CFD Study of Important Flare Operating Parameters for

2014 TARC Meeting/SETRPC Air Quality Symposium By

Raj Alphones, Kader Rasel, Vijaya Damodara, Daniel Chen, Helen Lou, & Peyton Richmond Dan. F. Smith Dept. of Chemical Engineering Ajit Patki, Xianchang Li Mechanical Engineering Department Lamar University August 8, 2014

Contents I. II. III. IV. V.

Needs Objectives Methodology Yr 1 Results Proposed Yr 2 Work

Introduction/Needs

Issues with Industrial Flares – Operators have a tendency to over-steam or overair to suppress smoke at the expense of combustion efficiency (CE) or carbon conversion Efficiency (CCE) – Incipient smoke point (ISP), while widely recognized as a convenient indicator for good combustion, is neither well understood nor scientifically defined. – Many factors affect soot emission and unburned/ produced VOC emissions. This leads to a question of how to operate the flares in order to achieve the optimal environmental performance (min. smoke + min. VOCs)? (EPA/OAQPS, 2012; http://www11.tceq.state.tx.us/oce/eer/index.cfm)

Needs for Computational Fluid Dynamics (CFD) and Response Surface Flare Modeling • Flare field tests are expensive • Validated, rigorous CFD flare models are useful for parametric studies & flare optimization • Response surface models are even more convenient for parametric studies, performance analysis, and flare optimization

Objectives • Understand the relationship between flare performance and the operating parameters at or near the Incipient Smoke Point (ISP). • Develop validated rigorous or empirical modeling tools to study the above-mentioned relationship.

Methodology

Approach • Develop reaction mechanism with soot precursor species or utilize built-in soot models in Fluent in order to strike a balance in soot and VOC modeling

• Develop validated CFD tools that can be used to study important flare operating parameters and to fill the data gap – By simulating various flare test cases for which both soot and VOC data are available

• Develop easy-to–use response surface models based on available experimental data

Data Sources for Validation of CFD Modeling Laboratory Flames

CH4 Sandia/ TU Darmstadt Flame (2006) Methane/Air Flame (Raman-Rayleigh-LIF, UC Berkeley 2005) Ethylene flames (MBMS, Zhang 2006) Methane/Ethane/H2/CO flames [TNF, 2012]

http://www.sandia.gov/TNF/DataArch/delft3.html Image Source: 2010 TCEQ Flare Study Project, Final Report

 Controlled Flares    

UT/John Zink/ARI (TCEQ 2010 Flare Study) Marathon Data & 2006/2011-12 HRVOC Flares Survey Data Carleton U. (Soot Formation, 2012-2014) J.H. Pohl, Evaluation of the Efficiency of Industrial Flares, 1984/1985, EPA600-2-85-95 and 106  Propylene/Propane flare with Continuous Monitors/GC (EPA, 1983)

9

Combustion Mechanisms • Reduced mechanisms can save computing time and, in many instances, are required (e.g., using FLUENT EDC chemistryturbulence interaction model)

• Lamar research group has developed a series of 50-species reduced mechanisms for the combustion of C1-C3 light hydrocarbons (LU1.0, 1.1, and 2.0 based on GRI-3.0 and USC-I mechanisms ) • New mechanism LU 3.0.1 that contains soot precursor species and is suitable for the combustion of C1-C4 light hydrocarbons has been developed in the current project period based on the USC-II mechanism. • All mechanisms were validated with experimental results like laminar flame speeds, adiabatic flame temperature, ignition delay, and burner stabilized flame. "A reduced reaction mechanism for the simulation in ethylene flare combustion,“ Clean Technologies and Environmental Policy, June 16, 2011; ,"Validation of a Reduced Combustion Mechanism for Light Hydrocarbons," Clean Technologies and Environmental Policy, “ Clean Technologies and Environmental Policy, 14(1) 1-12, 2012. "Optimal Reduction of the C1-C3 Combustion Mechanism for the Simulation of Flaring, " Industrial & Engineering Chemistry Research, February 13, 2012.

Fluent Model Selection •

•

Realizable k- viscous (or turbulence) model • Turbulence intensity = 15% • Turbulence viscosity ratio = 10 Turbulence-chemistry interaction model • Probability Density Function (PDF) Model • Eddy dissipation concept model (EDC, Reduced 50-species mechanism required) Table 3: Comparison of EDC and PDF models EDC (Eddy Dissipation Concept) Reactions taking place in the flame are governed by the Arrhenius rates

PDF (Probability Density Function) Reactions are governed by a conserved scalar quantity known as mixture fraction

Incorporates detailed chemical mechanisms Fast reactions are assumed (Valid for (More accurate for VOC species) >1600 K).

