alkali lignin, to ensure that this lignin was completely dissolved, the p H was adjusted to 12 with the addition o f 0.08 wt% N a O H . A "baseline" solution was also prepared by adjusting distilled water to a p H o f 12 using 0.04 wt% N a O H (solution 2). Three sodium salt solutions o f 2,4 and 6 wt% were prepared by adding 20,40, and 60 grams of a mixture o f sodium salts to distilled water (solutions 6, 7 and 8). The total concentration was chosen to represent typical total sodium salt levels in brown stock washing liquor, while the composition was chosen to be representative o f typical softwood black liquor (Table 2.10). The composition of the salt solution is shown in Table 5.1, along with the amount o f each salt added for the 2 wt% solution (double and triple these amounts were added to prepare the 4 and 6 wt% solutions). Sodium sulphide was added as N a S 9 H 0 ; the total weight o f this salt added was 2  adjusted accordingly.  77  2  Chapter 5: Materials and Methods T a b l e 5.1:  Sodium salt composition used for preparing salt solutions Salt  Composition,  wt%  G r a m s p e r 1000 m L  NaOH  10.0  2  Na S-9H G  17.5  3.5 (10.8 with H 0 )  Na C0 2  3  32.5  6.5  Na S0 2  3  10.0  2  Na S0  4  17.5  3.5  12.5  2.5  2  2  2  Na S 0 2  2  3  2  Black liquor samples were collected from the Howe Sound m i l l on three occasions, June 8, June 20 and September 22, 2006 (solutions 9 to 13). Samples from the 1 stage diffusion washer st  filtrate tank and the decker washer filtrate tank were collected into 3 litre glass bottles, brought back to the lab and stored in a refrigerator at 4°C. The June 8 samples were collected when the m i l l was running at reduced capacity; it appears that the diffusion filtrate sample was more dilute than usual. The mill was running at full capacity and under stable operation when the June 20 samples were collected and at 90% o f capacity and stable operation during the September 22 sample collection. The wood species being pulped were 50% Hemlock and 50% Interior Douglas F i r for the June samples and 100% Hemlock for the September samples. To ensure there was no interference with the G C signal for D M S from the other sulphur compounds, the black liquor samples were stripped of volatiles by purging with nitrogen gas at 250 mL/minute (foaming was noticed at higher rates) for 30 minutes. This was done by filling a 1000 m L graduated cylinder with black liquor and placing this in a fume hood. Nitrogen was introduced through a porous stone supplied by W tubing from a nitrogen cylinder. Periodic testing o f liquor samples during purging of the first sample indicated that 30 minutes purging was sufficient to reduce the volatiles to a level where they did not interfere with the dimethly sulphide signal. The black liquor sample was transferred to a sealed flask, and the flask headspace was purged with nitrogen for about 10 minutes to minimize potential oxidation reactions in the black liquor. A s with the other solutions, one m L o f the 1000 ppm (mol) D M S solution was injected into the black liquor flask to  78  Chapter 5: Materials and Methods  produce an approximately I ppm (mol) D M S black liquor solution.  A l l solutions tested are  summarized in Table 5.2.  Table 5.2: Dimethyl sulphide solutions used for phase equilibria testing Solution  Details  1  Distilled water  2  Distilled water, adjusted to a p H o f 12 using 50% N a O H  3  3 wt% alkali lignin in distilled water, adjusted to a p H o f 12 using 50% N a O H , lignin powder recovered from 1 stage diffusion washer filtrate (solution 13) st  4  3 wt% alkali lignin in distilled water, lignin powder purchased from Sigma-Aldrich  5  6 wt% alkali lignin in distilled water, lignin powder purchased from Sigma-Aldrich  6  2 wt% sodium salts in distilled water, salt composition given in Table 5.1  7  4 wt% sodium salts in distilled water, salt composition given in Table 5.1  8  6 wt% sodium salts in distilled water, salt composition given in Table 5.1  9  Decker washer filtrate, collected June 8, 2006 from the Howe Sound pulp m i l l , when pulping 50% hemlock / 50% Interior Douglas Fir  10  1 stage diffusion washer filtrate, collected June 8, 2006 from the Howe Sound pulp mill, when pulping 50% hemlock / 50% Interior Douglas Fir  11  Decker washer filtrate, collected June 20, 2006 from the Howe Sound pulp m i l l , when pulping 100% Hemlock  12  1 stage diffusion washer filtrate, collected June 20, 2006 from the Howe Sound pulp mill, when pulping 100% Hemlock  13  1 stage diffusion washer filtrate, collected September 22, 2006 from the Howe Sound pulp mill, when pulping 100% Hemlock  st  sl  st  79  Chapter 5: Materials and Methods  5.2.4  Phase E q u i l i b r i a Testing Procedure  On testing days, the solutions in the 1000 m L flasks were stored at room temperature and in a dark cupboard to minimize photo-oxidation effects.  The sample vials were purged with 250  mL/min o f nitrogen for a minimum o f three minutes and then preheated to the testing temperature for a minimum o f 30 minutes. The volume o f sample injected into each sample vial was determined by weight difference. A preheated sample vial was weighed, and either 0.3 or 10 m L o f sample was injected into the vial using disposable 1 m L and 10 m L syringes (Cole-Parmer), respectively. The vial was equalized to atmospheric pressure by inserting a syringe needle into the vial septum while the sample was being injected. The sample vial was again weighed, with the difference being the amount o f sample injected. Densities o f all solutions were determined, by weight difference using 50 m L flasks, to allow for conversion between volume and weight of solution. Once the sample was injected into the vial, the vial was fastened to a tumbler (Barnstead / Thermolyne Labquake) rotating at 15 rpm and placed in an oven ( V W R 1350FM, ±1 °C). The slow tumbling action was sufficient to provide good contacting between the liquid and vapour phase without heating the sample, which could be a factor at more vigorous rates o f mixing. The time to reach equilibrium varied depending on the volume o f sample injected into the vial and the testing temperature. It was found that six minutes was sufficient for the smaller sample size (0.3 m L ) to reach equilibrium at 20°C, while eighteen minutes was the longest time required, in this case for the larger sample size (10 m L ) at 90°C (Figure 5.2). The longer time at higher temperatures may be due to the fact that more o f the volatile substance must be transferred to the vapour phase at higher temperature to reach equilibrium. It may also have to do with the fact that the sample must first be heated from room temperature to the final temperature before equilibrium can be established.  80  Chapter 5: Materials and Methods  Time (minutes) Figure 5.2: Time for a 1 ppm (mol) solution o f D M S in 10 m L o f water in a 24.1 m L sample vial at 90°C to reach equilibrium  Once the vial in the oven had come to equilibrium, a known volume o f headspace sample was manually injected into the G C using a gas-tight syringe (Hamilton, 500 p L ) , also kept in the oven. This syringe was fitted with a Chaney adaptor (Cole-Parmer), which promised reproducibility of ±1 % when injections o f identical volumes are required, which was the case for this procedure. To minimize heat loss during injection, the area o f the syringe containing the sample was insulated with foam. The sample vial, when removed from the oven, was slipped into an insulating foam sleeve also kept in the oven. To minimize cooling o f the sample between removal o f the vial from the oven and injection of the headspace sample into the G C , a quick procedure was adopted. First the G C was prepared to receive an injection, then the syringe was removed from the oven along with the sample vial, which was placed in the foam sleeve, and then a known volume o f headspace sample was drawn into the syringe and injected into the G C . The time between removing the sample from the oven, to injection o f the sample into the G C was approximately 10 seconds. The sample vial was then placed back in the oven in preparation for the next injection.  81  Chapter 5: Materials and Methods  The G C injector was set at 200°C at a 75:1 injection split ratio. To minimize the time between injections, the G C oven was programmed to hold at 220°C, which resulted in a D M S peak at about two minutes and a total turnaround time between injections o f three minutes. To keep the amount of D M S injected within the detection range o f the G C , the injection volume ranged from 30 p L to 100 p,L, with the smaller volume used at 90°C where the D M S is more volatile and the headspace concentration higher. The exact volume injected is not important, only that the exact same amount is injected for each sample pair, ie., the vials containing 0.3 m L and 10 m L o f the same sample. The injection volume was maximized to push the signal to the upper edge o f the detection limit for the 10 m L sample without overloading the G C . This was done to maximize the strength of the signal for the 0.3 m L sample, which was near the lower detection limit.  A t least three  injections were done from each vial, with the G C output from these averaged to give the results ( A l and A 2 ) required in Equation (5.1). Each run, including time to prepare the two vials, time in oven and time for G C operation averaged out at about 45 minutes. To minimize random error, at least three runs per sample per temperature were conducted.  5.2.5  Testing of Solutions for Other Properties  The ash content o f alkali lignin powder was determined by weighing out a 2 gram sample into a crucible and placing it in the oven at 105 "C for 4 hours to remove any moisture. The crucible was then re-weighed and placed in a muffle furnace at 650°C for 20 hours, after which it was weighed again, with the ash portion determined by weight difference. The ash resembled a light blue crystalline powder. A s h determination procedures typically specify 550°C (Grace et al., 1989), but 650°C was used on the recommendation o f Paula Parkinson ( C i v i l Environmental Lab, University of British Columbia) on the basis that sodium will not volatilize at this higher temperature, and it w i l l assist in driving off the organics, providing a better sample for further tests. The purchased and recovered alkali lignin ash samples were then tested by the C i v i l Environmental Lab by atomic emission flame photometry using an air-acetylene flame to determine the sodium content.  82  Chapter 5: Materials and Methods The total dissolved solids o f the black liquor samples was determined by weighing out a 10 gram sample into a crucible and placing in the oven at 105°C overnight. The water content was determined by weight difference after drying. The ash fraction was determined by placing the crucible in a muffle furnace at 550°C overnight. For mill testing, the black liquor total dissolved solids concentration was determined using a moisture analyser (Omnimark Inst. Corp., Mark 3). A sample of black liquor collected at the Howe Sound m i l l was tested by Econotech (Delta, B . C . , Canada) by inductively coupled plasma (ICP) atomic emission spectrometry to determine the elementary composition o f the dissolved solids. The p H of the solutions was measured using a bench-top meter (ThermoOrion, model 710). The p H meter was calibrated using buffered solutions of p H 4.0, 7.0, and 12.0. The conductivity o f the solutions was measured using a hand-held meter (ThermoOrion, model 105). Distilled water dilutions o f 60, 20, and 10:1 of the 6 wt% sodium salts solution (solution 8), and 20, 10, and 5:1 o f the black liquor (solution 13) were prepared. These dilution ratios were used to bring the conductivity of these solutions into the same range as the alkali lignin mixtures (solutions 3, 4, and 5). Dilutions were prepared by weighting out 100 grams o f distilled water in a flask and adding the appropriate amount of solution.  5.3  M i l l Testing  A mill sampling and testing program was conducted around the brown stock washing area of the Howe Sound pulp mill. Process liquid and vapour samples were collected and analytical testing was completed to determine the concentration o f T R S compounds. Because T R S samples are time sensitive, with significant degradation in less than an hour, as discussed in Section 3.4, the testing equipment, including the gas chromatograph, was relocated to the mill site. A number o f challenges were overcome to conduct this testing including transportation o f fragile equipment to the mill site, lack o f sample points, poorly located sample points, sample instability, process instability, and unscheduled mill shutdowns.  83  Chapter 5: Materials and Methods  5.3.1  T h e H o w e S o u n d P u l p and P a p e r M i l l  , The kraft m i l l was completely modernized in 1989. Fibre-line equipment includes: * Kamyr two-vessel hydraulic continuous digester rated for 1300 A D t / d * Kamyr brown stock two-stage atmospheric diffusion washer (located on top o f the blow tank) * Ingersol-Rand pressure knotting and screening * Corrudek brown stock decker washer * Kamyr two-stage medium consistency oxygen delignification * Kamyr post oxygen delignification single-stage atmospheric diffusion washer * Corrudek post oxygen delignification washer * D E o p D n D bleach plant * Fourdrinier pulp machine and Flakt dryer.  The kraft power and recovery equipment includes: * B & W recovery boiler rated for 386 t/h * B & W bark power boiler rated for 239 t/h * Kamyr falling film evaporators rated for 456 t/h * A l l i s Chalmers lime kiln rated for 388 t/d * Dorr Oliver recausticizing.  Odorous non-combustion source T R S emissions are collected into two N C G systems. The concentrated N C G ( C N C G ) system sources include the digester flash steam condenser and the black liquor evaporator. The dilute N C G ( D N C G ) system sources include the digester steaming bin (chip bin), brown stock washer hoods and storage tanks for unwashed brown stock fibre and black liquor. The C N C G is burned in the lime kiln and the D N C G in the power boiler. A l l samples tested for this research were collected from D N C G sources in the brown stock washing area. Figure 5.3 is a simplified overview of the brown stock washing process and shows the location of the seven vapour and eight liquor sample points.  84  Chapter 5: Materials and Methods DIFFUSER VS1  2nd S T A G E DIFFUSION WASHER FILTRATE TANK  <LS2)|  1st S T A G E DIFFUSION WASHER FILTRATE TANK  DIFFUSION WASHER FILTRATE  DECKER WASHER FILTRATE TANK  STOCK FROM DIGESTER VS = Vapour Sample Point LS = Liquid Sample Point  Figure 5 . 3 : Howe Sound mill brown stock washing area overview showing liquid sample (LS) and vapour sample ( V S ) point locations  The brown stock washing process is designed to separate the residual cooking chemicals, dissolved lignin and other undesired products from the pulp stock. The operating pressure o f the digester pushes the stock through the blow-line to the bottom o f the 1 stage diffusion washer st  (located on top o f the blow tank). The stock passes up through the washer through screens that introduce wash liquor and extract washer filtrate. This is repeated in the 2  n d  stage diffusion washer,  with the product stock falling through two stock chutes into the blow tank. The stock in the blow tank is diluted and pumped through screens and knotters to the decker washer. Filtrate from the post-oxygen delignification system washer (referred to as 0 filtrate) is used 2  as wash water on the vacuum drum type decker washer. Some decker washer filtrate is used for dilution in the blow tank, knotters, screens and decker washer, with the balance introduced as wash water to the 2  n d  stage diffusion washer. The filtrate from the 2  n d  stage diffusion washer filtrate tank  is used for wash water in the 1 stage diffusion washer, with the filtrate from the 1 stage diffusion st  st  washer filtrate tank sent to the chemical recovery process. A s can be expected when conducting testing in an operating industrial environment, operation o f the mill may be variable at times, including an unscheduled mill shutdown in late 85  Chapter 5: Materials and Methods September that delayed testing, but in general, the process was stable on the most days that samples were collected. The only exception to this would September 28, 2005, when the mill was coming out o f an unscheduled six-day shutdown. Most of the samples were collected around the diffusion washer and filtrate tanks and around the decker washer and filtrate tank. Knotters and screens are located between these washers, but due to lack o f time, the complexity o f the systems (four stages o f screening with cascading flows) and lack o f sampling points, only a few samples were collected around this equipment. This decision appears to be justified; the limited testing and material balances conducted confirmed that this area was only a minor source of emissions, as w i l l be discussed in Section 6.4.  5.3.2  M i l l Testing Method  For determination of volatile organic sulphur compound concentrations in kraft black liquor, a full evaporation headspace technique, as described by Chai et al. (2000), was used. Methods for directed injection o f liquid samples into the G C are presented by Berube et al. (1999) and N C A S I (2002), but these were only used for waste-water samples, not black liquor. A s mentioned earlier, black liquor is corrosive and has a complex sample matrix containing many inorganic salts that discourage G C analysis by direct injection o f the liquid sample. A method presented by O'Conner and Genest (1997) of Paprican avoids these issues by sparging the black liquor sample with a measured amount of nitrogen to strip out the volatiles, with the collected nitrogen tested for volatiles concentration, and the liquor concentration calculated from this information. The main drawback to this method is the testing time, with up to an hour o f sparging required per sample. A headspace technique is relatively quick, avoids the interference from the sample matrix, and avoids G C column damage by the corrosive materials. The full evaporation headspace technique uses a very small sample size injected into a sample vial to achieve near complete transfer o f the volatile compound from a condensed matrix into the vapour phase in a very short period of time. A sample of the vial headspace is then injected into the G C . Gas samples were collected and tested using Environment Canada reference method E P S l / R M / 6 (Environment Canada, 1992). This method describes sample collection procedures for measurement of releases o f T R S compounds from pulp and paper operations. 86  Chapter 5: Materials and Methods  5.3.3  Sample Collection Procedure  A sample collection vacuum pump (Supelco 1060) was used to draw the samples via A" l  Teflon tubing through a phosphoric acid impinger (to remove water vapour), into a Tedlar bag. Figure 5.4 shows a photograph of this sample collection equipment. Three-way valves (Whitey, A'\ l  SS) were used to draw a sample through the gas pump and vent it to atmosphere until a representative sample was being was being drawn through.  A n extra-long-stem thermometer  (Control Company, Model 94460-40), inserted into the gas stream in the vent stack, was used to measure wet and dry bulb temperatures for determination o f relative humidity. A pitot-tube velometer (Alnor. Series 6000) was used to determine the vent line velocity, from which the volumetric flow was calculated.  Figure 5.4: Gas sampling equipment, including phosphoric acid impinger. Teflon tubing, 3-way valves, vacuum pump and Tedlar bag  The Tedlar bags were fitted with special dual valve fittings, which allowed collection of the sample through the valve, and syringe withdrawal o f a sample through the septum to be injected in the gas chromatograph. These bags were used to collect the gas samples as well as to prepare the 87  Chapter 5: Materials and Methods  gas standards required for testing. Each Tedlar bag was designated for one sample location, or for one gas standard, with the bags flushed with nitrogen between uses. Liquor samples were collected into narrow necked sample jars.  These jars were filled  completely and were immediately capped with minimal vapour headspace to minimize loss o f the volatile sulphur compounds.  5.3.4  Sample Collection Considerations  There was no opportunity for installation of new sample points, thus existing locations were used. For vapour sampling, the typical sample point consisted o f a A" pipe fitted with a ball valve, 3  originally installed for a pressure gauge, but with the gauge temporarily removed for our sampling purposes. A typical sample point, in this case the blow tank, being tested using the velometer, is shown in figure 5.5.  