Molar concentrations are derived from Reaction rates, which are calculated using ISAT algorithm

Molar concentrations are derived from the predicted mixture fraction fields

Any number of inlet streams can be defined

Only two inlet streams are allowed i.e. Fuel and Oxidizer

Computationally very expensive; requires 5-6 days for convergence

Requires less time for convergence; only 2-3 days

11

Validation of the CFD Simulations • The CFD methodology has been validated with the lab scale flames (Sandia Lab CH4/Air flame & McKenna C2H4/O2/Ar flat flame), the EDC model accurately predicts the profiles of temperature and concentrations of major species (CH4, C2H4 , CO2, CO).

UC Berkley: Sandia Lab (RamanRayleigh-LIF measurements) CH4 (33.33%) / Air (66.67%) NOx chemistry present (including premixed N2 from air)

McKenna Flat flame National Synchrotron Radiation Lab, China (MBMS, Molecular-Beam Mass Spectrometry) C2H4/O2/30% Ar 12 NOx data absent

Validation with John Zink Flare Tests (September 2010, Tulsa, OK) Data Modeling Air-assisted flares (Concentrated, localized fuel leads to a sustained flame)

Air-assist Fuel + Pilot Crosswind Outlet

Stack

• The EDC model with a new geometry (as shown) improves DRE of air-assisted low LHV/low jet velocity propylene flares with an average of 4.6% compared to 13.3% in the 2011 AQRP 10-022 report (for A/F mass ratio 160.0

S = -2718 - 28.3 logBC + 69.8 CCE - 5.80 logBC*logBC 0.427 CCE*CCE R^2=0.53

160

-2

-3

-4 84

86

88

90

92

94

96

98

100

CCE (%)

A < 5000.0 – 10000.0 – 15000.0 – >

0.5 0.0

5000

logBC

15000

-0.5

10000 20000

15000

20000

5000.0 10000.0 15000.0 20000.0 20000.0

Is there a potential for increasing CCE while maintaining low soot emissions?

-1.0

A = -252570 - 6968 logBC + 6806 CCE - 2166 logBC*logBC -1.5

- 43.0 CCE*CCE

-2.0 -2.5

76

80

84

88

CCE(%)

92

96

100

R^2=0.55

Analysis of Incipient Smoke Point Data: Absorbance, Transmittance, Absorptance, and the Beer-Lambert Law According to the Beer-Lambert law,

Transmittance , T = I/IO =>

T = e (-A)

Absorbance is defined as A = - ln (I/IO);

A = ε *L*W Absorptance

= 1 – Transmittance =

Soot visibility

ln (I/IO) =  0.06103 * W*L where I …….. Intensity of transmitted radiation (cd/ft2) Io …… Intensity of incident radiation (cd/ft2) ε ……. Molar absorptivity (104ft2/lb) W…… BC concentration (lb/MMft3) in Combustion Zone L …….. Path length (102ft) estimated from Plume Volume Ref: 1. Hawksley, Badzioch, and Blackett. (1961). Measurement of solids in flue gases. 206 – 209. British Coal Utiliz. Research Assn. Leatherhead. England.

1.2

1.2

1.0

1 Propylene (80%) %TNG (20%) 2010

0.8 0.6

Propane & Nitrogen - 1984

0.4 Propylene (100%) - 2010

0.2 0.0

Absorptance

Absorptance

Absorptance vs. Soot emission

Propylene (80%) % TNG (20%) -2010

0.8 0.6

Propane (80%) &TNG (20%) -2010

0.4

Propylene (100%) - 2010

0.2 0

0

0.5 1 Soot (lb/MMBTU)

Steam assisted flares

1.5

0

2

4 6 8 Soot (lb/MMBTU)

10

Air assisted flares

12

Absorptance vs Soot emission Absorptance = 1 - exp(-5.35586 *BC )

Absorptance = 1 - exp(-2.92011 * BC)

1.0

1.2

1.0

0.8

Absorptance

Absorptance

0.654 0.6

0.4

0.8

0.708 0.6

0.4

0.422

0.2

0.2

0.198

0.0 0.0

0.2

0.4

0.6

0.8

1.0

1.2

0.0

0

2

Soot(lb/MMBTU)

Steam assisted flares Absorptance at 0.1981lb/MMBTU = 0.654 Precision 17 Data Points R^2 = 0.9775 R^2adj = 0.9775 Rmsd = 0.0157 Variance = 0.0044

4

6

Soot (lb/MMBTU)

Air assisted flares Absorptance at 0.422 lb/MMBTU = 0.708

Precision 18 Data Points R^2 = 0.9999 R^2adj = 0.9999 Rmsd = 1.625E-04 Variance = 5.031E-07

8

10

Absorbance vs Soot emission 5

45

4.5

40

4

35 30 Propylene(80%)& TNG(20%)-2010

3 2.5 2

Propane & Nitrogen - 1984

1.5

Absorbance

Absorbance

3.5

Propylene(80%) &TNG(20%) 2010

25 20

Propane(80%) & TNG(20%) 2010

15

Propylene (100%) - 2010

10

1

Propylene(100%) - 2010

0.5 0

5 0

0

0.5 1 Soot (lb/MMBTU)

1.5

Steam assisted flares Absorbance = 4.5983*BC +0.2149 R2 = 0.914

0

5 10 Soot (lb/MMBTU)

Air assisted flares Absorbance = 4.02 *BC +0.272 R2 = 0.8632

ISP? Absorptance = 0.681 = 1 – exp (-Absorbance) Absorbance = 1.14

15

Summary • New mechanism LU3.0.1 was developed to handle both soot and VOC emissions for flaring C1 to C4 light hydrocarbons. • LU3.0.1 in conjunction with Fluent Moss-Brookes soot model was successfully applied in PDF modeling of 2010 flare study air flares and Carleton U’s Lab-scale flares. • Response surface models were developed for Log BC, CE, and DRE. • The most favorable operating ranges are determined via inverse response surface models of steam/air-assists as a function of Log BC and CE. • ISPs are estimated in terms of absorbance/absorptance

36

Planned Year 2 Tasks

Future Work • Work on Geometry/Meshing for steam/air assisted flares. • Continue to simulate 2010 JZ data (Propylene/Propane) and 1983/1984 EPA data (with Propane) with PDF & EDC models. • Include CU’s data (Air-Assist = 0) in statistical analysis • Use Dimensionless Variables in Response Surface Models • Work on CU’s data with Olefins and H2 (if funded). • Study the effect of fuel composition on soot particle size and absorbance (if funded)

Future Work (II) • Optimally define CZHV for steam and air flares. • Better define ISP in terms of absorbance/ absorptance • Better understand the relationship between ISP and soot particle size/ fuel species/plume temperature/steam chemistry, among others. • Analyze operating regions in terms of absorbance/absorptance to achieve overall environmental performance (Soot & CE)

Expanded Definition of CZHV for Steam and Air-assisted Flares f * H  m* H  CZHV   f  m  s  a*x i

i

• • • • • • • •

i

m eff

fi: Volume flow rate of ith component in vent gas m: Volume flow rate of makeup gas a: Volume flow rate of assisted air s: Volume flow rate of assisted steam Hi: Heating Value of the ith component in fuel gas (BTU/scf) Hm: Heating Value of the makeup gas (BTU/scf) CZHV: Combustion Zone Heating Value (BTU/scf) xeff : Effective fraction (effective fraction of air-assist that causes the dilution), 2% is proposed for 2010 JZ Tulsa tests

K. Singh et al, " Parametric Study of Ethylene Flare Operations and Validation of a Reduced Combustion Mechanism," Engineering Applications of Computational Fluid Mechanics, Vol. 8, No. 2, pp. 211–228 (2014). 40

Response Surface Models Using Dimensionless Variables • Consider Reynolds number with Diameter, U or V, air or flame viscosity • Consider Grashof number for flame buoyancy, heat release • Richardson number or momentum ratio

42

Milestone Chart

2nd year Activity Q1 Q2 Q3 Q4 1. CFD Modeling of Flare Tests ▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒ 2. Response Surface Models ▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒ 3. Model Analysis ▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒ 4. Annual/Final Reports ▒▒ ▒▒

Lamar University CFD Lab • Graduate Students – Kader Rasel, Vijaya Damodara, Lan Liu (PhD), Ajit Pataki, Raj Alphones, (DE), Hashim Mrayani, Anan Wang (MES)

• Cutting Edge High Performance Computing (HPC) Cluster – 3 X 12 core servers; Intel Xeon X5670 @2.93GHz – More than 50 high speed processors – Up to 10GBs/second of data transfer speed for faster parallel computing

Acknowledgements • Financial support from Texas Air Research Center (TARC) is gratefully acknowledged. • Special thanks are due to Ed Fortner and Scott Herndon of Aerodyne Research, Inc. (ARI) for providing numeric soot data for 2010 JZ flare campaign.