Figure 5.5: Typical sample point (blow tank vent) being tested using the velometer  8H  Chapter 5: Materials and Methods The locations o f a most sample points was less than ideal, some being located right on the tank outlet (blow tank), upstream o f an elbow (diffusion washer filtrate tank), upstream o f a valve and strainer (blow tank), or right on a "T" section (decker washer hood). With any o f these nonidealities, it is difficult to get an accurate averaged flow reading using the velometer, which w i l l compromise the accuracy o f the calculated flow. A s well, the operation o f some equipment, such as the diffusion washer, is cyclical; thus, the liquor flow to the filtrate tanks is cyclical, causing cycling in vent flow, temperature, and concentration. The diffusion washer sample point was better placed, but the vent flow reading was almost zero. This was, at the time, thought to be due to a plugged fibre strainer immediately downstream of the sample point, but inspection during a subsequent shutdown revealed an in-line valve with a reversed handle (thus closed). It appears that the vent gases from the diffusion washer were being drawn down the stock chute to the blow tank. Unfortunately a shutdown was required to fit new sample points or clean in-line equipment, and with the next shutdown scheduled for many months later, the best was made o f what was available.  5.3.5  M i l l Testing Procedure  For testing o f the gas samples, a 100 p L sample was withdrawn from the Tedlar bag using a gas-tight syringe (Hamilton, 500 p L ) fitted with a Chaney adaptor. This sample was immediately injected into the G C , which was set at a 50:1 injection split ratio. To achieve good separation of the T R S compounds, as illustrated in Figure 5.1, the G C oven was held at 40°C for 2 minutes, then ramped at 30°C per minute to 220°C, and then held for another 2 minutes, for a total run time o f 10 minutes. Gas standards were prepared from a size 32 (7" x 21") certified gas standard cylinder containing nominal 50 ppm (mol) o f each of the four T R S compounds with balance nitrogen ( B O C Gases, Langley, B.C.). Three additional standards o f 15, 5 and 1 ppm (mol) were prepared with dilutions of the gas standard with nitrogen into Tedlar bags. These dilutions were made by metering a set amount o f nitrogen into a Tedlar bag using a mass-flow meter calibrated for nitrogen ( M K S , model 2179), then using a gas-tight syringe (Hamilton, 50 m L ) to inject the required amount o f gas  89  Chapter 5: Materials and Methods  standard. Due to degradation problems discussed below, a fresh set o f these standards was prepared each morning and again in the afternoon. On the day preceding testing, sample vials were purged with 250 m L / m i n o f nitrogen for a minimum o f three minutes and then placed in an oven at 80°C. O n the day of testing, a vial was taken from the oven, equalized to atmospheric pressure with a syringe needle and 10 p L o f a liquor sample was injected using a micro-syringe (Hamilton, 10 p L ) fitted with a Chaney adaptor. The sample vial was placed in a shaker in an oven at 80°C for five minutes. The vial was then taken from the oven and a 1.0 m L headspace sample was withdrawn from the vial and injected into the G C at a 20:1 injection split ratio. The same oven ramp schedule and helium carrier gas flow as used for gas testing were also used for the liquor headspace technique. A set o f liquid standards was prepared using 99+% pure liquid D M S and 99+% pure liquid D M D S (Sigma-Aldrich). A sample vial was filled with nanopure water, capped and weighed. A small amount o f D M S was injected into the sealed vial, and the vial weighed. A small amount o f D M D S was then injected and the vial again weighed, with this being the base solution standard. The procedure was repeated, instead using the base solution in place o f the pure D M S and D M D S to produce the next standard. This was repeated twice more with the previous solution used to prepare the next. A total of four standards with D M S and D M S concentrations ranging from about 30 to 0.2 ppm (mol) were prepared. Linear calibration curves from gas and liquid standards were prepared by plotting the square root o f the P F P D signal against concentration. A typical calibration curve is shown in Figure 5.6.  90  Chapter 5: Materials and Methods  0  10  20  30  40  50  Sq.Root P P F D Count R-square = 0.991 # pts = 17 y = 0.051 + 0.717x 5.6: Typical liquid standard D M S calibration curve at the testing temperature o f 80°C Figure  5.3.6  M i l l Testing Considerations  During mill testing, significant degradation o f liquid standards was noticed after a few hours (Figure 5.7). It is not clear why the sulphide concentration in the liquid standard dropped to such an extent but one possibility is that sulphides may have absorbed onto the glass vial.  91  Chapter 5: Materials and Methods  100 80  Time (hours) Figure 5.7: Degradation o f T R S liquid standard held at 20°C and at an initial concentration o f 30 ppm (mol)  Rather than deactivating glassware or attempting to preserve the liquor samples against the degradation effects, samples were tested as quickly as possible after collection, typically within an hour. For liquid standards, new standards were prepared each day and used within an hour. Most of the complications discussed, including adsorption to glass, are time dependent and can be minimized by minimizing the time between collecting and testing the samples. The Environment Canada method requires that all testing of all gas samples must be done within an hour of the sample being collected. To test this requirement, a sample o f the gas standard containing nominal 50 ppm (mol) o f each of the T R S compounds was injected into a Tedlar bag. This bag was placed in an oven at 80°C, to simulate mill operating conditions, and tested at 5,35 and 65 minutes, with the results shown in Figure 5.8.  92  Chapter 5: Materials and Methods  50  Time (minutes) Figure 5.8: Degradation of T R S gas standard held at 80°C and at an initial concentration o f 5 ppm (mol)  Figure 5.8 illustrates that there is significant potential degradation, even within the prescribed one hour time limit. There should not have been any oxygen in this sample, so the degradation effects should not be due to oxidation, but rather one or a combination of the other effects discussed by Wardencki (1998) and summarized in Section 3.4. For mill process gas samples, the extent o f the oxidation reactions may be significant as the vent samples can contain a high proportion o f air. This can be exacerbated by ultraviolet light catalysed oxidation of the T R S compounds in the gas phase. These sample instabilities, all o f them time dependent, drove the decision to re-locate the testing equipment to the mill site. To meet the Environment Canada one-hour time requirement, and to minimize the degradation effects, gas samples were tested as quickly as practically possible. Once samples were collected, they were taken directly to the lab and injected into the pre-prepared gas chromatograph, typically within the hour. The gas standards were tested immediately after preparation, again within the hour.  93  Chapter 5: Materials and Methods  The following should be noted when viewing the analytical test results tabulated in Section 6.4: 1.  The gas chromatograph detection limit was approximately 0.1 ppm (mol); values below this are reported as non-detectible (nd).  2.  Vapour sample concentrations were corrected to include water vapour, based on the measured relative humidity level, to account for water vapour that was removed (in the phosphoric acid impinger) for testing, i.e., reported values are in ppm (mol) on a wet basis.  3.  Liquor sample concentrations are given on a stock-free basis.  4.  Liquor sample concentrations for liquid squeezed from stock may be low due to potential dilution in the sample collection pot and sampling handling technique. Liquor was squeezed from stock samples in the field and some of the T R S compounds, being highly volatile, may have been lost from the liquid. These potential sampling problems were only discovered when attempting preliminary mass balances, so those samples collected prior to November 30, 2005 may be compromised. In a particular, L S I was very difficult to sample due to the high operating pressure of the blow-line. There was a dedicated sample line and sample pot with flush connections to draw a sample from this line. To prevent plugging, the sample line had to be flushed before and after sampling and this would cause dilution o f the sample unless extreme care was taken. It was only on the last day of testing (December 1) that what appeared to be an undiluted sample was collected.  5.  The 1 stage diffusion washer filtrate tank vents through 2 st  n d  stage diffusion washer filtrate  tank via the overflow line. Only one vapour sample point was available, located on the combined vent from the 2 6.  nd  stage tank.  The diffusion filtrate tanks vent flow cycles (reversing the vapour flow) due to the cycling of the diffusion washer operation and liquor flow to these tanks. A vapour flow out o f the tank was recorded for about 60 seconds and peak at 6.4 m / m i n , after which the flow 3  reversed for about 10 seconds and peaked at about 8.6 m /min. The recorded flows are 3  averaged values. 7.  The diffusion washer vent registered little or no flow. A t the time this was thought to be due to a plugged fibre strainer, but later confirmed to be a closed valve (due to a reversed handle). The vent gases from this washer were likely venting through the stock chute to the blow tank. 94  Chapter 5: Materials and Methods  8.  The screen dilution tank flow was estimated because the velometer could not be used on the sample point due to interference with a handrail. The vent flow was assumed to be equal to the volume displacement caused by the greatest rate o f level change in the tank.  9.  Some early variability in results was attributed to standard type 2 syringe needles damaging the Tedlar bag septum and the G C injector septum, with the resulting rubber material plugging the needle. This was rectified by replacing the needles with type 5 rounded tip type with the orifice in the side o f the tip o f the needle.  5.4  Activity Coefficient Modelling  The activity coefficient, y , for a volatile substance i can be modelled using the N R T L {  equation, which consists o f the first two terms o f Equation (3.11), presented in Section 3.1.2. For a binary system at infinite dilution, i.e., when the solute, i , concentration, x approaches zero, and i5  the solvent, j , concentration, x approaches unity, the N R T L equation reduces to: j5  ln(r,)= ^, + G ^  ( 5  .2)  This equation can be used for a binary non-electrolyte system such as for i = D M S and j = water. A s described in Section 3.1.2, the N R T L equation can be extended to the e N R T L equation to describe the effect due to the presence of electrolytes (such as dissolved salts), by the addition o f the last two terms in Equation (3.11). Black liquor is a complex aqueous mixture including many dissolved salts (Table 2.10). N o e N R T L binary parameters could be found in the literature for the T R S compounds and these salts. To simplify the system, the black liquor dissolved salts were treated as a single substance, and the system was modelled as ternary system consisting o f D M S water-black liquor sodium salts. The dissolved black liquor salts were assumed to consist o f a single cation (sodium) associated with a single anion, i.e., x = x = x , where x is the mole fraction, c refers to the cation, c a  c  a  a to the anion, and ca to the salt. This terminology is used for modelling of electrolyte systems using the e N R T L equation (Chen and Song, 2004). A s described in Section 2.7.1, the major anions in black liquor are hydroxide, hydrosulphide, carbonate, sulphite, sulphate, thiosulphate and organic salts. These latter substances include the  95  Chapter 5: Materials  and Methods  sodium salts of phenolates (dissolved alkali lignin), polysaccharinic acids, resin acids and fatty acids. A t low salt concentrations, negligible error is introduced by assuming all salts consist o f a single cation associated with a single anion, even when considering the disodium salts. This is because the e N R T L equation is based on the effective mole fraction, X , rather than the actual mole fraction, x. For example, for N a C 0 , which dissociates into two cations and a single anion, i.e., x 2  3  c  = 2x , the absolute value o f the ionic charge o f the anion w i l l be double, i.e., C = 1 and C = 2. In a  c  a  this case, the effective mole fraction o f the anion will be double the actual mole fraction, i.e., X = a  C x = 2 x = 2(x /2) = x , and the effective mole fraction o f the cation w i l l equal the actual mole a  a  a  c  c  fraction, i.e., X = C x = x . A l s o note that for molecular species, such as water, that do not c  c  c  c  dissociate, C, = 1, thus Xj = x,. W i t h these assumptions, the system can be modelled as a three component system with i = D M S , j = water, and ca = black liquor sodium salts. For a ternary system, r = r  iaca  , r  = r = r , and r  caj  CJ  aj  ica  = r  Jcac  cai  = r = r , r ci  ai  ica  = r  icac  = z" . There are nine adjustable parameters: the solute-solvent aca  a ; the solute-salt pairs, r , r , <r ; and the solvent-salt pairs, T- , r , <r . For this  pairs, r ,  V]  tJ  ica  caj  ica  caj  jca  system, with a solute, i , at infinite dilution in a solvent, j , with a single salt, ca, added, the e N R T L Equation (3.11) reduces to: , / l  r  \ x - G J , T J I + 2-x -G ,-r , V i ) = — T T J • j i + • ca • J  c a  G  2  c a  x,-G  c a  x  x  X  2  'Xca  x. -j  —  G-  X  - ,ca G  + x„  — jca  1  • "ca  j  T~ *ica ica  V  ^jca  J  +  2-x G c a  ' ca ' Gcaj ' caj  2  M  r , J  c a j  v  ~ X-  X  ;  ^+  T  2• „ - X^  •G 0  -  ^  (5.3)  ^"jca  f~\ X  j ' ^jca  +  X  ca  J  The G parameters are determined from the r a n d a parameters using Equation (3.12).  The  temperature dependencies o f the r parameters are modelled using the adjustable parameters a and b and Equation (3.13).  96  Chapter 5: Materials and Methods 5.4.1  Regression Analysis of Phase Equilibria Testing  Data  Excel was used to compile and analyse the phase equilibria testing data. The dimensionless Henry's constants were experimentally determined for all solutions at 20, 50, 70 and 90°C; from the Henry's constants the activity coefficients were calculated. The r a n d a parameters that provided the best fit for the e N R T L equation for these experimental activity coefficients were determined using regression; a statistical technique used to explain or predict the behavior o f a dependent variable.  Regression was used to find the relationship between variables using the regression  equation, in this case the e N R T L equation.  This mathematical model was fitted to a set o f  experimental data (activity coefficients) using the least squares method. The experimental data values for the activity coefficients at the various temperatures were entered into the first column o f the Excel spreadsheet. The calculated value for the activity coefficient based on the e N R T L Equation (3.11) were entered in the second column. The activity coefficient calculations were based on r a n d a parameters values entered into separate cells in the spreadsheet, with the "first guess"values arbitrarily set at one. The square of the difference between the experimental value and the calculated value was entered into the third column; the sum o f squares was totalled below this column. The best fit for the e N R T L equation was achieved when the sum o f squares was minimized (least squares criteria). Excel includes a "solver" tool which can be used to manipulate specified variables to maximize or minimize a calculated value. In this case, the sum o f squares cell was specified as the "Set Target C e l l " to be minimized. The rand a parameter cells were specified as the " B y Changing Cells," i.e., the manipulated variables. The solver tool determines the values for r a n d a that minimize the sum o f squares, i.e., it would determine the values for the adjustable parameters that provided a best fit for the e N R T L equation to the experimental data. Aspen Plus was also used to regress the experimental data to find the parameters that achieved the best fit for the e N R T L equation. When using Aspen in this way, the data regression option is chosen when setting up the new file. Experimental data is entered as " T P X Y " , i.e., temperature, pressure and mole fraction compositions o f the liquid and vapour stream are entered in the data file. The E L E C N R T L (another way to refer to e N R T L ) properties method is chosen, and the e N R T L parameters to be fitted are chosen, while others not used are set to zero. The Aspen Plus 97  Chapter 5: Materials and Methods  data regression file is then run to determine the best fit e N R T L r a n d a  parameters.  The experimental data were regressed using both the Excel solver tool and Aspen Plus, partly to check each procedure to ensure no mistakes were made in the process. This proved to be a good decision as different results were initially produced, as w i l l be discussed in Section 6.3.5.  5.5  V L E Modelling  The mill testing data were modelled using a V L E module based on the e N R T L activity coefficient correlation. For an adiabatic V L E module, i.e., where there is zero heat duty, emissions from process equipment can be predicted based on feed stream properties and the outlet pressure or temperature. The general form of the solution of the V L E module, also called a "flash" module, that can be incorporated into a mill heat and mass balance is shown in Figure 5.9.  V a p o u r (V,y,T,P)  Feed (F,z,T ) F  J  V L E Module calculation block  Liquid (L,x,T)  V L E module used to predict emissions o f volatile compounds F i g u r e 5.9:  For an adiabatic V L E module, the properties o f the inlet feed stream must be known, including flow, F, composition, z , and temperature, T , along with the outlet pressure, P (or F  temperature, T). From this information, i f vapour liquid equilibrium is established, the outlet temperature (or pressure), and the outlet vapour flow, V , and composition, y, and the outlet liquid 98  Chapter 5: Materials and Methods flow, L , and composition, x , can be calculated. The main component of the V L E module is the phase equilibrium Equation (3.7) presented in Section 3.1.1.  5.5.1  Phase E q u i l i b r i u m E q u a t i o n  The V L E o f each condensible component is determined using Equation (3.7): y P=r x P " ,i=l,n s  i  i  i  ,  i  (3.7)  The V L E of each noncondensible component can also be determined using the above equation, but since these components by definition will be in very low concentrations, the simpler Henry's law Equation (3.8), described in Section 3.1.1, is often used instead: y,P=-^-,i=l,n K  (3.8)  Hi  Henry's law constants, k , for many noncondensibles, such as oxygen and nitrogen, have H  been collected together from many literature sources by Sander (1999). To allow conversion between Henry's constant and an activity coefficient, Equations (3.7) and (3.8) are combined to get: k  The vapour pressure, P;  sat  H i  =  T-^aT  (5-4)  at the corresponding temperature, T, can be determined using the  extended Antoine Equation (3.21) given in Section 3.1.5, with the parameters for the T R S compounds given in Table 3.9.  99  Chapter 5: Materials and Methods 5.5.2  Mole Balance Equation  Assuming there are no reactions and that steady state has been established, the total moles entering the system must equal the total moles leaving the system: Fz, = V y , + L x , i = l , n  (5.5)  i  I  x, = 1  (5.6)  1 y, = i  (5.7)  X  (5.8)  i=l,n  i = l,n  z, = 1  i = l,n  F, V and L are the molar flows, and z,y, and x are the mole fraction composition o f component i for the feed, and outlet vapour and liquid streams, respectively, and n is the total number of components.  5.5.3  Energy Balance Equation  In steady state, the total energy entering the system must equal that exiting the system: F ! Z , H : i = l,n  = v X y i H r + LXx.H, 1  i = l,n  (5.9)  i=l,n  To solve this equation, the enthalpy, H , o f each component must be known. For a case involving black liquor, which consists o f many substances which are often not defined, the enthalpy o f the feed liquor stream and the outlet liquor stream can determined using an empirical specific heat correlation given by Grace et al. (1989): Cp, ,ac L,c.uor = B  k  1.0 -  (l - C ) • S PfS  S is the percent total dissolved solids in the black liquor, and C solids, which can range from 0.3 to 0.5 (Grace et al. 1989).  100  Ps  (5.10)  is the specific heat of the dissolved  Chapter 5: Materials and Methods 5.5.4  Temperature (Boiling Point Rise) Equation  The boiling point rise ( B P R ) is defined as the difference between the boiling temperature o f a liquid containing dissolved solids and that o f the pure liquid with no dissolved solids. For a flashing liquid, the temperature o f the vapour w i l l match that o f the liquid, with the vapour superheated by the amount o f the B P R . The B P R for black liquor can be estimated using the following equation (Grace et al., 1989): (5.11)  The fraction S/(l-S) is the solids to water ratio in black liquor. The B P R is given in units of degrees Celsius. The average constant for this equation is 7, but it can range from 5 to 9, depending on the composition of the dissolved solids in the black liquor (Grace et al. 1989). The superheated vapour leaving the liquid vapour interface is at temperature T, with the saturated vapour temperature, T , sat  determined from the temperature and the B P R : sat  5.5.5  Solution of V L E  T - BPR  (5.12)  Model  The solution of the adiabatic V L E flash model involves the simultaneous solution of multiple non-linear equations. This includes activity coefficient, vapour pressure, phase equilibrium and mole balances for each component, along with overall energy balances. The mathematical solution may also require correlations to describe other properties such dissociation effects and liquid boiling point rise. These equations are summarized in Figure 5.10.  101  Chapter 5: Materials and Methods  Feed stream (F,z,T ,P) F  I  Electrolyte effects using eNRTL equation = fi(x,T)  Dissociation effects = f(x,T)  I  I  W-M  olution of multiple^ non-linear equations (Newton-Raphson or equivalent) .  | Activity coefficients using NRTL equation = «[x,T)  I  Pure component vapour pressure using extended Antoine equation = f(T)  / / / /  Boiling point rise effects using Grace equation = f(x,T)  I Energy balance = fi(F,V,L,x,y,z,T, T ,H) F  I  I  Mole balances = f(F,V,L,x,y,z)  Phase equilibria balances =f(7,x,y,P,P ) sat  Outlet stream (V,L,x,y,T, T ,P) sat  Figure 5.10: Summary o f V L E module calculation block nonlinear equations that require simultaneous solution using a Newton-Raphson or equivalent technique  In the case where the liquid feed stream is below its bubble point at the vessel operating pressure, the vapour flow w i l l be zero, unless a noncondensible component such as nitrogen or oxygen is present. These can enter either entrained with the feed liquid or as a separate feed stream, such as air entering a tank through an opening. This air stream may be introduced deliberately as sweep air or it may be undesired, such as tramp air entering through a poorly sealed overflow opening. Tanks at Howe Sound, including the filtrate tanks and blow tank, include vacuum breakers 102  Chapter 5: Materials and Methods  and are designed to be sealed so that any air that does enter the system is considered tramp air. The tramp air can be incorporated into a V L E balance as shown in Figure 5.11.  F i g u r e 5.11  V L E Module vapour and liquid <by-passes  A tramp air by-pass around the V L E module can be used to account for insufficient time for the tramp air to reach equilibrium with the liquid phase. A liquid by-pass can be used to account for incomplete mixing in the liquid phase. For example, liquor entering a tank may short-circuit to the suction o f the liquor outlet causing stratification o f the concentration o f the contaminants in the liquid phase in the tank. If these by-passes are required, the tramp air and liquor by-passes w i l l have to be determined for each individual piece o f equipment. Part o f the objective o f this work was to investigate whether the process equipment tested during the mill testing program was operating at equilibrium, or i f some type o f by-pass was required to fit the data.  103  Chapter 5: Materials and Methods 5.5.6  C o m m e r c i a l Software V L E M o d u l e s  A V L E module incorporating the Newton-Raphson method was programmed in Matlab (Mathworks) to solve a ternary system involving the simultaneous solution o f ten non-linear equations. The components for this system include water, methanol and nitrogen, with nitrogen classified as a noncondensible. This Matlab program is included in Appendix C . This program is limited to three components, so is o f limited practical use, but it was useful as a training tool with the programming o f the equations leading to a better understanding all o f the factors governing the mathematical solution. Simulation software such as Aspen Plus and C A D S i m Plus include pre-programmed V L E modules designed for multiple component systems. Aspen Plus includes a V L E module referred to as "Flash2" with their simulation software.  For this module, Aspen provides a number o f  correlations, including the e N R T L equation, their recommended method to model electrolyte systems.  If experimental data are unavailable, Aspen Plus also includes the U N I F A C group  contribution method to estimate activity coefficients. C A D S i m Plus was also used because it has a strong focus on the pulp industry. C A D S i m incorporates many empirically fitted correlations unique to the kraft pulping industry, including a properties database for fibre, alkali lignin, organic and inorganic dissolved solids and black liquor. For example, it includes Equations (5.10) and (5.11), the specific heat and B P R correlations for kraft black liquor. C A D S i m also includes many modules specific to kraft pulp mills such as diffusion washers, blow tanks, drum-type decker washers, etc., which make programming heat and material balances much simpler. C A D S i m Plus is used at many mills, particularly in Canada, including Howe Sound Pulp and Paper, where mill testing for this research was conducted.  The offices o f Aurel Systems, the  developers o f C A D S i m , are located near the University o f British Columbia; therefore, it was very convenient for support services. They were also willing to extend and modify C A D S i m to meet the requirements o f this work, including the incorporation o f a V L E module. Commercial simulation software can be costly; Matlab, C A D S i m Plus and Aspen Plus were made available to University o f British Columbia students for research purposes.  104  Chapter 6: Results and Discussion Chapter 6 Results a n d Discussion  The premise for this work is that emissions o f T R S compounds from kraft pulp m i l l processes can be predicted based on modelling o f their vapour-liquid equilibria behaviour. Before any phase equilibria or mill testing was conducted, preliminary phase equilibria calculations were performed using published data to determine i f volatile components in kraft pulp m i l l processes were at or near vapour-liquid equilibrium.  6.1  Phase Equilibria Testing using Published Data  Since no relevant published mill testing data could be found for the T R S compounds, preliminary analysis was done using methanol. Methanol, like methyl mercaptan and dimethyl sulphide, is formed in the digester in an undesired side reaction. It is relatively volatile compared to water, but less so than the T R S compounds (Figure 3.1), making it a good candidate for testing the relative merits o f this method. Due to the recent implementation of the Cluster Rule in the U . S . , which specifies methanol as a surrogate for emissions of hazardous air pollutants, fairly extensive methanol emissions testing has been completed by the National Council for A i r and Stream Improvement ( N C A S I ) . Data was extracted from N C A S I reports ( N C A S I , 1994a; 1994b; 1996) and from testing conducted by N C A S I for G u etal. (1998a). If the liquid and vapour are in equilibrium, with methanol defined as i , then its vapour mole fraction, y can be predicted from the liquid mole fraction, x using Equation (3.7). i5  i5  y P = / x P i  i  i  ,  (3.7)  B  i  The total pressure o f the system, P, is atmospheric in all cases for the published data. The vapour pressure, P , of methanol at the process temperature, can be determined using the extended Antoine sat  Equation (3.21) in Section 3.1.5, using parameters in Table 3.9. The activity coefficient, y , for {  methanol in water can be determined from the N R T L equation, the first two terms of Equation (3.11) in Section 3.1.2 using parameters in Table 6.1. These parameters were taken from Chen and Song  105  Chapter 6: Results and Discussion  (2004), who extracted these figures from the databank o f Aspen Plus version 12.1 (Aspentech). Aspen Plus is based on D E T H E R M , an extensive thermophysical properties databank compiled from numerous published sources ( D E T H E R M ) .  Table 6.1: Methanol(i) in waterQ) parameters for N R T L equation (Chen and Song, 2004) N R T L Parameter  Value  u  -2.626  a  4.824 h  828.387  h  -1329.544 0.3  Because the published methanol testing data did not include details on the composition o f the liquid streams, except for the methanol concentration, a binary methanol-water system was assumed and any potential effects from other solvents or dissolved solids were ignored. The published data also did not include details on liquid flows to and from equipment, so mass and energy balances could not be completed, and methanol emissions could not be predicted on a mass basis. The calculations that follow are not done to predict mass emissions, but solely to test i f methanol, as a surrogate volatile compound, is at or near equilibrium in any kraft mill equipment. Data from over 225 vapour and 250 liquid samples were collected from the N C A S I reports into an Excel spreadsheet for analysis (Appendix D). O f these data, only a subset was used, due to a number o f limitations. Data were considered i f they could be matched together in pairs; e.g., for a tank, corresponding samples o f the vent stack vapour stream and the liquid outlet stream were required, as these would be the streams potentially at equilibrium. O f these pairs, only those vapour and liquid samples collected at exactly the same time were used, to exclude variability in the process. N C A S I noted that their liquid measurements might be questionable, as a direct injection G C method was used to determine the methanol concentrations. This method is susceptible to matrix interference, especially in the black liquor samples. For vacuum drum washer filtrate tanks, Figure 6.1 shows a comparison o f measured 106  Chapter 6: Results and Discussion  methanol vent stack vapour outlet concentration compared to the predicted equilibrium concentration based on the outlet filtrate (black liquor) methanol concentration using Equation (3.7).  2000 Measured LU Predicted > o. 1500 Q.  C >  1000  O  c  CO  sz  0>  500  CO  > <  cn  Tt  > > < o  Tt  > o  oo  > _l  oo  >  00  > —J  Equipment Identification Code  F i g u r e 6.1: Vacuum drum washer filtrate tank vent stack measured methanol concentration compared to predicted concentration based on outlet filtrate concentration  The letter in the identification code refer to the mill and the numbers refer to the specific equipment where the measurements were made. N C A S I does not state where these mills were located or provide any specific details for the equipment. A l l that is known is that for the vacuum drum washers measurements, shown in Figure 6.1, the 10 pairs o f measurements were taken from seven different washers at four different mills. In the majority of cases, the vapour-liquid equilibrium method predicts fairly well, with 6 o f 10 pairs predicting within 25%. The measured values range from 225 to 1493 ppm (mol) (average 710) with an average root mean squared error ( R M S E ) o f 361 ppm (mol) for the predicted values. Better agreement might be expected with a more accurate methanol testing technique and incorporation of the dissolved solids effects. 107  Chapter 6: Results and Discussion  The vacuum drum washer hood and diffusion washer comparisons are shown in Figure 6.2 and 6.3, respectively. For these, the predicted equilibrium was based on the inlet wash liquor concentration. This might not seem intuitive as the first thought might be that outlet streams should be in equilibrium, but in displacement washing, the inlet wash liquor is the liquid in most intimate contact with the outlet vent gas. G u et at. (2001) used this basis to design their emissions module for W i n G E M S , except for the vacuum drum washer they also included a term for the inlet vat area of the washer based on the inlet stock concentration. Since the published data did not include this latter information, the predicted value shown in Figure 6.2 are based only on the shower water concentration.  mv)  1000  o_ Q. C  Measured D Predicted! 800 600  > 75  400  c  CO  0)  200 0  ^ ^ > > b <o < *o <o* > >  (O (/)(/)</) CQ DO DQ < < < < CD CO. CO.  X X X  r m io w m in  CO CO  *ooooo ****  ffllll  JJJ  XX  Equipment Identification Code Figure 6.2: Decker washer hood vent stack measured methanol concentration compared to predicted concentration based on inlet wash liquor concentration  108  Chapter 6: Results and Discussion  1500 > E  CL  — 1000 .*-» c CD > c  I  500  0)  > >  >  O  >  O  >  >  _  (D O  I  _  I  J  <  <  Equipment Identification Code Figure 6.3: Diffusion washer vent stack measured methanol concentration compared to predicted concentration based on inlet wash liquor concentration  For the decker washer hoods, 10 o f 17 pairs predict values within 50% o f the measured values. The measured values range from 64 to 916 ppm (mol) (average 256) with average R M S E of 260 ppm (mol) for the predicted values. For the diffusion washers, 7 o f 11 pairs predict within 50%. The measured values range from 57 to 1350 ppm (mol) (average 576) with an average R M S E of 308 ppm (mol) for the predicted values. Results were more scattered for weak black liquor tanks, as can be seen in Figure 6.4. The measured values ranged from 1 to 2600 ppm (mol) (average 556) with an average R M S E of 913 ppm (mol) for the predicted values. The poor prediction may be a result o f the more variable operation of these liquor tanks compared to brown stock washing equipment. For example, i f more liquor is being withdrawn from a liquor tank than is being pumped in, there may be a reverse flow in the vent pipe, drawing in atmospheric air, which would result in a l o w or non-detectable methanol concentration reading in the vent gas.  109  Chapter 6: Results and Discussion  3000 Measured • Predicted  •ill  JLrJ  §§§^s|||<<<--oo«  i i i  inti  2  0 0 0 0 0 0 & > & « « « « < \ - i - \ - \ - \ -  222  OOOOO  Equipment Identification Code F i g u r e 6.4: Weak black liquor tanks vent stack measured methanol concentration compared to predicted concentration based on liquor outlet concentration The poor prediction for weak black liquor tanks (Figure 6.4) can be contrasted with the results for vacuum drum washer filtrate tanks (Figure 6.1). The level is typically held constant in filtrate tanks, giving a more consistent positive vapour flow, which should result in a more accurate prediction. A s described in Section 6.7, testing at the Howe Sound mill indicated that liquor storage tanks were only minor contributors to overall T R S emissions (less than 3%); therefore, the decision was made to focus testing and modelling work on the brown stock washing area.  Taking into  account variability in the pulping process, sampling and testing limitations, and lack o f reported details in the published data (such as dissolved solids concentration in the liquid), the results using published data for methanol (Figures 6.1 to 6.3) showed enough promise to proceed with a study plan for the T R S compounds.  6.2  Phase E q u i l i b r i a Testing Results  The complete results o f phase equilibria testing o f D M S in all solutions are shown in the form o f an activity coefficient in Table 6 . 2 . The raw data for phase equilibria testing are provided 110  Chapter 6: Results and Discussion  in Appendix E. Each activity coefficient given in this table was averaged from a minimum o f three data points, with each data point calculated from the G C output averaged from three separate injections. The standard deviations given in this table, and the 95% confidence bars used in the following figures, were calculated from these three or more data points.  T a b l e 6.2:  Vapour-liquid equilibrium activity coefficients for D M S solutions tested  Solution  Activity coefficient (± standard deviation) 20°C  50°C  70°C  90°C  1  173 ± 6  145 ± 2  128 ± 5  124 ± 1  2  176 ± 4  154 ± 2  133 ± 6  122 ± 3  3  181 ± 7  159 ± 7  142 ± 4  126 ± 5  4  200 ± 14  154 ± 4  133 ± 3  129 ± 6  5  220 ± 19  160 ± 9  139 ± 10  132 ± 4  6  237 ± 2 1  186 ± 14  158 ± 6  151 ± 10  7  276 ± 24  225 ± 0  180 ± 7  171 ± 5  8  351 ± 6  292 ± 16  243 ± 3  202 ± 4  9  255 ± 7  208 ± 6  183 ± 4  170 ± 14  10  261 ± 4  211 ± 2  189 ± 0  174 ± 3  11  269 ± 18  203 ± 2  168 ± 4  164 ± 13  12  314 ± 2 4  224 ± 1 1  187 ± 6  179 ± 14  13  251 ± 6  223 ± 5  214 ± 18  173 ± 10  To illustrate the effect of the addition o f increasing amounts o f alkali lignin (solutions 4 and 5), the shift in the activity coefficient o f a binary D M S - w a t e r system is shown as a function o f temperature in Figure 6.5. To provide a baseline for comparison purposes, binary DMS-water data (solution 1) are shown in Figures 6.5, 6.6 and 6.7. A l l data points on the three figures are shown with 95% confidence bars.  Ill  Chapter 6: Results and Discussion  400 -6 wt% Alkali Lignin in D W  -350  -3 wt% Alkali Lignin in D W  Q)  1300  - Distilled Water (DW)  **-  <j250  &  >200  *->  u  <150 100 290  310  330 350 Temperature (K)  370  F i g u r e 6.5: Temperature effect on DMS-water activity coefficient at various alkali lignin concentrations (solutions 4 and 5)  The increase in the activity coefficient of a binary DMS-water system caused by the addition of a mixture o f sodium salts (solutions 6, 7 and 8), is illustrated in Figure 6.6.  400 « - 6 wt% Sodium Salts in D W »- 4 wt% Sodium Salts in D W Sodium Salts in D W Water (DW)  100 290  310  330 ,350 Temperature (K)  T  370  Figure 6.6: Temperature effect on DMS-water activity coefficient at various sodium salts concentrations (solutions 6, 7, and 8)  112  Chapter 6: Results and Discussion The increase in the activity coefficient of a binary DMS-water system caused by the dissolved solids in black liquor is illustrated in Figure 6.7.  400  100  -I  ,  290  310  1  1  330 350 Temperature (K)  1  370  F i g u r e 6.7: Temperature effect on DMS-water activity coefficient at various total dissolved solids concentrations in black liquor (solutions 11 and 12)  From Figures 6.5 and 6.6 it can be seen that the addition o f sodium salts to a DMS-water solution shifts the equilibrium to a much greater degree than the addition o f an equal amount o f alkali lignin. This suggests that the shift in activity coefficient in black liquor seen in Figure 6.7 would be mainly due to the dissolved inorganic salts.  6.2.1  O t h e r Properties of Tested Solutions  The ash content o f the Sigma-Aldrich alkali lignin powder (used to prepare solutions 4 and 5) was measured at 20.9 wt%, while the Howe Sound alkali lignin powder (used to prepare solution 3) was measured at 6.4 wt%. These lignin ash samples were found to contain 21.4 and 15.7 wt% sodium, respectively. From this data, the total sodium in the Sigma-Aldrich alkali lignin sample was calculated to be 4.5 wt%, while the Howe Sound alkali lignin was calculated to be 1.0 wt%. 113  Chapter 6: Results and Discussion  The measured ash content o f the Sigma-Aldrich alkali lignin was much higher than the 3 to 7 wt% stated in the supplier's data sheet. A l k a l i lignin is typically recovered by acid precipitation, with the resulting "paste" washed with weak acid before drying into powdered form (Oilman, 2006). This was the method used to recover alkali lignin from the Howe Sound black liquor sample, as described in Section 5.2.2. The total sodium left in the alkali lignin w i l l be a factor of how well this paste is washed, because the sodium is stripped out by the acid. One possible explanation for the high ash content o f the purchased alkali lignin sample would be inefficient acid washing. . A n elementary composition analysis was done on the dissolved solids o f a sample o f Howe Sound weak black liquor. It was found to contain 20.7 wt% sodium, 0.8 wt% potassium and less than 0.1 wt % of other metals. This sodium content falls into the typical range o f 18 to 22 wt% given for typical softwood black liquor (Table 2.11). The measured p H , total dissolved solids, ash and sodium content o f all solutions is given in Table 6.3.  T a b l e 6.3: p H , tota dissolved solids, ash, and sodium content o f solutions tested Solution  pH  Total dissolved solids (wt%)  Ash (wt%)  Sodium (wt%)  1  7.0  0  0  0  2  12.0  0.04  0.04  0.02  3  12.0  3.1  0.27  0.08  4  8.7  3.0  0.63  0.13  5  9.1  6.0  1.3  0.27  6  12.8  2.0  2.0  0.86  7  13.0  4.0  4.0  1.7  8  13.2  6.0  6.0  2.6  9  12.8  6.6  3.3  1.4  10  12.9  7.8  3.9  1.6  11  12.5  6.6  3.2  1.4  12  12.6  9.7  4.8  2.0  13  12.9  8.2  4.1  1.7  114  Chapter 6: Results and Discussion  The addition of electrolytes, such as sodium salts, alters phase equilibrium behaviour, while no similar effect is theorized for non-ionic dissolved organic substances (Chen and Song, 2004). It is not clear what causes the equilibrium shift in the dissolved alkali lignin mixtures, but it was thought to be an ionic effect, either from residual inorganic salts in the alkali lignin, or due to the dissociation o f sodium phenolates, the main component o f alkali lignin (Grace et al., 1989).  