09/18/2008

Chen, Yuan, Lou, Lin, Li

46 46

Comparison reduced mechanisms for mole fraction of major species at residence time of 1 sec for C3H6 fuel Species

USC II

LU 3.0.1

Abs. error % LU 1.0

Abs. error % LU 2.0

Abs. error %

C2H2

1.46E-06

1.32E-06

9.72

1.19E-06

18.53

1.21E-06

17.23

CH4

3.01E-07

3.02E-07

0.23

3.30E-07

9.68

3.91E-07

30.07

CO

5.59E-03

5.70E-03

1.97

6.24E-03

11.68

5.98E-03

7.06

CO2

1.21E-01

1.21E-01

0.2

1.20E-01

0.64

1.21E-01

0.35

H2

1.35E-03

1.37E-03

2.1

1.51E-03

12.31

1.45E-03

7.41

Average abs. error %

2.84

10.57

12.42

Comparison of prediction errors for mole fraction of trace species at residence time of 1 sec for C3H6 fuel

Species

USC II

New

Error, a factor of

C3H6

4.35E-08

4.67E-08

1.07

4.59E-08

1.05

1.48E-07

3.41

HO2

1.19E-07

1.16E-07

1.02

2.06E-07

1.73

2.51E-07

2.1

OH

1.27E-03

1.33E-03

1.05

1.26E-03

1

1.22E-03

1.04

CH3CHO

3.16E-12

4.22E-12

1.34

3.58E-11

11.34

4.44E-13

7.11

CH2O

2.11E-07

1.68E-07

1.25

1.75E-07

1.21

2.02E-07

1.04

C2H4

1.81E-08

3.16E-08

1.74

3.84E-08

2.12

2.47E-08

1.36

CH2CHO

8.80E-12

1.10E-11

1.25

1.07E-11

1.21

1.70E-11

1.93

Average error

1.25

LU 1.0

Error, a factor of

LU 2.0

Error, a factor of

2.81

2.57

Complexity in Flare Emissions • Process Type (Vent Gas Species/Heating Value/Flammability) – Refinery, Olefin, Polymer, Landfill, and Exploration fields (H2-C4; Alkanes vs. Alkenes) • Operation Mode (Exit velocity) – Startup, Shutdown, Upset, Maintenance, and Standby ( Turndown Ratio up to 15000:1) • Flare Design/Control – Air assisted, Steam assisted, Nonassisted, Pressure-assisted – Elevated, Enclosed – Steaming, Aeration – Tip Diameter • Meteorological condition – Cross wind

What species are emitted? DRE/CE?

ethylene

Methodology Base mechanism

Methodology

Reaction path Analyzer USC-II Reaction Rate analysis

Result

LU3.0.1

Key performance indicators of a flame • Laminar flame speed -Speed at which a laminar flame propagates through a pre-mixture of fuel and air. -Fundamental property of a fuel-air mixture -Strongly influences design parameters of combustion equipment.

• The ignition delay time -Period between the creation of a combustible mixture when the fuel is injected in an oxidizing environment, and the sustained, on onset of the rapid reaction phase leads to the rise of temperature and pressure.

• Adiabatic flame temperature -Measure of the maximum temperature that could be reached by combusting a particular gas mixture under a specific set of conditions.

TCEQ Air assist geometry & mesh

Eddy Dissipation Concept • For turbulent flows – Detailed Arrhenius chemical kinetics can be incorporated in turbulent flames. • It assumes that reaction occurs in small turbulent structures, called finite scales. • Combustion occurs as a constant pressure reactor with initial conditions taken as current species and temperature in the cell. • Reactions, governed by Arrhenius rates proceeding over time are numerically integrated using ISAT algorithm(In-Situ Adaptive Tabulation)

Non-Premixed Combustion (PDF) • Probability Density Function (PDF) model used. • 30 steady flamelets are generated with 100 grid points in each flamelet • Viscous model  k-ε turbulent model (Realizable) with standard wall functions • Moss-Brookes soot model for soot  Soot precursors- C2H2 and C6H6  Surface growth species – C2H2, C2H5 & C6H6

• The mass fraction of the soot as well as the mean mass of individual soot particle can be obtained

EDC Results-Case A1.1 Experiment: DRE = 96.9% CE = 98 % Experiment_soot = 3.05 lb/MM BTU Simulation_soot = 2.6 lb/MM BTU

EDC Results-Case A2.1 Experiment: DRE = 96.8% CE = 97.8 % Experiment_soot = 4.6 lb/MM BTU Simulation_soot = 3.02 lb/MM BTU

Major bottlenecks • Very dilute fuels with low LHVs are difficult to simulate with EDC model • Sufficient mixing is not observed in the EDC cases for dilute fuels. • Simulations for non-premixed combustions are computationally easy but 1. assumes very fast reactions 2. 100% burning of fuel is observed 3. turbulent diffusion at inlet is observed leading to higher errors in C and H balance.

Simulated and experimental combustion efficiency of C1-C4 alkane mixture Jet Velocity (m/s) 0.28 0.56 1 1.67

CE % CE % Experimental Simulation 99.67 (+/-0.31) 99.96 99.70 (+/-0.06) 99.95 99.75 (+/-0.05) 99.93 99.75 (+/-0.04) 99.87

Maximum flame temperature attained by flare

Test no.

Jet velocity (m/s)

Maximum Flame Temperature (K)

12 13 14 15

0.28 0.56 1.00 1.67

1766.2 1783.4 1797.4 1802.1

CO2 yield Jet CO2 yield CO2 yield Velocity experimental simulation m/s kg/kg kg/kg 0.28 2.83 2.85 0.56 2.83 2.84 1 2.84 2.84 1.67 2.84 2.84

Soot yield kg/kg

Jet velocity m/s

•CE are within the experimental uncertainties; •Soot yields are in the same order of magnitude even though the trend is a little off.

New steam geometry

New Air assist geometry

Air ass Pi ga Ve gas

CCE versus CE

17 – 22% decrease in CCE

8% decrease in CCE

CCE vs CE

CCE vs CE

100

100 95

CCE (%)

CCE(%)

95 90

90 85 80

85

75 75

80 80

85

90

95

CE (%)

100

80

85

90

CE (%) Propylene (80%) & Propane (20%) - 1983

Propylene (80%) & Propane (20%) - 1983

Propylene (80%) & TNG (20%) -2010

Propylene (80%)& TNG (20%) - 2010

Propane (80%)& TNG (20%) - 2010

Propylene (100%) - 2010

Propylene (100%) - 2010

Steam assisted flare

Air assisted flare

95

100

Mass fraction of Soot at ISP • Steam assist flare test: Max soot emission – 1.17lb/MMBTU (S8.3.1) Mass of soot/Mass of C in Propylene = 7.469 lb of soot/ 251.14 lb of C = 0.0297lb of soot/lb of C in Propylene

• Air assist flare test: Max soot emission – 9.84 lb/MMBTU (A6.1.1) Mass of soot/Mass of C in Propylene(feed) = 25.22 lb of soot/ 101.14 lb of C = 0.249 lb of soot/ lb of C in Propylene

Flare Operating Parameters • Combustion zone heating value (or lower flammability limit) • Jet velocity/Crosswind • Diameter • Composition • Sensitivity tests for H2 and C1-C4 alkanes by keeping CZHV (or LFL) constant • Sensitivity tests for C2-C4 alkenes by keeping CZHV (or LFL) constant • Sensitivity tests for H2-Etylene, Ethylene-Ethane, PropylenePropane 50%-50% mixture

64

Lower flammability limit (LFL) (I) • Lower flammability limit (LFL, vol.%), an important chemical property, is the lower end of the concentration range (standard value is given at 25 °C and atmospheric pressure) for which air/vapor mixtures can ignite. – The flammability range is confined by the upper and lower flammability limits (UFL & LFL), which are functions of temperature and pressure. – Flammability limits of a combustion zone mixture can be calculated using Le Chatelier's mixing rule for combustible volume %i – All inerts, including nitrogen, are assumed to have an infinite lower flammability limit (e.g., LFLN2 = ∞). – However, adjustments are made for water and carbon dioxide for nitrogen equivalency

Lower flammability limit (LFL) (II) • 1/LFLmix=  (%i/LFLi)-(Ne, H2O-1)xH2O -(Ne,CO2-1)xCO2