6.2.2  C o n d u c t i v i t y as a F u n c t i o n o f S o d i u m C o n c e n t r a t i o n  One measure o f the ionic strength o f a solution is its conductivity. The term conductance refers to the ability o f materials to carry an electric current, with solutions referred to as electrolytic conductors. Under the influence o f an electric field, the flow o f current through an electrolytic conductor is accomplished by the movement of cations and anions. The alkali lignin mixtures were tested for conductivity, with the results shown in Table 6.4. For comparison purposes, dilutions o f the sodium salts solutions and black liquor samples were prepared that gave conductivities in a similar range to the alkali lignin mixtures.  T a b l e 6.4:  Conductivities o f alkali lignin mixtures, sodium salt solutions, and black liquor  Solution  Dilution  Sodium (wt %)  Conductivity (mS)  1  0  0  0  3  0  0.08  3.8  4  0  0.13  6.7  5  0  0.27  11.9  8  60:1  0.04  2.2  8  20:1  0.13  6.0  8  10:1  0.26  11.3  13  - 20:1  0.08  3.7  13  10:1  0.17  6.9  13  5:1  0.34  14.1  115  Chapter 6: Results and Discussion  In black liquor, sodium makes up a large fraction of the potential cation content (Table 2.11), with the balance mainly consisting o f potassium. This was confirmed by the results o f the ICP test conducted on the Howe Sound black liquor which indicated that sodium makes up 96 wt% o f the total metals in the sample. The ionic strength associated with sodium includes the salts and the hydroxyl and hydrosulphide ions (Equation 3.15), the latter of which is in equilibrium with hydrogen sulphide (Equation 3.14). Not all ions in black liquor are associated with sodium, such as methyl mercaptan (Equation 3.17), although these are at negligible concentrations compared to the ions associated with sodium. This raised the question, can the conductivity o f these solutions be related to their concentration o f sodium? To illustrate this, the conductivity is plotted as a function o f sodium concentration in Figure 6.8. Conductivity should increase linearly with increasing ionic strength, and this seems to be born out in the plot.  Sodium (wt%) Figure 6.8: Conductivity o f alkali lignin mixtures, sodium salts solutions, and black liquor as a function of sodium concentration  The conductivities correlate reasonably well, within 10%, with the sodium content of these solutions. This leads to the question, can the activity coefficient o f these solutions be related to their concentration o f sodium? 116  Chapter 6: Results and Discussion 6.2.3  A c t i v i t y C o e f f i c i e n t as a F u n c t i o n o f S o d i u m C o n c e n t r a t i o n  Activity coefficients are plotted as a function of sodium concentration for 90°C in Figure 6.9 (results for other temperatures were similar). For clarity, the data points for each solution are connected. A l s o for clarity, only the alkali lignin data is shown with 95% confidence bars.  220 - Black liquor  |200  —•— Sodium salts solution  o  —•—Lignin mixture  ? 180 o  o >>160 >  I  140 120 0.0%  0.5%  1.0%  1.5%  2.0%  2.5%  3.0%  Sodium (wt%) Activity coefficient at 90°C of alkali lignin mixtures, sodium salt solutions and black liquor, as a function o f sodium concentration  F i g u r e 6.9:  Figure 6.10 provides a close-up of the same data as Figure 6.9, but focussing on the bottom left corner o f the graph with a sodium concentration up to 0.5 wt%.  117  Chapter 6: Results and Discussion  140 —*r - Black liquor  .1 135 u  —•—Sodium salts solution —•—Lignin mixture  120  0.0%  0.1%  0.1%  0.2%  0.2%  0.3%  0.3%  Sodium (wt%) F i g u r e 6.10: Activity coefficient at 90°C (up to 0.5 wt% sodium) o f alkali lignin mixtures, sodium salt solutions and black liquor, as a function o f sodium concentration  The increases in the activity coefficient shown in Figures 6.9 and 6.10 correlate well with an increasing sodium content for all solutions. It appears that there may be a correlation between the activity coefficient and the sodium cation content o f the solution, irrespective o f which anion with which the sodium is associated. This suggested that the shift in vapour-liquid equilibrium in black liquor could be modelled based solely on the sodium concentration. To test this hypothesis, the data for the sodium salts were overlain with the data points for all of the black liquor samples (solutions 9 to 13) and plotted against their inorganic solids concentration in Figures 6.11 to 6.14, at 20, 50, 70 and 90°C, respectively. Even though there appears to be a linear response, there is no theoretical basis for this, so for clarity, the sodium salts solution data points are simply connected.  118  Chapter 6: Results and Discussion  400 •Sodium salts solution C O  350  Black liquor  £o 300 o o 250 > 200  o  <  150 100 0.0%  0.5%  1.0%  1.5%  2.0%  2.5%  3.0%  Sodium (wt%) F i g u r e 6.11: Sodium concentration effect on DMS-water activity coefficient for sodium salts and black liquor at 20°C  400 •Sodium salts solution Black liquor  *- 350  100 0.0%  0.5%  1.0%  1.5%  2.0%  2.5%  3.0%  Sodium (wt%) F i g u r e 6.12: Sodium concentration effect on DMS-water activity coefficient for sodium salts and black liquor at 50°C  119  Chapter 6: Results and Discussion  400 •Sodium salts solution  350  Black liquor  .2 o 300 -  !fc  < ou 250 o 200 o  <  150 100 0.0%  0.5%  1.0%  1.5%  2.0%  2.5%  3.0%  Sodium (wt%) F i g u r e 6.13: Sodium concentration effect on DMS-water activity coefficient for sodium salts and black liquor at 70°C  400 •Sodium salts solution  c  350  Black liquor  .2 "o 300  £  o o 250 > 200 o < 150 100 0.0%  0.5%  1.0%  1.5%  2.0%  2.5%  3.0%  Sodium (wt%) F i g u r e 6.14: Sodium concentration effect on DMS-water activity coefficient for sodium salts and black liquor at 90°C  120  Chapter 6: Results and Discussion  There appears to be a very good correlation between the increase in the activity coefficient and the sodium concentration, with the 95% confidence interval o f the black liquor activity coefficient data consistently overlapping the sodium salt activity coefficient data.  6.3  Phase Equilibria Testing Data Regression  The phase equilibria experimental data were regressed to fit functions using the software tools described in Section 5.2.6.  6.3.1  Fitting of Henry's Constant Equation  Henry's constants for all solutions tested at all temperatures were calculated from the activity coefficients in Table 6.2 using Equation (5.4). A regression analysis, similar to the technique described in Section 5.4.1, was used to determine the best fit parameters for the temperature dependent Henry's constant Equation (3.20). The adjustable parameters for this equation include Henry's constant at 298 K , and a temperature dependency constant, - A , H /R. The best fit for these S0  parameters are shown in Table 6.5.  T a b l e 6 . 5 : Regressed Henry's constants for dimethyl sulphide in solutions tested 1, 2 9 8 K K H  -A ,H/R  (mol fract/mol fract)/MPa  (K)  1  0.093  2780  20 to 90  2  0.091  2820  20 to 90  3  0.088  2870  20 to 90  4  0.082  2560  20 to 90  5  0.075  2440  20 to 90  6  0.069  2570  20 to 90  7  0.059  2590  20 to 90  Solution  S 0  121  Temperature range (°C)  Chapter 6: Results and Discussion  Table 6.5 (cont.): Regressed Henry's constants for dimethyl sulphide in solutions tested u  Solution  K  298K  H  -A  s o l  H /R  Temperature range (°C)  (mol fract/mol fract)/MPa  (K)  8  0.046  2600  20 to 90  9  0.063  2700  20 to 90  10  0.062  2660  20 to 90  11  0.061  2470  20 to 90  12  0.053  2350  20 to 90  13  0.063  2930  20 to 90  Henry's constant for a binary DMS-water system (solution 1) was found to be 0.093 (mol/mol)/MPa at 298 K , which compares favourably to the literature values presented in Table 3.5 in Section 3.1.4, which range from 0.085 to 0.100 (mol/mol)/MPa. The literature sources that also provided Henry's constant data for temperatures other than 298 K are shown on Figure 6.15 along with the experimental data and best fit line from this work.  0.35 •  30 ~ 0 25 JS a 20  5f  w £ 0  fro i  S ^ o  This work This work (best fit) Przyjazny et al. (1983) Dacey et al. (1984) De Bruyn et al. (1995)  15 10  0.05 0.00 270  290  310  330  350  370  Temperature (K) F i g u r e 6.15: Henry's constant for D M S in water as a function o f temperature  122  \  Chapter 6: Results and Discussion  In Figure 6.15, there is good agreement between the Henry's constant Equation (3.20) fitted from the experimental results from this work and that from the literature sources. There are two literature sources that give Henry's constant data for a DMS-water system with sodium salts added, with details given in Table 3.6.  Przyjazny et al. (1983) provide data for  solutions containing 0.7 M N a C l and 0.33, 0.66, 1.00, and 1.33 M N a S 0 , and Tormund (1997) 2  4  provides data for solutions containing 0.3 and 3.0 M N a C l . Henry's constant data for the sodium salts solutions from this work (solutions 6, 7, and 8) and for the two literature sources are plotted in Figure 6.16 against sodium concentration. Data are plotted at 40°C as this is the lower end o f the valid range for the Tormund (1997) data (40 to 80°C), and at 70°C, as this is the upper end o f the valid range for the Przyjazny et al. (1983) data (25 to 70°C).  •  This work 40°C  —•—Tormund (1997) 40°C — - P r z y j a z n y et al. (1983) 40°C •  This work 70°C  —O—Tormund (1997) 70°C —O -Przyjazny etal. (1983) 70°C  - — -- — - © - - . _ .  0.00 0 0%.  1.0%  2.0%  3.0%  4.0%  5.0%  6.0%  7.0%  Sodium (wt%) Henry's constant for D M S in water as a function of sodium salts concentration at 40°C and 70°C  F i g u r e 6.16:  Taking into account the limited data, there is reasonably good agreement between the experimental results from this work and that from the literature sources.  123  Chapter 6: Results and Discussion  6.3.2  F i t t i n g of N R T L E q u a t i o n for D M S - W a t e r System  A regression analysis, described in Section 5.4.1, was used to find the best fit for the N R T L equation, using the adjustable r a n d a parameters, to the experimental binary-DMS water activity coefficient data (solution 1). The N R T L equation consists o f the first two terms o f the e N R T L Equation (3.11), which can be simplified to Equation (5.2) for a system at infinite dilution.  Table 6.6: Regressed N R T L equation parameters for DMS(i)-water(j) system N R T L Parameter  Aspen Plus Results  Excel Results  u  1.00  2.93  by  4.04  10.1  2.48  2.06  567  549  0.3 (fixed)  0.3 (fixed)  a  \  The regression analysis was done using the data regression tool in Aspen Plus and a technique using the solver tool in Excel, with each returning a different set of parameters (Table 6.6). Even though the reported parameters are different, the fit is identical; i.e., the resulting best fit line calculated using the N R T L equation and shown in Figure 6.17 is the same using either o f the sets of parameters.  124  Chapter 6: Results and Discussion  200 190  • Experimental Data  c 180 o  — N R T L Equation Best Fit  •  t 110 100 290  310  330 350 Temperature (K)  370  Figure 6.17: DMS-water activity coefficient experimental data and N R T L equation best fit (R = 0.95) 2  It is common for different regression tools to report different best fit parameters. This is due to the fact that with four adjustable parameters, there are multiple sets of parameters that can provide a best fit. It is also possible for the same regression tool to report different sets o f parameters, with the result depending on a number of factors including the specified starting values, fit tolerances and regression criteria (objective function). Both tools used here incorporate a least squares criteria; the adjustable parameters that provide the best fit are determined by minimizing the sum of squares between the experimental value and the calculated value. The Excel technique was set up using a simple sum o f squares objective function incorporating the activity coefficient; Aspen Plus uses a more complex weighted sum o f squares objective function which also incorporates the second measured variable, temperature. Normally this objective function may be expected to produce a better fit, but because the experimental data was reported at set temperatures with varying activity coefficients, the objective function was heavily weighted to the activity coefficient, and both tools reported a set o f parameters (albeit different) that provide an equally good fit.  125  Chapter 6: Results and Discussion 6.3.3  C o m p a r i s o n of N R T L F i t to O t h e r S o u r c e s  The results o f the regression fit for this work were compared to the results o f a fit using the N R T L parameters of Olsson and Zacchi (2001). Because there are multiple solutions, the parameters can not be compared directly; instead, the results calculated from the regressed parameters must be compared. A s described in Section 3.1.4, Olsson and Zacchi held a^ and a^ constant at zero. Their parameters are given in Table 6.7 and the activity coefficients determined from these parameters are shown in Figure 6.18. The experimental results were also compared to the activity coefficient estimated using the U N I F A C model. The U N I F A C method is not based on experimental data for a DMS-water system; instead, it is based on a group contribution method discussed in Section 3.1.2. The U N I F A C method is incorporated into Aspen Plus, so this was used to generate the N R T L parameters for a binary DMS-water system. Aspen includes D M S in its databank, with the U N I F A C groups identified as C H S - and - C H based on a structure o f C H - S - C H . The N R T L parameters from the U N I F A C 3  3  3  3  method are given in Table 6.7 and the resulting activity coefficients are shown in Figure 6.18. Both Olsson and Zacchi (2001) and the U N I F A C method hold a^ and a^ constant at zero. To check the validity o f this, a regression was attempted using the experimental data from this work, with the results also show in Table 6.7 and Figure 6.18.  T a b l e 6.7:  D M S (i) in water (j) parameters for N R T L equation from other sources  N R T L Parameter  h  Olsson and Zacchi (2001)  U N I F A C (using Aspen Plus)  This work (holding a^ and a,; at zero)  \  0 (fixed)  0 (fixed)  0 (fixed)  by  696.07  37.31  2143.15  0 (fixed)  0 (fixed)  0 (fixed)  1576.49  746.81  1301.87  0.3 (fixed)  0.3 (fixed)  0.3 (fixed)  126  Chapter 6: Results and Discussion  For comparison purposes, the experimental activity coefficient data points determined from this work are shown in Figure 6.18.  700  s  ^  600  |  500  s  •  Experimental Data N R T L Best Fit, aij = aji = 0 - - Olsson and Zacchi — 'UNIFAC  s s s  T.  ss s  % 400  o o  >,300 +J £ 200  u  <  100 0  —  1  290  310  330 350 Temperature (K)  370  F i g u r e 6.18: Activity coefficients determined from Olsson and Zacchi (2001) N R T L parameters, U N I F A C parameters and best fit to experimental data and holding a^ and a constant at zero (R = 0.26) 2  jf  The N R T L parameters supplied by Olsson and Zacchi (2001) overestimate the activity coefficient by a large degree, while the U N I F A C parameters underestimate by almost equally large degree. It is not clear why either provide such a poor fit to the experimental data. The work o f Olsson and Zacchi (2001) involved mixtures at much higher concentrations, so they may not have been concerned with the accuracy at infinite dilution when regressing their data. The DMS-water mixture is highly non-ideal, which likely explains the error in the U N I F A C method, which in general loses accuracy as the mixture moves away from the ideal. In either case, it does not appear that holding a and fj  constant at zero is a good simplification. The best fit that could be achieved with  the experimental data from this work with a^ and a^ fixed at zero resulted in an R o f 0.26 (Figure 2  6.18) versus an R o f 0.95 when these parameters are allowed to vary (Figure 6.17). 2  127  Chapter 6: Results and Discussion 6.3.4  Range of Validity for Infinite Dilution  The activity coefficient for a DMS-water system, using the parameters from Table 6.6, was calculated using the N R T L Equation (3.11) and a simplified version o f the N R T L Equation (5.2). The latter equation was simplified by assuming that the solute D M S was at infinite dilution in the solvent water.  Over the temperature range o f 20 to 90°C, the maximum error introduced by  assuming infinite dilution is 0.01% at 100 ppm (mol) and 0.1% at 1000 ppm (mol). The same assumption is made when using Henry's constant to model a system, with the same error introduced. The highest concentration measured as part o f this work is less than 100 ppm (mol), thus the assumption o f infinite dilution is applicable because the introduced error is negligible.  6.3.5  F i t t i n g of e N R T L E q u a t i o n for D M S - W a t e r - S o d i u m Salts System  The binary DMS-water N R T L parameters determined from this work (Table 6.6) were then used in the e N R T L equation to allow solute-salt parameters to be fitted. The sodium salts (solutions 6, 7, and 8) activity coefficient data were fitted using the e N R T L Equation (3.11). A s discussed in Section 5.4, the system was modelled as a ternary DMS(i)-water(j)-black liquor sodium salts(ca) system. The e N R T L equation is based on mole fractions, with the mole fraction sodium content, x , ca  calculated from the weight fraction based on the composition given in Table 5.1. The mole fractions of sodium used were 0.0067, 0.0133, and 0.0200 for 2, 4 and 6 wt%, respectively. For a dilute weak electrolyte system, a good fit can usually be achieved by fixing the saltsolute and salt-solvent parameters to zero. A s well, it is normal to fix the solvent-salt arparameters at 0.2 (Chen and Song, 2004). For regression using Aspen Plus, it was discovered, after much trial and error, that fixing the solvent-salt and solute-salt r parameters at zero resulted in the r parameters defaulting to 8 and -4 for water-ion and ion-water, respectively, and 10 and -2 for non-water-ion and ion-non-water, respectively. This was rectified by fixing the r parameters at 1 e-6 instead o f zero. The best fit e N R T L parameters are shown in Table 6.8.  128  Chapter 6: Results and Discussion  Table 6.8: Regressed e N R T L equation parameters for DMS(i)-water(j)-black liquor sodium salts (ca) system e N R T L Parameter  DMS a  ,ca  39.1  b  ica  163  a  cai  0(fixed)  b  ca,  0(fixed)  r ica  T cai  ^ica  0.05  ^cai  a  ica  2.77  b  ,ca  2292  a  caj  0 (fixed)  b  ca,  0 (fixed)  *jca  r caj  ^ica  0.2 (fixed)  ^caj  For consistency, the experimental data and the best fit lines for the e N R T L equation are shown in weight percent sodium content, in Figure 6.19.  400 •  100 '— 0.0%  Exp. 20°C  -  i  0.5%  - r -  1.0%  -  T  -  1.5%  2.0%  2.5%  3.0%  Sodium (wt%) Figure 6.19: DMS-water-sodium salts activity coefficient experimental data and e N R T L equation best fit ( R = 0.95) 2  129  Chapter 6: Results and Discussion  The e N R T L equation, using the parameters in Table 6.6 and 6.8, was used to estimate the activity coefficients for the literature sources for the black liquor samples studied (solutions 9 to 13). The calculated activity coefficient values and experimental values are shown in Table 6.9, along with the percent difference between these figures. Table 6.9: DMS-black liquor activity coefficients Solution  Temperature (K)  Sodium (mole frac.)  9  293  10  Activity Coefficient Calculated  Experimental  Difference (%)  0.0063  252  255  0.9  293  0.0074  269  261  -3.1  11  293  0.0061  251  269  6.8  12  293  0.0090  299  314  5.1  13  293  0.0078  275  251  -8.5  9  323  0.0063  202  208  2.9  10  323  0.0074  214  211  -1.4  11  323  0.0061  202  203  0.6  12  323  0.0090  235  224  -4.5  13  323  0.0078  218  223  2.5  9  343  0.0063  179  183  2.4  10  343  0.0074  189  189  0.3  11  343  0.0061  178  168  -5.8  12  343  0.0090  206  187  -9.3  13  343  0.0078  192  214  11.4  9  363  0.0063  161  170  6.0  10  363  0.0074  169  174  3.3  11  363  0.0061  160  164  2.7  12  363  0.0090  183  179  -2.1  13  363  0.0078  171  173  0.9  130  Chapter 6: Results and Discussion There is good agreement, typically with only a few percent difference and no more than 12%, between the activity coefficient calculated using the e N R T L equation and the experimental values. The data are also shown on a scatter diagram in Figure 6.20.  350 300 ro  co 250  Q  2c 200 <D  .i_1 1 5 0 o *100 LU  50 0 0  50  100 150 200 250 300 350 eNRTL Prediction  Comparison of activity coefficient determined from e N R T L equation to black liquor experimental data (solutions 9 to 13) Figure 6.20:  The e N R T L Equation (3.11), using the parameters in Table 6.6 and 6.8, was used for modelling the D M S vapour-liquid equilibrium for black liquor systems for the m i l l testing data presented in Section 6.4.  6.3.6  Fitting of e N R T L E q u a t i o n for H S - , M M - a n d D M D S - W a t e r - S o d i u m Salts Systems 2  Although D M S was used as a surrogate compound for modelling T R S emission in the brown stock washing area, there are other areas o f the mill, such as the black liquor evaporators, where modelling for each individual T R S compound may be desirable. Activity coefficients for H S , M M 2  131  Chapter 6: Results and Discussion  and D M D S were calculated using Equation 5.4 from the Henry's constants found in the literature (Tables 3.1 to 3.8). The data o f Barrett et al. (1988), Przyjazny et al. (1983) and Tormund (1997) were used because solutions with sodium salts were also tested. Using the same regression technique that was used for D M S , the best fit parameters for the e N R T L equation were determined; these are given in Table 6.10.  T a b l e 6.10: Regressed e N R T L equation parameters for H S - , M M - and DMDS(i)-water(j)-sodium salts (ca) system 2  e N R T L Parameter  H S  MM  DMDS  42.8  1.87  2.76  -190  -104  24.6  4.5  4.71  4.99  -350  -414  353  0.3 (fixed)  0.3 (fixed)  0.3 (fixed)  60.1  -0.22  75.8  ica  -78.6  3929  -9102  ^•cai  0 (fixed)  0 (fixed)  0 (fixed)  t>cai  0 (fixed)  0 (fixed)  0 (fixed)  0.05 (fixed)  0.05 (fixed)  0.05 (fixed)  jca  8.78  17.5  19.5  jca  -145  -2370  -1699  0 (fixed)  0 (fixed)  0 (fixed)  0 (fixed)  0 (fixed)  0 (fixed)  0.2 (fixed)  0.2 (fixed)  0.2 (fixed)  2  a  u  \ %  h  \ a  lj =  a  sl  T-ica b  Tcai•  ^ica  ^cai  ^jca b  O  caj  a  r caj  b ^jca  caJ  ^cai  The parameters given in Table 6.10, and those determined for D M S and given in Tables 6.6 and 6.8, were used to calculate activity coefficients at a typical brown stock washing temperature o f 80°C; the results are shown in Figure 6.21.  132  Chapter 6: Results and Discussion  o 2500 o  ©  00  c  2000 — DMDS --DMS --- MM - H2S  o  o 1500 O  1000  > o  500  <  0  o  0.0%  1.0% 2.0% Sodium (wt%)  3.0%  Figure 6 . 2 1 : Activity coefficients determined from the e N R T L equation for the T R S compounds at 80°C  The D M D S activity coefficients are an order o f a magnitude higher than the next highest, D M S , but this is still considerably less than for wood extractives such as the terpenes, which have activity coefficients that exceed 100,000 (Fichan et al., 1999). Hydrogen sulphide and methyl mercaptan w i l l dissociate at high p H (Figure 3.2).  The  undissociated fraction, i.e., the fraction that will potentially be equilibrium with the vapour phase, can be estimated using Equations 3.16 and 3.18.  6.4  Mill Sampling and Testing Results  Sample collection and testing was conducted at the Howe Sound Pulp and Paper mill located at Port Mellon, British Columbia. Composition data for liquid and vapour streams at a pulp mill were required to test the concept o f using vapour-liquid equilibrium correlations to estimate T R S emissions. Since no such data could be found in the literature, a mill testing program was organized. In the kraft pulping process, for non-combustion sources, the T R S compounds are mainly emitted from the digester area and from the black liquor evaporation plant. Not including sources collected to the C N C G system, the brown stock washing T R S emissions are much higher than those 133  Chapter 6: Results and Discussion  from the black liquor evaporation area, which was confirmed as part of this work, so m i l l testing was focussed in the brown stock washing area. Testing around the brown stock washing area o f the mill was done from mid September to early December 2005, with samples collected on twelve days spread over this period. The raw data from these testing sessions are provided in Appendix F. Operating data, required to develop heat and mass balances across the system, were collected from the mill-wide optimization system ( M O P S ) historian. The M O P S historian data are included in Appendix G . The results of the twelve days o f testing are summarized in Tables 6.11 to 6.22.  T a b l e 6.11:  M i l l test results for September 16, 2005  VAPOUR SAMPLES  Time  Flow AnrVmin  Temp. °C  Relative  H2S  MM  DMS  DMDS  Humidity ppm (mol) ppm (mol) ppm (mol) ppm (mol) kg S / day kg S / day kg S/day kg S/day  VS6  Decker Washer Filtrate Tank  13:30  15.1  83.0  100%  VS6  Decker Washer Filtrate Tank  15:45  15.1  83.0  100%  LIQUOR SAMPLES  Time  pH  LS6 LS6  13:30 15:45  11.7 11.7  Temp. °C 80.0 80.0  Decker Washer Filtrate Decker Washer Filtrate  T a b l e 6.12:  Dissolved  nd 0.0 nd 0.0 H2S  nd 0.0 nd 0.0 MM  716 52.4 17.1 2.5 545 27.3 13.0 1.3 DMS DMDS  Solids ppm (mol) ppm (mol) ppm (mol) ppm (mol)  nd nd  nd nd  1.84 1.26  0.17 0.01  H2S  MM  DMS  DMDS  M i l l test results for September 21, 2005  VAPOUR SAMPLES  Time  Flow AiwVmin  Temp.  °c  Relative  Humidity ppm (mol) ppm (mol) ppm (mol) ppm (mol) kg S/day kg S / day kg S / day kgS/day  VS 1 Diffusion Washer Filtrate Tanks  14:10  3.2  60.0  LIQUOR SAMPLES  Time  PH  LS2  14:10  11.7  Temp. °C 80.0  1 st Stage Diffusion Washer Filtrate  134  77% Dissolved  nd 0.0 H2S  nd 0.0 MM  2187 20.2 0.2 11.9 DMS DMDS  Solids ppm (mol) ppm (mol) ppm (mol) ppm (mol)  nd  nd  8.74  0.33  Chapter 6: Results and Discussion Table 6.13:  M i l l test results for September 22, 2005  VAPOUR SAMPLES  Flow  Temp.  AnvYmin  °C  10:00  15.9  75.0  LIQUOR SAMPLES  Time  pH  Temp.  LS6  10:00  12.0  80.0  VS6  Decker Washer Filtrate Tank  Time  °C  Decker Washer Filtrate  T a b l e 6.14:  Relative  MM  DMS DMDS  100% Dissolved  kg S / day  kg S / day  1.9 0.0 H2S  2.3 0.1 MM  kg S / d a y  kg S / d a y  1396 226 35.9 11.6 DMS DMDS  Solids ppm (mol) ppm (mol) ppm (mol) ppm (mol)  nd  nd  H2S  MM  2.91  0.65  M i l l test results for September 28, 2005  VAPOUR SAMPLES  Time  Flow Temp. °c  AmVmin  Relative  Diffusion Washer  16:05  3.2  52.0  71%  VS6  Decker Washer Filtrate Tank  11:30  15.1  52.0  71%  VS6  Decker Washer Filtrate Tank  16:05  15.1  62.0  70%  LIQUOR SAMPLES  Time  pH  Temp.  LS6 LS6  11:30 16:05  12.0 12.0  52.0 62.0  °C  Decker Washer Filtrate Decker Washer Filtrate  DMS DMDS  Humidity ppm (mol) ppm (mol) ppm (mol) ppm (mol)  VS2  Table 6.15:  H2S  Humidity ppm (mol) ppm (mol) ppm (mol) ppm (mol)  Dissolved  kg S / day  kg SI day  nd 0.0 nd 0.0 nd 0.0 H2S  nd 0.0 nd 0.0 nd 0.0 MM  kg S / day  kg S / day  132 5.4 0.7 0.1 251 3.1 6.5 0.2 194 4.1 4.9 0.2 DMS DMDS  Solids ppm (mol) ppm (mol) ppm (mol) ppm (mol)  nd nd  nd nd  H2S  MM  0.82 0.93  nd nd  M i l l test results for September 29, 2005  VAPOUR SAMPLES  Time  Flow  Temp.  AmVmin  °C  Relative  VS2  Diffusion Washer  16:00  0.6  63.0  100%  VS3  Blow Tank  16:00  54.5  75.0  100%  VS4  Screen Feed Tank  09:40  10.9  62.0  82%  VS5  Screen Dilution Tank  09:40  3.2  36.0  75%  VS6  Decker Washer Filtrate Tank  13:00  15.1  76.0  100%  VS7  Decker Washer Hood  13:00  159.9  63.0  86%  LIQUOR SAMPLES  Time  pH  Temp.  LS4 LS6 LS8  16:00 13:00 13:00  11.7 11.7 11.4  81.0 76.0 77.0  °C  Stock from Diffusion Washer Decker Washer Filtrate 0 2 Filtrate  135  DMS DMDS  Humidity ppm (mol) ppm (mol) ppm (mol) ppm (mol)  Dissolved  kg S / day  kg S / day  3.3 0.0 2.1 0.2 nd 0.0 nd 0.0 nd 0.0 nd 0.0 H2S  6.8 0.0 3.3 0.3 nd 0.0 nd 0.0 11.6 0.3 nd 0.0 MM  kg S / day  kg S / d a y  486 27.6 0.5 0.1 810 84.4 71.4 14.9 42.6 2.8 0.8 0.1 12.0 nd 0.1 0.0 2056 110 50.0 5.3 51.5 4.2 13.8 2.3 DMS DMDS  Solids ppm (mot) ppm (mol) ppm (mol) ppm (mol)  6.7% 4.9% 2.0%  nd nd nd  nd nd nd  6.96 4.94 0.33  1.30 0.40 nd  Chapter 6: Results and Discussion  T a b l e 6.16: M i l l test results for September 30, 2005 VAPOUR SAMPLES  Time  Flow AnrVmin  Temp.  Relative  112 S  MM  DMS DMDS  °C Humidity ppm (mol) ppm (mol) ppm (mol) ppm (mol) kgS/day kg S / day kg S / day kg S / day  VS1  Diffusion Washer Filtrate Tanks  08:30  4.3  80.0  81%  VS1  Diffusion Washer Filtrate Tanks  10:30  4.8  80.0  81%  VS2  Diffusion Washer  14:00  2.4  70.0  83%  VS3  Blow Tank  14:00  56.9  78.0  88%  Time  pH  Temp.  LIQUOR SAMPLES  °C  LS2 LS3 LS2 LS3 LS4 LS6  1 st Stage Diffusion Washer Filtrate 2nd Stage Diffusion Washer Filtrate 1 st Stage Diffusion Washer Filtrate 2nd Stage Diffusion Washer Filtrate Stock from Diffusion Washer Decker Washer Filtrate  08:30 08:30 10:30 10:30 14:00 15:00  11.9 11.9 12.0 12.0 12.0 11.9  83.0 82.0 83.0 82.0 81.0 79.0  Dissolved  3.9 0.0 5.4 0.0 3.4 0.0 nd 0.0 H2S  35.2 0.2 54.1 0.4 5.8 0.0 4.6 0.4 MM  14938 332 102.0 4.5 17336 216 133.1 3.3 952 52.0 3.7 0.4 1169 87.7 106.5 16.0 DMS DMDS  Solids ppm (mol) ppm (mol) ppm (mol) ppm (mol)  11.7% 9.3% 9.8% 8.2%  nd nd nd nd nd nd  nd nd nd nd nd nd  Relative  112 S  MM  47.5 19.0 39.7 20.5 7.36 4.32  6.25 2.53 6.15 2.45 1.56 1.11  T a b l e 6.17: M i l l test results for November 22, 2005 VAPOUR SAMPLES  Time  Flow  Temp.  Am'/min  °C  DMS DMDS  Humidity ppm (mol) ppm (mol) ppm (mol) ppm (mol) kg S / day kg S / day kg S / day kg S / day  VS1  Diffusion Washer Filtrate Tanks  15:00  3.2  70.0  83%  VS2  Diffusion Washer  15:00  0.6  61.0  95%  VS6  Decker Washer Filtrate Tank  10:00  19.3  75.0  100%  VS7  Decker Washer Hood  10:00  186.6  66.0  100%  LIQUOR SAMPLES  Time  pH  Temp.  LSI LS2 LS3 LS4 LS5 LS6 LS7 LS8  15:00 15:00 15:00 15:00 10:00 10:00 10:00 10:00  Stock from Digester 1 st Stage Diffusion Washer Filtrate 2nd Stage Diffusion Washer Filtrate Stock from Diffusion Washer Stock to Decker Washer Decker Washer Filtrate Stock from Decker Washer 0 2 Filtrate  °c  80.0 79.0 78.0 77.0 76.0 76.0 76.0 81.0  136  Dissolved  2.7 0.0 nd 0.0 nd 0.0 nd 0.0 ICS  21.7 0.1 4.0 0.0 10.5 0.3 nd 0.0 MM  16605 518 87.5 5.5 522 31.0 0.5 0.1 2471 162 77.0 10.1 64.8 3.9 2.4 20.1 DMS DMDS  Solids ppm (mol) ppm (mol) ppm (mol) ppm (mol)  nd nd nd nd nd nd nd nd  nd nd nd nd nd nd nd nd  27.3 36.0 20.0 7.69 5.10 5.02 0.21 0.50  5.57 4.64 2.40 0.86 0.52 0.63 0.03 nd  Chapter 6: Results and Discussion  T a b l e 6.18: M i l l test results for November 23, 2005 VAPOUR SAMPLES  Time  Flow Ani'/min  Temp.  Relative  H2S  MM  DMS  DMDS  °C Humidity ppm (mol) ppm (mol) ppm (mol) ppm (mol) kg S / day kg S / day kg SI day kg S/day  VS1  Diffusion Washer Filtrate Tanks  09:00  3.2  65.0  100%  VS3  Blow Tank  09:00  54.5  71.0  100%  VS6  Decker Washer Filtrate Tank  13:30  17.6  75.0  100%  VS7  Decker Washer Hood  13:30  186.6  65.0  91%  Time  pH  LIQUOR SAMPLES  Temp. Dissolved °C  LS1 LS2 LS3 LS4 LS5 LS6 LS7 LS8  Stock from Digester 1 st Stage Diffusion Washer Filtrate 2nd Stage Diffusion Washer Filtrate Stock from Diffusion Washer Stock to Decker Washer Decker Washer Filtrate Stock from Decker Washer 02 Filtrate  09:00 09:00 09:00 09:00 13:30 13:30 13:30 13:30  11.7 11.6 11.6 11.7 11.6 11.6 11.6 11.5  80.0 79.0 78.0 77.0 76.0 76.0 76.0 80.0  2.2 0.01 nd 0.00 nd 0.00 nd 0.00  H2S  12.1 0.06 2.6 0.23 nd 0.00 nd 0.00 MM  8976 154 48.0 1.7 1124 71.5 100.2 12.7 2725 122 77.5 6.9 204 7.0 63.4 4.4 DMS DMDS  Solids ppm (mol) ppm (mol) ppm (mol) ppm (mol)  13.4% 10.8% 8.9% 8.6% 7.6% 6.9% 4.5% 4.1%  nd nd nd nd nd nd nd nd  nd nd nd nd nd nd nd nd  Relative  H2S  MM  35.5 43.5 23.5 8.90 4.64 5.57 0.44 0.39  5.39 5.18 2.39 1.08 0.68 0.92 0.08 0.02  Table 6.19: M i l l test results for November 24, 2005 VAPOUR SAMPLES  Time  Flow  Temp.  Am /min  °C  3  DMS  DMDS  Humidity ppm (mol) ppm (mol) ppm (mol) ppm (mol) kg S/day kg S / day kg S/day kg S/day  VS1  Diffusion Washer Filtrate Tanks  09:30  3.2  65.0  100%  VS3  Blow Tank  09:30  56.9  72.0  100%  VS6  Decker Washer Filtrate Tank  13:30  18.4  72.0  100%  VS7 Decker Washer Hood  13:30  186.6  63.0  100%  LIQUOR SAMPLES  Time  pH  Temp. Dissolved °C  LSI LS2 LS3 LS4 LS5 LS6 LS7 LS8  Stock from Digester 1 st Stage Diffusion Washer Filtrate 2nd Stage Diffusion Washer Filtrate Stock from Diffusion Washer Stock to Decker Washer Decker Washer Filtrate Stock from Decker Washer 0 2 Filtrate  09:30 09:30 09:30 09:30 13:30 13:30 13:30 13:30  11.7 11.6 11.6 11.7 11.6 11.6 11.6 11.6  137  82.0 80.0 79.0 78.0 74.0 74.0 74.0 79.0  3.0 0.02 nd 0.00 2.6 0.08 nd 0.00  H2S  17.0 0.09 15.1 1.40 26.8 0.81 nd 0.00 MM  10138 125 54.2 1.3 1295 130 120.1 24.1 3789 69.5 113.9 4.2 185 8.1 57.8 5.1 DMS DMDS  Solids ppm (mol) ppm (mol) ppm (mol) ppm (mol)  nd nd nd nd nd nd nd nd  nd nd nd nd nd nd nd nd  28.1 31.3 19.7 7.32 6.97 7.88 0.82 0.31  3.94 2.59 1.79 0.89 1.12 1.31 0.21 nd  Chapter 6: Results and Discussion  Table 6.20: M i l l test results for November 30, 2005 VAPOUR SAMPLES  Time  Flow  Temp.  Am 7m in  °C  Relative  H2S  MM  DMS  DMDS  Humidity ppm (mol) ppm (mol) ppm (mol) ppm (mol) kg S/day kg S / day kg S / day kg S / day  VS1  Diffusion Washer Filtrate Tanks  15:00  3.2  64.0  100%  VS3  Blow Tank  15:00  56.9  70.0  100%  VS6  Decker Washer Filtrate Tank  11:00  13.4  74.0  100%  VS7  Decker Washer Hood  11:00  186.6  64.0  95%  Time  PH  Temp.  LIQUOR SAMPLES  °C  LSI LS2 LS3 LS4 LS5 LS6 LS7 LS8  Stock from Digester 1st Stage Diffusion Washer Filtrate 2nd Stage Diffusion Washer Filtrate Stock from Diffusion Washer Stock to Decker Washer Decker Washer Filtrate Stock from Decker Washer 02 Filtrate  15:00 15:00 15:00 15:00 11:00 1.1:00 11:00 11:00  11.6 11.6 11.6 11.6 11.4 11.4 11.4 11.4  Dissolved  2.2 0.01 nd 0.00 nd 0.00 nd 0.00 H2S  14.6 0.08 nd 0.00 8.4 0.18 nd 0.00  12886 69.1 692 64.5 1987 43.2 56.8 17.7  MM  DMS  157 1.7 58.2 10.9 111 4.8 4.3 2.7 DMDS  Solids ppm (mol) ppm (mol) ppm (mol) ppm (mol)  80.0 79.0 78.0 77.0 75.0 75.0 75.0 80.0  nd nd nd nd nd nd nd nd  nd nd nd nd nd nd nd nd  H2S  MM  12.9 33.8 22.6 7.20 5.18 4.38 0.43 0.13  2.23 6.75 3.15 0.85 1.07 0.46 0.10 nd  Table 6.21: M i l l test results for December 1, 2005 VAPOUR SAMPLES  Time  Flow  Temp.  Am'/min  °c  Relative  Diffusion Washer Filtrate Tanks  14:00  2.7  63.0  100%  VS3  Blow Tank  14:00  54.5  71.0  96%  VS6  Decker Washer Filtrate Tank  11:00  11.7  77.0  100%  VS7  Decker Washer Hood  11:00  186.6  65.0  100%  Time  pH  Temp.  Dissolved  °C  LSI LS2 LS3 LS4 LS5 LS6 LS7 LS8  Stock from Digester 1 st Stage Diffusion Washer Filtrate 2nd Stage Diffusion Washer Filtrate Diffusion Washer Stock Out Stock to Decker Washer Decker Washer Filtrate Stock from Decker Washer 02 Filtrate  14:00 14:00 14:00 14:00 11:00 11:00 11:00 11:00  11.6 11.6 11.4 11.5 11.7 11.7 11.7 11.7  138  81.0 80.0 79.0 78.0 76.0 76.0 76.0 81.0  DMDS  kg S / day kg S/day kg S / day kg S/day  VS1  LIQUOR SAMPLES  DMS  Humidity ppm (mol) ppm (mol) ppm (mol) ppm (mol)  3.2 0.01 nd 0.00 nd 0.00 nd 0.00 H2S  14.2 0.06 8.1 0.72 4.6 0.09 nd 0.00  16299 73.1 1095 97.6 1590 30.0 95.9 29.8  MM  DMS  150 1.3 65.7 11.7 61.0 2.3 4.5 2.8 DMDS  Solids ppm (mol) ppm (mol) ppm (mol) ppm (mol)  13.8% 12.7% 9.8% 8.5% 7.0% 6.7% 5.1% 4.5%  nd nd nd nd nd nd nd nd  nd nd nd nd nd nd nd nd  50.3 40.9 21.8 7.86 4.77 4.09 0.57 0.19  6.52 5.19 3.40 1.00 0.66 0.68 0.11 nd  Chapter 6: Results and Discussion  T a b l e 6.22: M i l l test results for December 2, 2005 VAPOUR SAMPLES  Time  Flow  Temp.  Am'/min  °C  Relative  H2S  MM  DMS DMDS  Humidity ppm (mol) ppm (mol) ppm (mol) ppm (mol) kg S / day kg S/day kg S/day kg S/day  Chip Bin (23/11/05)  13:30  48.0  78.0  88%  Chip Bin (24/11/05)  09:30  33.6  77.0  100%  Chip Bin (01/12/05)  14:00  43.2  80.0  100%  D N C G - total to boiler  09:45  255.9  19.0  100%  HBL Tanks  08:30  6.7  94.5  100%  W B L & Cond. Tanks (& sweep air)  09:00  10.1  35.0  100%  D N C G - total recovery area  09:20  16.8  48.0  100%  Time  pH  Temp.  LIQUOR SAMPLES  °C  Screen Feed Tank Liquor (29/09/05) 09:40 Screen Dilution Tank Stock (29/09/05 09:40  11.7 11.7  Dissolved  385 29.6 231 12.5 267 18.3 79.6 39.2 239 2.5 18.5 0.3 85.2 2.5 H2S  911 70,0 599 32.3 1145 78.7 245 120.7 387 4.0 32.3 0.6 163 4.8 MM  1486 11.5 114.2 1.8 1033 4.2 55.7 0.5 2854 5.9 196.3 0.8 767 28.5 378.1 28.1 264 94.2 2.7 1.9 218 14.6 4.0 0.5 215 38.3 6.3 2.2 DMS DMDS  Solids ppm (mol) ppm (mol) ppm (mol) ppm (mol)  76.0 76.0  nd nd  nd nd  2.24 2.32  nd nd  The mill operation was stable for all testing days, with one exception. The mill was shutdown from September 2 2  nd  to the early morning of the 28 . lh  The samples with the lowest  concentrations were collected on the 28 in the late morning and middle afternoon, apparently before th  the dimethyl sulphide concentrations could build up in the system. The concentrations were back up to "normal" levels by the next day. To keep dissolved alkali lignin from precipitating, the kraft pulping process is operated with sufficient excess alkali to keep the brown stock washing process above a p H o f about 11 and more typically between 11.5 and 12.5 (Grace etal., 1989). This was confirmed during this testing session, with the liquor samples ranging in p H from 11.4 to 12.0 (Tables 6.11 to 6.22). A s discussed in Section 3.1.4, hydrogen sulphide and methyl mercaptan are weak acids and are essentially fully dissociated above a p H o f 11.  A s expected, the hydrogen sulphide and methyl mercaptan  concentrations in the vapour samples were either below the detection limit or at very low concentrations, the highest measured being 5.4 and 54.1 ppm (mol) (Table 6.16), respectively. 139  Chapter 6: Results and Discussion  With hydrogen sulphide and methyl mercaptan concentrations typically below detection levels due to the high p H , and with very little oxygen in the system resulting in relatively low concentrations of dimethyl disulphide, dimethyl sulphide was the greatest contributor to the T R S in the vent gases. O n all testing days, dimethyl sulphide contributed over 90% o f the sulphur in the vent gases. Thus, for modelling purposes, it was decided to use dimethyl sulphide as a surrogate compound for T R S and all phase equilibria testing focussed on this compound, as discussed in Section 6.2.  6.4.1  Howe Sound Equipment Dimensions and Operating Conditions  Some D N C G systems are designed to include "sweep air." A n opening is included in the tank and the vacuum created by the D N C G collection system draws outside air through the tank, sweeping along the volatiles into the D N C G system. The sources at Howe Sound do not include sweep air, instead they are designed to be sealed against air ingress. A n y air that is drawn into the system is undesired and is referred to as "tramp air." A sealed system such as Howe Sound requires vacuum breakers to protect tankage, but the volumetric flow of N C G collected w i l l be lower and the mass loading o f volatiles w i l l be lower because there will be less stripping o f volatiles. Equipment dimensions, vapour-to-liquid volume ratios, and liquid phase residence times are provided for all equipment in Table 6.23.  140  Chapter 6: Results and Discussion T a b l e 6.23: Equipment dimensions and operating conditions Tank inside  Vapour-liquid volume ratio  Liquid flow (mVm  Residence time (m:  s l  Stage  Diffusion Washer Filtrate  Vertical  4.9 m  4.4  83  0.33  10.2  8.1  cylindrical steel  diameter by  tank  5.8 m high  2.9  58  0.24  8.1  6.8  10  1000  3.6  12  83  Tank 2  nd  Stage  Diffusion Washer Filtrate  (110 m ) 3  Vertical  4.9 m  cylindrical steel  diameter by  tank  3.8 m high  Tank B l o w Tank  'G  and volume  dimensions  l  c  Liquid volume (r  Type  Typical liquid level (m)  Equipment  (72 m ) 3  Vertical  14.4 m  cylindrical steel  diameter by  tank, partial  34 m high  cone  (4600 m ) 3  top/bottom Decker Washer  Drum washer  n/a  n/a  n/a  n/a  n/a  n/a  Decker Washer  Rectangular  14.3 m by  3.35  390  0.41  87  4.5  Filtrate Tank  concrete pit  8.2 m by 4.7  Hood  m high (550 m ) 3  141  Chapter 6: Results and Discussion  A simplified process flow diagram (Figure 5.3) and process description o f the brown stock washing area o f the mill was provided in Section 5.3.1. Besides the mechanical design o f the equipment, the process operation can also influence the potential equilibrium that may establish between the liquid and vapour phases in this equipment. The 2  n d  stage diffusion washer filtrate tank is located on top o f the 1 stage tank with both st  sharing a common overflow line, which is sealed where it enters the sewer. The 1 stage tank is st  vented v i a this overflow line to the 2  nd  stage filtrate tank, with the vent from the 2  n d  stage tank  collected to the D N C G system. Therefore, the vent vapour sampled on the "common" vent for these tanks w i l l be in contact, and potential equilibrium with, the contents o f the 2  nd  stage tank.  