• %i = Percentage of combustible component i in mixture, volume percent • xH2O & xCO2= volume fraction for H2O and CO2 • Ne, H2O & Ne,CO2= nitrogen equivalency for H2O and CO2 • 1/LFLi can be viewed as the contribution to flammability for component i • H2O and CO2 can be viewed as contribute negatively to flammability (fire retardants)

Lower flammability limit (LFL)

Time Sequence of Flare Vent Gas Moving Through Flammability Region (Between B & C) [EPA Office of Air Quality Planning and Standards (OAQPS), April 2012.] 67

Publications •

•

•

•

•

•

•

K. Singh, T. Dabade, H. Vaid, P. Gangadharan, D. Chen, H. Lou, X. Li, K. Li, C.Martin, "Computational Fluid Dynamics Modeling of Industrial Flares Operated in Stand-By Mode," Industrial & Engineering Chemistry Research, 51 (39), 12611-12620, October, 2012. H. Lou, D. Chen, C. Martin, X. Li, K. Li, H. Vaid, K. Singh, P. Gangadharan, "Optimal Reduction of the C1-C3 Combustion Mechanism for the Simulation of Flaring, "Industrial & Engineering Chemistry Research, 51 (39), 12697-12705, October, 2012. H. Lou, C. Martin, D. Chen, X. Li, K. Li, H. Vaid, A. Tula, K. Singh,"Validation of a Reduced Combustion Mechanism for Light Hydrocarbons," Clean Technologies and Environmental Policy, 14 (4), pp 737-748, August 2012. H. Lou, C. Martin, D. Chen, X. Li, K. Li, H. Vaid, A. Kumar, K. Singh, & D. Bean, "A reduced reaction mechanism for the simulation in ethylene flare combustion," Clean Technologies and Environmental Policy, 14 (2), pp 229-239, April 2012. Hitesh S. Vaid, Kanwar Devesh Singh, Helen H. Lou, Daniel Chen, Peyton Richmond, "A Run Time Combustion Zoning Technique towards the EDC Approach in Large-Scale CFD Simulations," International Journal of Numerical Methods for Heat and Fluid Flow, Vol. 24 No. 1, 2014, pp. 21-35. Kanwar Devesh Singh, Preeti Gangadharan, Daniel Chen, Helen H. Lou, Xianchang Li, P. Richmond, " Parametric Study of Ethylene Flare Operations and Validation of a Reduced Combustion Mechanism," Engineering Applications of Computational Fluid Mechanics, Vol. 8, No. 2, pp. 211–228 (2014). Kanwar Devesh Singh, Preeti Gangadharan, Daniel Chen, Helen H. Lou, Xianchang Li, P. Richmond, “CFD Modeling of Laboratory Flames and an Industrial Flare,” Journal of the Air & Waste Management Association (in Press, 2014). 68

Incipient Smoke Points of Flare Tests Steam assisted flare tests: Test case

46

91

94

102

105

S1.5

S4.1

S5.1

S6.1

S8.3

Report year

1984

1984

1984

1984

1984

2010

2010

2010

2010

2010

Steam flow (lb/MMBTU)

0

21.43

2.96

3.89

2.38

94

101

111

84

84.85

BC (lb/MMBTU)

0.071

3.97E-05

0.004

3.96E-05

0.004

0.011

0.015

0.683

0.431

1.171

Air assisted flare tests: Test case

A1.1

A2.1

A3.1

A4.1

A5.1

A6.1

A7.1

Report Year

2010

2010

2010

2010

2010

2010

2010

Air Flow (lb/MMBTU)

8247

12000

4950

7600

5250

4440

4679

BC (lb/MMBTU)

3.237

4.442

3.949

2.401

3.901

9.569

0.068

Absorbance vs Soot emission 5

45

4.5

40

4

35 Propane & Nitrogen - 1984

3 2.5

Propylene(100 %) -2010

2

Propylene(100%) -2010

30 Absorbance

Absorbance

3.5

25 Propylene(80%) &TNG(20%) 2010

20 15

1.5

Propylene(80% )&TNG(20%)2010

1 0.5

Propane(80%)& TNG(20%) 2010

10

5 0

0 0

0.5 1 Soot (lb/MMBTU)

Steam assisted flare Absorbance = 4.5983*BC +0.2149 R2 = 0.914

1.5

0

5 10 Soot (lb/MMBTU)

Air assisted flare Absorbance = 4.02 *BC +0.272 R2 = 0.8632

15