There was also the potential added complication caused by the diffusion washer operating on a 60 to 90 second cycle. During the last 10 seconds of this cycle, the extraction liquor flow from the diffusion washer to the filtrate tanks is stopped, causing a rapid drop in the liquor level in both of these tanks (the flow o f liquor pumped from the tanks remain constant). The operating level for the l  s l  stage filtrate tank is typically controlled at 75% (4.4 m), while the 2  n d  stage filtrate tank  normally operates at 100% level (2.9 m) with a portion o f the filtrate overflowing to the 1 stage st  tank. During the part of the wash cycle when the liquor flow to these tanks is stopped, the 1 and st  2  nd  stage filtrate tank levels drop to about 2.3 m and 1.3 m, respectively. The vapour flow in the vent  lines on these two tanks reverses during this period (this effect was confirmed during sampling o f the vent vapour). B y watching the liquor valves open and close, it was possible to collect the vent vapour samples during the period o f the cycle that liquor was flowing to the tank. A complicating factor for the blow tank is the potential for tramp air ingress through poorly sealed overflow openings. These overflows are large rectangular openings near the top o f the tank that are "sealed" with plastic sheets attached at the top and weighted at the bottom; openings were quite visible around the edges o f these sheets. The D N C G system draws a slight vacuum on the blow tank, which in turn can draw tramp air in through these overflow openings. The D N C G vent nozzle is located on top o f the blow tank, very near the overflow openings, so it is likely that most of the tramp air is drawn into the tank and right back out via the D N C G system. The Howe Sound decker washer hood is shown in Figure 6.22. A fibreglass hood encloses the drum washer, with the D N C G vent stack just visible exiting on top o f the hood at the far end.  142  Chapter 6: Results and Discussion  Figure 6.22: Decker washer at the Howe Sound pulp mill  For the decker washer, use o f a single wash liquor source simplifies the analysis, so there are only two liquid streams in contact with the vapour: the liquor in the stock feed and the wash liquor used for washing and for repulping. The wash liquor is filtrate from the post-oxygen delignification system washer ( 0  2  filtrate).  Brown stock is fed to the inlet vat o f the washer as a slurry at a consistency o f about 1% (similar to runny porridge). The stock is pulled onto the turning drum (which is half submerged in the feed brown stock), and the liquor is drawn from the stock through the drum screens by the vacuum inside the drum. This vacuum is formed by the filtrate liquor dropping down the seal leg to the filtrate tank. A series o f shower nozzles, with the first set located immediately after the stock has been pulled onto the drum, spray wash liquor onto the brown stock mat on the turning drum. The mat o f stock, at a consistency o f about 12% (similar to wet cardboard), is scraped off the drum screens into the outlet vat (repulper) o f the washer. The brown stock slurry surface area at the inlet vat is 15.3 m based on a width o f 1.3 m and 2  a length o f 11.8 m. The rotating washer drum is 4.7 m diameter by 11.5 m long with 85 m o f 2  exposed brown stock area. The brown stock surface area at the outlet vat is 14.2 m based on a 2  width o f 1.2 m and a length o f 11.8 m. The inlet vat makes up only about 13% of the total exposed  143  Chapter 6: Results and Discussion  surface area, whereas the washer drum and outlet vat make up about 87%. The 0 filtrate is sprayed through the vapour space in the washer hood, and onto the surface 2  of the brown stock mat on the washer drum. The liquor in the feed stock that is pulled out o f the inlet vat and onto the surface of the drum is almost immediately displaced with 0 filtrate. Because 2  0  2  filtrate is sprayed through the vapour space and is in contact with the vapour for a large fraction  of the exposed liquid surface, it is expected to have the greatest impact on the vapour concentration. Based on this, the wash liquid was used as the liquid phase for modelling phase equilibrium.  6.4.2  T i m e to E q u i l i b r i u m for D M S i n B l a c k L i q u o r  Process equipment in a mill may have limited liquid phase residence times, as low as a few minutes in some cases (Table 6.23). To determine i f typical residence times are sufficient time for equilibrium to be established, lab testing was conducted to determine the time required for D M S in black liquor to come to equilibrium with its vapour headspace. The equilibrium tests were done using black liquor samples collected September 22, 2006. Vapour to liquid volume ratios and intensity of mixing were varied to determine their effects. Some of these tests were replicated using both 1 stage diffusion washer filtrate and decker washer filtrate to determine i f the total dissolved st  solids concentration in the liquor was a factor. The operating temperature o f the brown stock washing process varies little during normal operation, typically only within a few degrees o f 80°C, so all testing was done at this temperature. Two vapour-liquid volume ratios and two agitation levels were tested.  The first vapour-liquid  volume ratio o f 5 m L liquid in a 24 m L vial (ratio o f 3.8) roughly represents typical blow tank conditions. The second vapour-liquid volume ratio o f 20 m L liquid in a 24 m L vial (ratio o f 0.2) roughly represents typical filtrate tank conditions. The agitation levels were simulated by using a tumbler, slowly rotating at about 15 rpm to provide "light" agitation, while a variable speed shaker was used to provide a "vigorous" level o f mixing. It is difficult to quantify the level o f agitation in equipment, but the blow tank would likely be on the light end, while the filtrate tanks would be somewhere between light and vigorous. For all tests, a liquor sample was preheated to 80°C and injected into a preheated 24 m L vial, with the vial placed in the agitator located in the oven. A headspace sample was withdrawn and 144  Chapter 6: Results and Discussion  injected into the G C about every 3 minutes (the time required to complete a G C run). Theoretically equilibrium is never reached; instead, the practical equilibrium concentration is reached when the change in concentration over time can no longer be detected with the available measuring device. For this test, practical equilibrium was judged to have been reached when there was less than 5% change (at which point the change became indistinguishable from G C signal noise) in three consecutive injections. The D M S headspace concentration data for each run have been normalized to the largest value for each run, with the results shown in Figure 6.23.  1.00  O CD CD  o  0.90 ^  I 0.80  - • - D e c k e r , Vigorous, 5 ml - * - Decker, Light, 5 ml -AT- Diffusion, Light, 5 ml - • - Decker, Vigorous, 20 ml - * - Diffusion, Vigorous, 20 ml -a-Diffusion, Light, 20 ml  8 g ro  t  £ o 0.70  TD CD CD  X  - S  0.60  C/)  Q  0.50 0  2  4  6  8 10 12 14 Time (minutes)  16  18  20  22  Figure 6.23: Time required for D M S phase equilibrium to be established in a black liquor sample held at 80°C  Equilibrium was established more rapidly as the vapour-liquid volume ratio and the level o f agitation increased. There was no discernable difference in time-to-equilibrium between the decker filtrate and the diffusion filtrate. For all liquor samples, equilibrium was established in less than 10 minutes for the 5 m L sample at vigorous agitation, while 10 to 15 minutes were required for the 5 m L at light agitation and the 20 m L at vigorous agitation, and just over 15 minutes for the 20 m L sample at light agitation. Based on the laboratory results, for the blow tank with a high vapour-liquid volume ratio and a low level of agitation, equilibrium should be established in 15 minutes or less, and with 83 minutes 145  Chapter 6: Results and Discussion liquid phase residence time (Table 6.23), there should be more than adequate time. For the filtrate tanks, with a low vapour-liquid volume ratio and a higher level o f agitation, equilibrium should also be established in under 15 minutes. With liquid phase residence times ranging between 4.5 and 8.1 minutes (Table 6.23), there is insufficient time for equilibrium to be established. Referring to Figure 6.22, the measured vent vapour concentration for the filtrate tanks would be expected to be in the range o f 80 to 95% o f the theoretical equilibrium value.  6.5  M o d e l l i n g of H o w e Sound E q u i p m e n t  The V L E model, based on the e N R T L parameters determined in Section 6.3, was applied to the mill sampling and testing data presented in Tables 6.11 to 6.22. Similar to the analysis o f methanol data from literature sources described in Section 6.1, the mill testing data were analysed to determine i f process conditions in the equipment were at or near vapour-liquid equilibrium. If the liquid and vapour were in equilibrium, with D M S defined as i , then the vapour mole fraction, y  j5  could be predicted from the liquid mole fraction, x using Equation (3.7): j5  v.P^x.P,  5 3  '  (3.7)  The total pressure o f the system, P, was atmospheric for the equipment tested. The D M S vapour pressure, P , was determined for the equipment operating temperature using the extended Antoine sat  Equation (3.21) using the parameters in Table 3.9. The activity coefficient for D M S in black liquor was determined using the e N R T L Equation (3.11) using the parameters determined from phase equilibria testing given in Tables 6.6 and 6.8.  146  Chapter 6: Results and Discussion 6.5.1  M o d e l Sensitivity Analysis  A sensitivity analysis was performed to see how the model output changed with the input parameters. The input parameters were varied over their range o f uncertainty and the change in the model response was calculated. Uncertainty may be introduced by possible errors in measurement (instrument sensitivity or measuring technique), absence o f information, or poor or partial understanding o f the driving forces and mechanisms. The model output, i.e., the predicted D M S vapour phase concentration, y was calculated j5  using Equation (3.7) from the measured variables: D M S concentration, x and pressure, P. The i5  model output is also dependent on two other variables, temperature, T, and sodium concentration, x , with temperature used to calculate D M S vapour pressure, Pj , and both used to calculate the Sal  ca  activity coefficient, YJ- For temperature, the process was operating near 80°C, with field transmitters providing readings typically within a degree o f the measured temperature. To be conservative, the sensitivity range for temperature was set at 353 ± 2 K , i.e., ± 0.6%. For pressure, the process was operating near atmospheric pressure with the D N C G system drawing a slight vacuum. The vacuum at the sources could not exceed the setting of the vacuum breakers installed to protect the tanks, with these set at 0.5 kPag. The sensitivity range for pressure was set at 101.3 ± 1 kPa, i.e., ± 1%. For determination o f D M S concentration, x confidence must take into account  i5  for the black liquor samples collected, the range o f  sample degradation  issues (see  Section 3.4), syringe  reproducibility (± 1% when using a Chaney adaptor), and calibration curve accuracy (Figure 5.6, R - 0.99).  2  The sensitivity range for this parameter was set at ± 5%. For the total dissolved solids level,  the moisture analyser provided by Howe Sound m i l l had an accuracy level of 0.1 wt% and the lowest measured value was 2.0 wt%, so the sensitivity range was set at ± 5%. The results of the sensitivity analysis are shown in Figure 6.24.  147  Chapter 6: Results and Discussion  g, 96% c  CD  O  94% 0.96  0.98  1  1.02  1.04  Parameter Multiplier Figure 6.24: Sensitivity analysis for prediction o f D M S vapour phase concentration  Temperature has the greatest effect, but the range o f uncertainty is small, introducing a potential error o f up to 5%. The liquid phase concentration has a linear effect; e.g., a 5% error w i l l result in a 5% error in the model prediction. It can be seen that confidence in the model results are in the range o f ± 5% based on all input variables, although these may be cumulative. A s discussed in Section 6.5.2, the error in the predicted values were greater than can be explained with the factors studied in the sensitivity analysis. To explain this, two other parameters were considered when modelling the Howe Sound equipment: insufficient liquid residence time for equilibrium to be established and dilution of the vent vapour stream with tramp air drawn in through openings in the equipment.  6.5.2  E q u i p m e n t M o d e l l i n g Results for D M S  Comparisons between measured and predicted D M S concentrations in the vent vapour stream were made for the decker washer filtrate tank, decker washer hood, blow tank and diffusion washer 148  Chapter 6: Results and Discussion  filtrate tanks. The diffusion washer N C G vent line was closed off, so no comparisons could be made for this source. For the testing days where the total dissolved solids were not measured, the average for that particular liquor sample point from all other testing days was used. In Figure 6.25, the measured D M S vent vapour concentrations from the decker washer filtrate tank are compared to the predicted equilibrium vent concentrations based on the  filtrate  concentration.  5000 Measured •  Predicted  > 4000 E Q. Q.  C > C  3000 2000  CO  Q  1000  C J ) C T ) C J > 0 } C J ) C J >  T  —  T  —  T  —  1  Date Measured F i g u r e 6.25: Measured versus predicted D M S concentrations for decker washer filtrate tank N C G vent  There appears to be a good response by the model to the changing concentration o f D M S in the liquid phase. The model fit for the decker washer filtrate tank and other equipment is quantified in Section 6.5.3. In Figure 6.26, the measured D M S vent vapour concentration from the diffusion washer filtrate tanks are compared to the predicted equilibrium vent concentrations based on the filtrate concentration in the 2  n d  stage tank, again with good results.  149  Chapter 6: Results and Discussion  20000  <J>  T -  T -  3>  ^  ^  ci  to  <M  «M  ^oi  °  ^  Date Measured  T -  ^  p«l  *~  o CO  o  F i g u r e 6.26: Measured versus predicted D M S concentrations for 2 stage diffusion washer N C G vent  n d  Comparison of measured data to predicted values for the blow tank vent was not straightforward. The diffusion washer is mounted on top of the blow tank and the brown stock from the washer drops down through a stock chute, into the blow tank. The brown stock, at a consistency of about 8% (clumps of wet fibre saturated with black liquor), drops from the stock chute, lands and settles on top o f the stock pile in the blow tank. The stock consistency is too high for it to act like a liquid, so the stock moves down the blow tank in a plug flow type motion until it is removed from the bottom o f the tank. The stock is diluted right at the bottom o f the blow tank with decker washer filtrate so that it can be pumped to the knotters and screens and onto the decker washer. The stock going to the blow tank was sampled as it dropped down the stock chute, but the stock in the blow tank itself could not be sampled because the stock is diluted ahead o f any potential sample point. The vapour from the blow tank would theoretically be in equilibrium with the stock from the blow tank, but since this was not sampled, the D M S concentration of the liquor in the stock had to be determined indirectly. The D M S concentration of the stock leaving the blow tank (prior to dilution) was determined from a mass balance calculation conducted around this tank. The D M S concentrations in the stock 150  Chapter 6: Results and Discussion  to the blow tank, and in the vapour from the blow tank, were measured and the mass flow o f each stream was calculated. From this, the mass flow o f D M S in the stock from the blow tank could be calculated along with its concentration.  In Figure 6.27, the measured D M S vent vapour  concentrations from the blow tank are compared to the predicted equilibrium vent concentration based on the calculated D M S concentration in the stock leaving the blow tank. The comparison is not favourable; the predicted values are about three times greater than the measured values (that were determined by the mass balance around the blow tank). A s discussed in Section 6.5.3, the measured values were thought to be low due to dilution from tramp air ingress.  Measured •  Predicted  > 4000 E Q. Q.  c CD  c 2000  CO  o CN  CM CM CM  CO CM  CM  CO  Date Measured F i g u r e 6.27: Measured versus predicted D M S concentration for blow tank N C G vent  In Figure 6.28, the measured D M S vapour concentrations in the vent from the decker washer hood are compared to the predicted equilibrium vent concentrations based on the inlet wash liquor ( 0 filtrate) D M S concentration. For the latter four sets o f data there appears to be a favourable 2  comparison; although it is unclear why the first two predict so poorly.  151  Chapter 6: Results and Discussion  300 250  s  E  a.  200  -4—*  |  150  w  1  Q  0  0  50 0  Date Measured  j  F i g u r e 6 . 2 8 : Measured versus predicted D M S concentration for decker washer hood N C G vent  6.5.3  Equipment Modelling Results for other T R S C o m p o u n d s  Hydrogen sulphide and methyl mercaptan were below detection limits for all liquor samples. Other than D M S , only D M D S was measured in high enough concentrations for modelling purposes. In Figure 6.29, the measured D M D S vent vapour concentrations from the decker washer filtrate tank are compared to the predicted equilibrium vent concentrations based on the filtrate concentration.  152  Chapter 6: Results and Discussion  1000 Measured • > E  Predicted  800  Q. Q.  ^  600  CD  > .£  400  CO Q  i  200  o <B  o  CM  o CM  CM CM CM  CO CM  CM  O  CO  o  Date Measured 6 . 2 9 : Measured versus predicted D M D S concentrations for decker washer filtrate tank N C G vent Figure  It was very difficult to avoid mixing o f air with the liquor sample when it was collected, because the liquor line was under high pressure and it sprayed from the sample valve. A s discussed in Section 3.4, significant oxidation o f the methyl mercaptide to D M D S occurs after only a few minutes (Reaction 2.9). D M D S concentrations are very low, ranging from 0.17 to 1.3 ppm in the liquor samples (Tables 6.11 to 6.22); whereas, the concentration o f the mercaptide is expected to be in the range of double that o f D M S (Figure 2.1 and 2.2), i.e., up to about 100 ppm (mol). Therefore, oxidation o f only a very minor fraction o f the mercaptide would have a large impact on the D M D S concentration. This oxidation effect is suspected of causing the over-prediction seen in Figure 6.29. A false high measured concentration o f the D M D S in the liquor w i l l lead to a false high D M D S prediction in the vapour phase.  Without this complication, the quality o f the prediction for the  decker washer filtrate tank for D M D S would be expected to be similar to that for D M S (Figure 6.25). If this effect was confirmed, it would provide further reason to choose D M S as a surrogate for modelling of T R S emissions.  153  Chapter 6: Results and  6.5.4  Discussion  E q u i p m e n t M o d e l l i n g Analysis  Quantification o f the accuracy o f the predicted vent vapour concentration for the Howe Sound equipment was done using the root mean square error ( R M S E ) . This is defined as the square root of the sum of the square of the error, where the error is the amount by which the predicted value differs from the measured quantity. The difference occurs because o f randomness or because the predicted value does not account for information that could produce a more accurate estimate.  Table 6.24: Root mean square error ( R M S E ) o f V L E model vent vapour concentration prediction Equipment  Decker Washer Filtrate Tank Diffusion Washer  Measured vapour  Predicted vapour  RMSE  concentration (ppm (mol))  concentration (ppm (mol))  (ppm (mol))  range  average  range  average  194 to  1611  247 to  1977  412  14651  3552  3215  2261  162  95  3789 8976 to  Filtrate Tanks  17336  B l o w Tank  692 to  4202 13707  15485 1031  1295 Decker Washer Hood  52 to  13473 to  2532 to 3946  110  204  67 to 272  For all equipment, the error appears to be a systematic over-prediction, rather than random error. The error is greater than what could be explained by the sensitivity analysis, i.e., there are unaccounted factors involved. These factors are suspected to be insufficient liquid phase residence time in the tank for equilibrium to be established, and/or dilution o f the vent vapour stream by tramp air entering the equipment through openings such as poorly sealed overflows. The filtrate tanks are sealed against tramp air ingress, so the error was likely introduced due to insufficient liquid phase residence time in the tank. For the decker washer filtrate tank, this is supported by the data in Figure 6.23, which predict that the vapour should be in the range o f 80 to 90% of the equilibrium value after 4.5 minutes; the average of the measured values was 82% o f the 154  Chapter 6: Results and Discussion  average o f the predicted values. The 2  nd  stage diffusion washer filtrate tank data are also supported by the data in Figure 6.23,  with this predicting that the vapour should be in the range of 85 to 95% of the equilibrium value after 6.8 minutes; the average o f the measured values for these tanks was 94% of the average o f the predicted values. There was more scatter in this data compared to the decker washer filtrate tank, which is likely attributable to the cyclical operation o f the diffusion washer, and venting o f the 1 stage filtrate tank via the 2  nd  st  stage tank.  The blow tank has more than sufficient time to reach equilibrium. The error was likely introduced by tramp air ingress through poorly sealed overflow openings. The averaged measured values were 32% of the average predicted value, indicating that almost 70% of the vent vapour flow from this tank was drawn in as tramp air. The tramp air is likely drawn into the tank and right back out v i a the D N C G system; therefore, it has insufficient contact with the stock in the tank for equilibrium to be established. For the decker washer hood, tests done on the latter four days have measured results which agree well with the predicted results (Figure 6.28), but it is unclear why there was an over-prediction for the first two testing days. It appears that random error is an issue, but is not clear with the limited data for this source i f there is a systematic error, such as tramp air ingress. To further analyse the data for systematic error, the D M S vapour phase predictions were adjusted by a set percentage of the predicted equilibrium value. This percentage was determined by minimizing the R M S E o f the corrected value. Table 6.25: V L E model correction factor for systematic error Equipment  Correction Factor for Systematic Error (%)  RMSE (ppm (mol))  Decker Washer Filtrate Tank  84  168  Diffusion Washer Filtrate Tanks  93  3408  B l o w Tank  31  300  Decker Washer Hood  61  66  155  Chapter 6: Results and Discussion The predicted values based on the V L E model and predicted values adjusted to account for systematic error, are compared to measured data on scatter plots in Figures 6.30 to 6.33.  Measured (ppmv) Figure 6.30: Comparison between decker washer filtrate tank measured D M S vapour concentration and predicted equilibrium value using the V L E model, and predicted value corrected for systematic error  156  Chapter 6: Results and Discussion  M e a s u r e d (ppmv) Figure 6.31: Comparison between diffusion washer filtrate tanks measured D M S vapour concentration and predicted equilibrium value using the V L E model, and predicted value corrected for systematic error  157  Chapter 6: Results and Discussion  M e a s u r e d (ppmv) Figure 6.32: Comparison between blow tank measured D M S vapour concentration and predicted equilibrium value using the V L E model, and predicted value corrected for systematic error  158  Chapter 6: Results and Discussion  300 250 > E 200 io  J  Q. T3  Q)  150  O  TJ  CD  100  CL  50  Q  Model Model (corrected)  0 50  100  150  200  250  300  Measured (ppmv) Figure 6.33: Comparison between decker washer hood measured D M S vapour concentration and predicted equilibrium value using the V L E model, and predicted value corrected for systematic error  For the decker washer filtrate tank and the blow tank, the scatter plots appear to confirm a systematic error, insufficient residence time for the former and tramp air ingress for the latter. For equipment with insufficient residence time, the V L E model could be extended to include gas-liquid mass transfer limitations, although more extensive testing would be required to fit such a model. For modelling o f the Howe Sound process using a V L E model, which is discussed in Section 6.7, a liquor by-pass technique was used to account for the lack o f residence time and a vapour by-pass technique was used to account for tramp air effects.  159  Chapter 6: Results and Discussion 6.6  M i l l T e s t i n g D a t a C o m p a r e d to E m i s s i o n F a c t o r s  Emission factors are provided by the U . S . E P A for estimating T R S emissions from chemical wood pulping facilities. The relevant factors are discussed in Section 3.3, with details provided in Table 3.10. T w o sets o f emission factors are provided, one for "digester relief and blow tank," and a second for a "brown stock washer." These factors were last updated in September 1990 and are based on an older process configuration consisting of batch digesters blowing directly to a blow tank, followed by a series o f vacuum drum washers used for brown stock washing. In this process, the first emission factor refers to the C N C G sources. The equivalent sources in the continuous digester process used at Howe Sound are the extraction liquor flash tanks, which were not tested as part o f this work. The second factor refers to the D N C G sources, which are equivalent to the sources tested in this work. The Howe Sound process consists of a continuous digester followed by a two stage diffusion washer, blow tank, knotters, screens, and decker washer. The blow tank in this position can not be considered equivalent to the blow tank referred to in the emissions factors provided for a batch m i l l . For this comparison, the blow tank has been included as part o f the D N C G brown stock washing emissions. To allow comparison to emission factors, the test data from Tables 6.11 to 6.22 were used to calculate the emissions of each T R S compound on a mass basis; this information is included in these tables. Emission factors are given for H S , and for the organic T R S compounds, i.e., for the sum o f 2  M M , D M S and D M D S . The emission factors for the brown stock washing process are 0.01 and 0.2 kg sulphur per air dry tonne pulp ( A D T P ) for H S and the organic T R S compounds, respectively. 2  Figures 6.34 and 6.35 compare the measured emissions and those determined using this emission factor. Only the testing days when all major sources were tested are shown, i.e., November 23, 24, 30 and December 1, 2005 (Tables 6.18 to 6.21).  160  Chapter 6: Results and Discussion  0.2  20 33  0.15  5 5  15  CO  "D  CD i_  0.1  10 % UL  CO  cc (D  E o  co 0.05  * %  CN  CN  X  X  CM  CO CM  O CO  CM  o  Date Measured Figure 6.34: Total measured H S emissions (left axis) compared to predicted emissions using emission factor (right axis) for brown stock washing process (kg o f sulphur per day) 2  The measured H S emissions are two to three orders of magnitude lower than those expected 2  based on emission factors (Figure 6.34). The undissociated H S concentration in the liquor, the 2  fraction that contributes to vapour pressure and thus to emissions, is strongly dependent on p H . The undissociated fraction is typically below detection limits above a p H o f 9 (Figure 3.2). The lowest measured p H during the Howe Sound testing was 11.4; therefore, the expectation agrees with the result, i.e., the H S in the vapour phase was negligible. To keep dissolved alkali lignin from 2  precipitating, the brown stock process must be operated at p H higher than 11; thus, it is questionable i f an H S emission factor for this process is necessary. 2  161  Chapter 6: Results and Discussion  500 5  to  Measured G E m i s s i o n Factor  CO  400  L_  o o  CO 300 u_ Eo v 200 H—  CO  100 0 CO CM  or CO CO  o  CM  CO  Date Measured F i g u r e 6 . 3 5 : Total measured organic T R S ( M M , D M S and D M D S ) emissions (left axis) compared to predicted emissions using emissions factor (right axis) for brown stock washing process (kg o f sulphur per day)  The organic T R S emission factor provides a better estimate o f emissions, with measured values ranging from 215 to 383 kg/day as sulphur (average 291) with an average R M S E o f 84 for the predicted values. A n emission factor is not given for D M S alone, so a direct comparison to the D M S m i l l data is not possible. Summing the total organic T R S emissions from all brown stock washing sources, 90.7% of the sulphur emissions originated from D M S . For comparison purposes, the emission factor was adjusted by this amount; i.e, the brown stock washing D M S emission factor used was 0.2 * 0.907 = 0.181 kg sulphur per A D T P . It is difficult to directly compare how well these emission factors predict D M S emissions when compared to a V L E model. A n emission factor is given for the entire brown stock washing line, not for each piece o f washing equipment.  To allow comparison, the emission factor was  divided among each o f the washing equipment process elements. For Howe Sound, the potential major emitters include the diffusion washer filtrate tank, diffusion washer, blow tank, screen feed 162  Chapter 6: Results and Discussion  tank, screen dilution tank, decker washer filtrate tank and decker washer hood. Of these, the diffusion washer was valved off and the screen feed and dilution tanks were found to have negligible emissions. The DMS emission factor was divided up between the rest of the sources based on the fraction of measure emissions from each source. For example, based on measured data from all testing days, 23.9% of the D M S emissions originated from the decker washer filtrate tank. The prorated DMS emissions factors for each source are listed in Table 6.26.  Table 6.26: Brown stock washing DMS emission factors Sample Point  Process Element  % of total D M S (avg.)  DMS Emission Factor kg S / ADTP  VS1  Diffusion Washer Filtrate Tanks  29.6  0.054  VS2  Diffusion Washer (valve closed)  negligible  -  VS3  Blow Tank  34.2  0.062  VS4  Screen Feed Tank  negligible  -  VS5  Screen Dilution Tank  negligible  -  VS6  Decker Washer Filtrate Tank  23.9  0.043  VS7  Decker Washer Hood  12.3  0.022  Brown Stock Washing Area (total)  100  0.181  For the decker washer filtrate tank, Figure 6.36 show a comparison between DMS emissions based on measured data, predicted emissions based on V L E correlations and a prorated emission factor.  163  Chapter 6: Results and Discussion 150  M e a s u r e d D Predicted 5  oo  n  E m i s s i o n Factor  100  CD  GO  50  T - T - C N J C N C N I C M f N C ^ t ^ f O o  Date Measured Figure 6.36: Decker filtrate tank emissions based on measured data and predicted using V L E correlations and emission factors  Figure 6.36 illustrates the advantage of the V L E model over emission factors for predicting emissions o f volatile contaminants. The measured values range from 4.9 to 114 kg/day as sulphur (average 42.6) with a R M S E o f 10 kg/day for the predicted values using V L E and a R M S E o f 31 kg/day for the predicted values using the emission factor. A n emission factor is independent o f D M S concentration in the process. It is based solely on production levels, thus it w i l l tend to over-predict when the D M S concentration in the process is low, and under-predict when the D M S concentration is high. This is illustrated in Figure 6.37, a scatter plot o f predicted values based on V L E and on a prorated emission factor.  164  Chapter 6: Results and Discussion  or  0  •  20  40  60  i  80  '  i  .  i  100 120  M e a s u r e d (kg/day sulphur) F i g u r e 6.37: Comparison between decker washer filtrate tank measured D M S vapour concentration and predicted equilibrium value using the V L E model, and predicted value using emission factor  Emission factors may provide a good averaged emissions estimate over time, but being independent o f D M S concentrations, they can not be used for modelling changes to the process.  6.7  H o w e Sound M i l l M o d e l l i n g  The final section o f this work provides an example on how this modelling technique can be applied to an industrial situation. According to Gerry Pageau o f Howe Sound, high S 0 emissions 2  from the power boiler have been an ongoing concern at the m i l l . The mill has a D N C G system and the collected gases are incinerated in the power boiler. These gases were suspected to be the main contributor o f sulphur to the combustion process that results in the S 0 emissions. Some means o f 2  reducing the sulphur loading in the D N C G would contribute towards meeting power boiler S 0 165  2  Chapter 6: Results and Discussion  emissions requirements. One o f reasons that Howe Sound agreed to assist in this research was that they were hoping to gain some insight into where the sulphur in the D N C G originated and possibly find solutions on how to reduce the sulphur loading to the power boiler. Based on mill testing data from the days when all major D N C G sources were tested (Tables 6.18 to 6.22), the average sum o f the sulphur loading from all D N C G sources was 512 kg/day. The brown stock washing area and the digester chip bin were suspected to be the main contributors to sulphur in the D N C G . The brown stock area average sulphur loading was 291 kg/day. These sources include about 57% o f the total sulphur loading in about 82% o f the total D N C G flow. The chip bin average sulphur loading was 204 kg/day. This source includes about 40% o f the total sulphur loading in about 13% of the total D N C G flow. The recovery area, which includes the heavy black liquor ( H B L ) , weak black liquor ( W B L ) and contaminated condensate tanks was confirmed as a low sulphur contributor at 17 kg/day. This tankage includes about 3% o f the total sulphur loading in about 5% of the total D N C G flow. The combined D N C G flow to the boiler was also tested yielding a total sulphur loading o f 566 kg/day. Considering the variability in the process and the potential errors in measurement, there is reasonably good agreement, within 10%, between the total sulphur loading based on summing o f the sources and the total loading measured in the combined D N C G . Contaminated steam from the extraction liquor flash tanks is used for pre-steaming in the chip bin, and when there is a low chip bin level, this T R S laden steam breaks through the chip pile and is collected by the D N C G system. The sulphur loading in the D N C G from the chip bin is highly variable due to the sporadic nature of this contaminated steam break-through. The frequency o f the steam break-through can be minimized by controlling the chip pile at a higher level in the chip bin. Other means can be used to reduce the sulphur loading from this source, including switching to clean steam (although at an increased operating cost), or switching to clean steam when the bin level is low. Because brown stock washing is the largest sulphur contributor to the D N C G , sampling and testing, and subsequent modelling, was focussed on this area. Where changes to the process are being considered or improvements are desired, it may be desirable to "bench-mark" the existing operation. A base-case heat and mass balance model can be constructed which reflects current 166  Chapter 6: Results and Discussion operation. Once calibrated using the mill testing and operating data, the base-case model can be modified to evaluate process changes and their effect on D M S emissions.  6.7.1  Base-Case Balance of the H o w e S o u n d Process  A base-case heat and mass balance was constructed for the Howe Sound brown stock washing system, using C A D S i m Plus. To account for vapour phase non-idealities, such as tramp air entering the system through the poorly sealed overflows on the blow tank, a modelling technique was incorporated where a percentage o f the vapour flow was by-passed around the V L E module. This by-pass was used to simulate tramp air that is drawn into the tank and promptly out through the vent stack, with essentially no contact with the brown stock. Where there was suspected to be insufficient liquid phase residence time to establish equilibrium, a percentage of the liquid flow was by-passed around the V L E module. The base-case balance was based on m i l l testing data averaged from the days when all major brown stock washing area sources were tested (Tables 6.18 to 6.21). This was the same subset o f testing days that were used to do the emission factor comparisons in the previous section. These days were chosen because the mill was operating at full capacity, the process was stable, a full set of samples was collected and there was generally the highest confidence in the experimental data collected (the mill sampling and testing technique had been refined over the previous testing days). The vapour and liquid sample test results are shown in Tables 6.27 and 6.28, respectively.  167  Chapter 6: Results and Discussion T a b l e 6.27: Vapour sample testing data for November 23, 24, 30, and December 1, 2005 Location VS1  Parameter  Units  Average  Range  Diffusion  Flow  m /min  3.1  2.7 to 3.2  Washer  Temperature  °C  64  63 to 65  Filtrate  Relative Humidity  %  100  100 to 100  D M S Concentration  ppm (mol)  12075  8976 to 16299  D M S flow  kg /day as S  61.1  48.0 to 73.1  Flow  m /min  55.7  54.5 to 56.9  Temperature  °C  71  70 to 72  Relative Humidity  %  99  96 to 100  D M S Concentration  ppm (mol)  1051  692 to 1295  D M S flow  kg /day as S  95.6  64.5 to 120.1  Decker  Flow  nrVmin  15.3  11.7 to 18.4  Washer  Temperature  °C  74.5  72 to 77  Filtrate Tank  Relative Humidity  %  100  100 to 100  D M S Concentration  ppm (mol)  2523  1590 to 3789  D M S flow  kg /day as S  66.2  30.0 to 113.9  Decker  Flow  nrVmin  186.6  186.6 to 186.6  Washer  Temperature  °C  64.3  63 to 65  Hood  Relative Humidity  %  97  91 to 100  D M S Concentration  ppm (mol)  135.5  56.8 to 204  D M S flow  kg /day as S  42.1  17.7 to 63.4  Tanks  VS3  VS6  VS7  B l o w Tank  3  3  168  Chapter 6: Results and Discussion  Table 6.28: Liquid sample testing data for November 23, 24, 30, and December 1, 2005 Location LSI  LS2  Parameter  Units  Average  Range  Stock from  pH  -  11.7  11.6 to 11.7  Digester  Temperature  °C  80.8  80 to 82  Total Dissolved Solids  %  13.6  13.4 to 13.8  D M S Concentration  ppm (mol)  50.3  1/12/07 only  1 Stage  pH  -  11.6  11.6 to 11.6  Diffusion  Temperature  °C  79.5  79 to 80  Washer  Total Dissolved Solids  %  11.8  10.8 to 12.7  D M S Concentration  ppm (mol)  37.4  31.3 to 43.5  pH  -  11.6  11.4 to 11.6  Diffusion  Temperature  °C  78.5  78 to 79  Washer  Total Dissolved Solids  %  9.3  8.9 to 9.8  D M S Concentration  ppm (mol)  21.9  19.7 to 23.5  Diffusion  pH  -  11.6  11.5 to 11.7  Washer  Temperature  °C  77.5  77 to 78  Stock out  Total Dissolved Solids  %  8.5  8.5 to 8.6  D M S Concentration  ppm (mol)  7.82  7.2 to 8.9  Stock to  pH  -  11.6  11.4 to 11.7  Decker  Temperature  °C  75.3  74 to 76  Washer  Total Dissolved Solids  %  7.3  7.0 to 7.6  D M S Concentration  ppm (mol)  5.39  4.64 to 6.97  st  Filtrate LS3  2  nd  Stage  Filtrate LS4  LS5  169  Chapter 6: Results and Discussion  T a b l e 6.28 (cont.): Liquid sample testing data for November 23, 24, 30, and December 1, 2005 Location LS6  LS7  LS8  Parameter  Units  Average  Range  Decker  pH  -  11.6  11.4 to 11.7  Washer  Temperature  °C  75.3  74 to 76  Filtrate  Total Dissolved Solids  %  6.8  6.7 to 6.9  D M S Concentration  ppm (mol)  5.48  4.09 to 7.88  Stock from  pH  -  11.6  11.4 to 11.7  Decker  Temperature  °C  75.3  74 to 76  Washer  Total Dissolved Solids  %  4.8  4.5 to 5.1  D M S Concentration  ppm (mol)  0.57  0.43 to 0.82  pH  -  11.6  11.4 to 11.7  Temperature  °C  80.0  79 to 81  Total Dissolved Solids  %  4.3  4.1 to 4.5  D M S Concentration  ppm (mol)  0.25  0.13 to 0.39  0 Filtrate 2  Relevant operating data for the base-case balance was extracted from the m i l l M O P S historian data (Appendix G). Operating data for the four days were averaged, with the results shown in Table 6.29.  170  Chapter 6: Results and Discussion  Table 6.29: M O P S historian data for November 2 3 , 2 4 , 3 0 , and December  1, 2 0 0 5  Location  Parameter  Units  Average  Digester  Flow  bone dry  2673  Chip feed  Range 2 5 1 8 to  2902  tonne/day  Stock from  Y i e l d (on bone dry wood)  %  43  digester  Flow (stock only)  bone dry  1150  1083  to 1 2 4 8  tonne/day Flow (total)  L/s  127  120  Temperature  °C  80.6  79.6  Consistency  %  9.63  9.2  to  9.8  1 stage  Filtrate flow to  L/s  163  148  to  170  diffusion  Filtrate flow from  L/s  153  132  to  161  washer  Tank level  %  75  74  to  77  Filtrate flow to  L/s  131  121  to  142  diffusion  Filtrate flow from  L/s  128  115  to  138  washer  Tank level  %  102  101  to  102  B l o w tank  Tank level  %  24  18  to  35  Knotters  Feed consistency  %  4.1  3.8  to  4.4  Screens  Feed consistency  %  1.85  1.67  to  1.98  Decker  Product flow  L/s  131  123  to  143  washer  Product consistency (after  %  9.1  8.8  to  9.3  Feed wash liquor flow  L/s  121  101  to  142  Feed wash liquor temperature  °C  79.7  79.4  Tank level  %  70  Filtrate temperature  °c  75.6  st  2  n d  stage  to  137  to 8 2 . 1  dilution in repulper)  171  69  to 8 0 . 0 to  70  74.4 to 7 6 . 4  Chapter 6: Results and Discussion  The base-case heat and mass balance for the brown stock washing system was set up based on the fibre, water and total dissolved solids ( T D S ) flow measurements. The data used included flow, temperature and consistency readings from the M O P S data, vent vapour flows from mill testing and total dissolved solids measurements from collected samples. The variables used to model washer performance were the displacement ratio ( D R ) and washed pulp consistency, both o f which are related to the dilution factor (DF). The washed pulp consistency from the diffusion washer is not measured, but recent manual lab tests conducted by the mill showed the consistency was averaging about 8%. This is lower than expected and indicates the diffusion washer was operating at lower than expected efficiencies. This was confirmed when an attempt was made to fit the total dissolved solids data to the base-case model; the diffusion washer displacement ratio that best fit the data was 62%. A n atmospheric diffusion washer would normally be expected to operate at a displacement ratio of about 80%. A study was recently completed on decker washer performance by a consultant hired by the m i l l . They found that the decker washer was operating at an average displacement ratio o f 75%, which is typical for a vacuum drum washer. The feed and washed stock consistencies were not measured, but this information, based on manual lab tests, was included in the consultant's report. The average feed stock consistency was 1.26%, and the average washed stock consistency was 12.3%; these values are fairly typical for a vacuum drum washer. "Tramp water", also called "cheater flow", was added to balance the inlet and outlet water of the system. This tramp water enters the system at various locations such as water hoses, foam showers or leaking glands on seal water for pumps. For simplicity, the tramp water was added as one stream to the decker washer filtrate tank. The base-case balance is shown in Figure 6.38; the data was extracted from the C A D S i m model.  172  4.0|3.1176.5  0|0|0  77|55.7|76.5  0|0|0 0|0|0  19|15.3|75.3 241|186.6|68.6  « L  DIFFUSER FILTRATE  cn  10448|121|4.3|0|79.7  0  2  CO  o ro o  2nd STAGE DIFFUSION WASHER FILTRATE TANK DIFFUSION WASHER FILTRATE A  1st STAGE DIFFUSION WASHER FILTRATE TANK  —J  to cn  9212|109|5.0|12.3|78.5 REJECTS  14184|157|10.7|0|78.4  STOCK TO 0 DELIGNIFICATION 2  DECKER WASHER  SCREENS KNOTTERS  130|7.2|8.4|76  ro CO  ro  STOCK FROM DIGESTER  oo on  120021126113.619.6180.6 cn  DECKER WASHER FILTRATE TANK  TRAMP WATER  1200|14|0|0|20  Vapour flows: t/d|m /min|°C 3  Liquid flows: t/d|l/s|%TDS|%Co|°C  Os  ?0  a s a.  «  Co  F i g u r e 6.38: Base-case heat and mass balance for the brown stock washing area of the Howe Sound mill  Co  S' 3  Chapter 6: Results and Discussion After the base-case balance had been adjusted to best fit the fibre, water and T D S data, a V L E module was added at all o f the potential vent points. D M S was added to the mass balance and the base-case balance was adjusted using the vapour and liquid by-passes to best match the measurements from the samples collected. A n example of the by-pass technique, for the blow tank, is shown in Figure 6.39.  NCG VENT 54.5 m3/min 72.2 °C 1095 ppmv DMS TRAMP AIR 34.8 m3/min 10.0 C  12.9 m3/min  n  VAP 101.3 kPag  DIFFUSION STOCK PRODUCT LIQ  156 l/s 78.0 "C 7.90 ppmv DMS  156 l / s 77.5 °C 3.52 ppmv DMS STOCK TO KNOTTERS  F i g u r e 6.39: Detailed view o f a blow tank C A D S i m V L E module heat and mass balance  A s discussed in Section 5.3.6, there was less confidence in the measurements for D M S concentrations in the black liquor samples squeezed from stock (LS1, LS4, and LS7). The measured concentrations o f these samples were thought to be low due to the sample collection method used. This was particularly true for the stock from the digester ( L S I ) , where there were added difficulties collecting a sample from a line under high pressure. This appears to be confirmed in the base-case balance where a good fit was achieved with simulation values for L S I , L S 4 and L S 7 consistently higher than the measured values. A n overview of the D M S results for the base-case balance taken from Figure 6.38 is shown in Figure 6.40, with the D M S balance shown in kg/day (as sulphur).  174  Chapter 6: Results and Discussion  o  2  DIFFUSER FILTRATE  DECKER WASHER FILTRATE TANK  Base-case D M S mass balance for the brown stock washing system o f the Howe Sound mill ( D M S in kg/day as sulphur)  F i g u r e 6.40:  For the base-case operating conditions, a large fraction o f the D M S was washed from the • digester brown stock in the diffusion washer, with 75% o f the D M S exiting the system with the diffusion washer filtrate. Only about 2% of the D M S passed through to the 0 delignification system 2  with the washed stock. 23% of the total D M S entering the brown stock washing system was flashed off with the vent gases and collected in the D N C G system.  6.7.2  Predicted Effect on D M S Emissions f r o m Process  Changes  Various operational and equipment changes to the brown stock washing process were investigated to determine their effect on overall D M S emissions. The base-case model was modified to simulate these changes and to predict their effect on D M S emissions. The changes investigated are given in Table 6.30 with descriptions and analysis following.  175  Chapter 6: Results and Discussion T a b l e 6.30: Predicted effect on Howe Sound brown stock washing D M S emissions as a result o f operational or equipment changes Changes made to base-case heat and  D M S emissions (kg/day as sulphur) Diffusion Filtrate Tanks  Blow Tank  Decker Washer Hood  Decker Washer Filtrate Tank  Total  Change from . base-case (%)  mass balance  Base-case  61  96  42  66  265  0%  Worst-case (by-passes set to zero)  52  227  13  24  316  19%  Emission factor  69  79  29  55  232  -12%  Decrease temperature o f stock from digester by 10°C  56  85  45  68  254  -4.2%  Decrease temperature o f decker wash water ( 0 filtrate) by 10°C  58  87  45  66  256  -3.4%  Reduce D N C G flow from blow tank by 50% (seal over-flow openings)  63  57  51  79  250  -5.7%  Reduce D M S in stock from digester by 10%  55  86  38  60  239  -10%  Increase diffusion washer displacement ratio from 62% to 75%  62  52  27  40  181  -33%  Increase decker washer displacement ratio from 75% to 80%  61  96  43  67  267  0.7%  Increase diffusion washer washed stock consistency from 8% to 10%  68  88  34  52  242  -8.7%  Increase decker washer washed stock consistency from 12.3% to 14%  55  87  39  60  241  -9.1%  Sparge diffusion washer filtrate tank D N C G in decker washer filtrate tank  0  101  48  106  255  -3.7%  Increase temperature o f stock from digester to 105°C (hot blow)  72  129  36  61  298  12%  Stock by-pass o f diffusion washer to blow tank on hot blow o f 105"C  11  989  24  52  1076  306%  2  176  Chapter 6: Results and Discussion  For process modelling, when designing a new mill or for emissions reporting, it may be desirable to ignore the residence time and tramp air effects so that the model reflects a "worst-case" scenario for total emissions. If the V L E model is used without accounting for these effects, it w i l l over-predict D M S concentrations in the vent vapour. The worst-case scenario was determined by setting all V L E module by-passes to zero.  This balance may be preferable for design or  environmental reporting purposes since D M S emissions are over-predicted by about 20%, therefore providing a contingency factor. The base-case model was also compared to estimated emissions based on an emission factor (Table 6.26), with the factor predicting low by 12%. Two trials were conducted to determine temperature effects on overall D M S emissions from the brown stock washing area. The temperatures of the two inlet streams that could be manipulated in a brown stock washing process, the stock from the digester and the wash water ( 0 filtrate) were 2  each reduced by 10°C. For both trials, the change in D M S emissions was relatively insignificant with about a 4% reduction. There are other consequences o f reducing these temperatures, such as reduced washing efficiencies, but since this process change does not appear to be promising for reducing D M S emissions, discussion o f possible side-effects are not necessary. A relatively high D N C G flow was noted from the blow tank, with a large fraction likely entering through poorly sealed over-flow openings. A trial was conducted to determine the effect of better sealing these overflow openings. It is assumed that tramp air ingress could be reduced by an amount that would be sufficient to reduce the D N C G flow from the blow tank by half. With a 50% decrease in the volume of D N C G from the blow tank, the amount o f D M S in the vent gas from the blow tank was reduced by about 40%, from 96 to 57 kg/day. Even though the blow tank emissions were reduced by 39 kg/day, total emissions from the brown stock washing system were reduced by only 15 kg/day. A cursory look at the situation may lead one to conclude that halving the vent gas flow out the blow tank would lead to a reduction in D M S sulphur emissions o f 48 kg/day (half o f the basecase total from the blow tank), or 18% overall. According to the model, a reduction in D M S emissions from upstream process equipment w i l l increase the D M S concentration in stock and liquor flowing to downstream equipment, increasing emissions from this equipment, and the overall emissions reduction would be only 15 kg/day, or 5.7% overall. A trial was then conducted to determine the effects o f reducing D M S loading to the brown 177  Chapter 6: Results and Discussion  stock washing system.  O n a practical level, this could be accomplished in a number o f ways  including a reduction in sulphidity of the cooking process, which would in turn reduce the formation of D M S in the digester (Figure 2.2). A s discussed in Section 2.2.2, D M S is formed from a reaction between a mercaptide ion with a lignin methoxyl group. For this reaction to proceed, the mercaptide ion must first be formed from a reaction between the hydrosulphide ion and a lignin methoxyl group. Sulphidity is a measure related to the initial concentration o f the hydrosulphide ion in the white liquor. Determining the extent that these reactions proceed in the digester is difficult, with the complexity increased by the practice o f recycling black liquor back to the digester, such as at Howe Sound which uses the "Lo-Solids" cooking process. For this trial, the D M S concentration in the stock from the digester was reduced by 10% to determine the magnitude o f the effect on the brown stock washing process. The effect was found to be linear; i.e., a 10% reduction in D M S in the stock from the digester w i l l result in a 10% reduction in emissions (although T R S emissions from other parts o f the mill would likely also be reduced with a reduction in sulphidity). There would be other potentially significant consequences o f sulphidity reduction; therefore, reducing sulphidity for possibly only modest environmental gains would likely not be considered. Another possible way to reduce D M S loading to the brown stock washing process is to optimize the washing efficiency in the digester washing zone prior to this stock being released to the brown stock washing process. The D M S is washed from the liquor along with the dissolved lignin and excess cooking chemicals. A n increase in washing efficiency w i l l decrease the D M S in the stock from the digester.  This same principal holds true for stock processing within the brown stock  washing system; i f the efficiency o f the diffusion washer could be increased, more D M S would be captured into the filtrate and less would be carried through to downstream process equipment. According to the base-case balance, the Howe Sound diffusion washer was not operating as efficiently as would typically be expected.  The reasons for this are not fully understood; the  equipment supplier should be consulted for advice on how to optimize operation. Because there appears to be room for improved operation, trials were conducted to determine the effect on D M S emissions i f some operating parameters o f the washers could be improved. A trail was conducted by increasing the displacement ratio o f the two stages o f diffusion washing from 62% to 75%. The overall D M S emissions from brown stock washing were reduced by 33% with this change. A s expected, the emissions from the diffusion washer filtrate tanks were 178  Chapter 6: Results and Discussion  slightly higher because the filtrate D M S concentrations were higher, but this increase was more than offset by a decrease in emissions in downstream equipment. A similar trial, increasing the displacement ratio, was then done for the decker washer. Even though the decker washer appeared to be operating at a reasonable efficiency, a trial was conducted to determine the magnitude o f the effect that could be expected i f there was a change. When the decker washer displacement ratio was increased from 75% to 80%, the overall D M S emissions actually increased. Increasing the washer efficiency w i l l reduce the D M S in the washed stock going to 0  2  delignification system, but at the expense o f an increased D M S concentration in the decker  washer filtrate, with the subsequent higher emissions in equipment processing this liquor. Washing efficiency is also related to washed stock consistency; i.e., a washer operating at a higher washed stock consistency w i l l contain less liquor (higher dilution factor); therefore, the washed stock w i l l contain less dissolved solids (and D M S ) .  A trial was conducted by increasing  the consistency o f the washed stock that exits the diffusion washer, from 8% consistency to a more typical value o f 10%. The overall D M S emissions from brown stock washing were reduced by 8.7% with this change. Similar to the trial where the displacement ratio was increased, the emissions from the diffusion washer filtrate tanks were higher, but again this increase was more than offset by a decrease in emissions in downstream equipment. When the washed stock consistency from the decker washer was increased from 12.3% to 14% (still a reasonable design target), the overall D M S emissions were decreased by 9.1%. In this case, the higher dilution factor from increasing the washed stock consistency results in a lower D M S concentration in the decker washer filtrate and a subsequent reduction in D M S emissions from other equipment using this liquor for processing. For emissions reduction, the final trial was to return D M S emissions back to the process. High D M S concentration D N C G from the diffusion washer filtrate tanks was "scrubbed" by sparging it into the decker washer filtrate tank. Based on phase equilibrium, the relatively low concentration decker filtrate w i l l absorb D M S from this gas.  This does occur, but the resulting higher D M S  concentration in the decker washer filtrate results in higher emissions not only from this tank, but from other process equipment as well, and the overall reduction in D M S emissions was only 3.8%. Two trial were conducted to determine the effect o f "hot blowing" on D M S emissions. This term refers to when the stock from the digester climbs above about 90°C. With an increase in stock 179  Chapter 6: Results and Discussion  temperature to 105°C, D M S emissions increase by only 12%. The stock from the digester first flows to the 1 stage o f the diffusion washer where it is washed (and cooled) by the washing liquor st  (although at this temperature there may be flashing inside the diffusion washer). This results in hotter liquor temperatures (increasing from 78°C for the base-case to 95°C) in the 1 stage diffusion st  washer filtrate tank, which results in the higher D M S emissions. During hot blowing, to avoid damaging the diffusion washer due to flashing, some mills w i l l temporarily by-pass the diffusion washer and blow the stock directly to the blow tank. If the stock from the digester goes directly to the blow tank at 105°C, emissions w i l l go up dramatically. The stock will flash in the blow tank from 105°C down to 101 °C (there is a boiling point rise o f about 1.1°C due to the dissolved solids), with approximately 0.8% o f the water fraction vaporizing, resulting in a vent vapour volumetric flow of 80 A m / m i n . This would likely overwhelm the D N C G 3  collection system, resulting in odorous vapour spilling out the poorly sealed overflow openings to atmosphere. Because D M S relative volatility compared to water is high, about 90% w i l l flash off into the vent vapour. This will quadruple overall D M S emissions from 265 to 1076 kg/day (as sulphur). It is upset situations such as this, often occurring during startup or shutdown situations, that result in many o f the odour complaints from the surrounding community.  6.73  R e d u c i n g B r o w n Stock W a s h i n g D M S Emissions  The brown stock washing process is a counter-current washing operation beginning with the wash water ( 0 filtrate) introduced at the decker washer and finishing with the diffusion washer 2  filtrate exiting the 1 stage diffusion washer. There is recycling of decker washer filtrate within the st  washing process, but only downstream o f the diffusion washer; decker washer filtrate is used for dilution o f stock in the bottom of the blow tank and ahead of the decker washer, and for de-knotting and screening. The recycling o f liquor results in the recycling o f D M S ; from the base-case model in Figure 6.40, it can be seen that the D M S loading in the decker filtrate is 828 kg/day, more than three times higher than that contained in the stock passing through the blow tank. Due to liquor recycling, any D M S in the washed stock leaving the diffusion washer will have multiple opportunities to be 180  Chapter 6: Results and Discussion  emitted; therefore, operational or equipment changes aimed at reducing D M S emissions should be focussed on the process upstream o f the blow tank. The most significant reductions in D M S emissions are based on achieving better washing, either in the digester washing zone or in the diffusion washer. For Howe Sound, there appears to be potential for improving the operation o f the diffusion washer. Increasing the efficiency o f this washer would have production benefits (such as reduced operating costs from lower consumption of bleaching chemicals) and it would have the beneficial side-effect o f reducing overall emissions from the washing process. More efficient operation of the diffusion washer w i l l result in the capture of more D M S (and other volatiles) into the washer filtrate, with this liquor processed in the evaporators, where the vent is collected to the C N C G system. For Howe Sound, this w i l l have the benefit o f shifting sulphur loading from the D N C G to the C N C G system. Unlike the D N C G which is fired in the power boiler, potentially causing S 0 emissions, C N C G is incinerated in the lime kiln. The lime kiln can generally 2  tolerate sulphur in the combustion process, with most of the S 0 absorbed into the lime mud forming 2  sodium and calcium sulphate. For other mills, capturing higher levels o f D M S and other volatiles into the washer filtrate may have an even more profound impact. Not only are C N C G systems much smaller, therefore cheaper to install and operate, but most mills already have these systems. For a mill without a D N C G system, emissions from the brown stock washing area to atmosphere could be reduced, and the necessity of collecting D N C G sources from downstream of a highly efficient first washing stage could be questioned. A s a first stage of an emissions reduction program, a mill could optimize their initial stages of brown stock washing. Then, since the N C G flow from the first washing stage filtrate tanks is low and the concentration is already relatively high, averaging 13,700 ppm (mol) at Howe Sound (Table 6.24), which is near the L E L o f 22,000 ppm (mol) (Table 2.2), this source could be added to their existing C N C G system.  /  If the m i l l is planning to install a D N C G system, some mill testing would be required to construct a base-case balance similar to the one presented here for the Howe Sound m i l l .  DNCG  systems collect up to 30 sources and can cost up to 10 million dollars to install, so elimination of just a few sources and reduction in the D N C G flow from other sources could result in a significant savings, not only in installation costs, but also in operating costs. 181  Chapter 6: Results and Discussion  6.8  T h e F u t u r e of N C G Collection Systems  Testing at Howe Sound showed that only about 2% of the D M S contained in the stock from the digester going to brown stock washing remained in the washed stock (Figure 6.40). Therefore, with efficient washing, collection of N C G vent sources after the brown stock washing process is not necessary. Testing at Howe Sound also showed that the N C G flow from sealed equipment, such as the filtrate tanks, was relatively low; whereas, flow from unsealed sources such as the blow tank and decker washer hood was relatively high (Table 6.27). The high flows from these sources was mainly due to tramp air ingress. Therefore, to minimize the volume o f N C G that requires collection and treatment, washing equipment should be sealed; and to further prevent tramp air ingress, all washing equipment could be operated pressurized. This equipment is commercially available, including pressure diffusion and drum washers and sealed screens and knotters. Historically low-volume high-concentration N C G sources have been collected into a separate dedicated concentrated N C G ( C N C G ) system with the theory being that the concentration o f combustibles in this gas would be above the upper explosive limit ( U E L in Table 2.2); i.e., there is insufficient oxygen available to sustain c