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Quantifying Flare Efficiency and Emissions: Application of Research to Effective Management of Flaring Matthew R. JOHNSON Ph.D., P.Eng Canada Research.

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Presentation on theme: "Quantifying Flare Efficiency and Emissions: Application of Research to Effective Management of Flaring Matthew R. JOHNSON Ph.D., P.Eng Canada Research."— Presentation transcript:

1 Quantifying Flare Efficiency and Emissions: Application of Research to Effective Management of Flaring Matthew R. JOHNSON Ph.D., P.Eng Canada Research Chair in Energy & Combustion Generated Air Emissions Mechanical & Aerospace Engineering Carleton University Ottawa, ON, CANADA

2 Quantifying Flare Performance What are the emissions from flaring? How can we best manage and mitigate impacts of flaring?

3 Organization of Research & Results Primary Research Activities: 1.Quantifying Flare Efficiency Understanding factors affecting emissions 2.Modelling flare efficiency and predicting GHG emissions Management tools and strategies 3.Quantifying soot emissions from flares PM reporting and management 4.Development of novel diagnostics Field testing

4 1. "Flare Efficiency" Conversion Efficiency,  – Characterizes combustion completion i.e. mass of carbon in fuel converted to CO 2 and/or mass of sulphur in fuel converted to SO 2 Carbon Conversion Efficiency is defined as: Can also define a Sulphur Conversion Efficiency Fuel as OriginallyCarbon of CO toConvertedCarbon of 2 Mass = 

5 1. Quantifying Flare Efficiency Focus is on Solution Gas Flaring – Flares typically 3-8” diameter – Typical volumes of up to ~10 6 m 3 per year (<2000 SLPM) – Variable composition – ~63 % of flaring/venting in Alberta, Canada Methodology – Mass balance on combustion products – Closed-loop windtunnel testing as well as multipoint sampling in large open-loop windtunnel

6 Methodology: Windtunnel Testing University of Alberta (Closed Loop Tunnel) Bourguignon et al., Comb. Flame 119: (1999)

7 Methodology: Windtunnel Testing National Research Council M-46 (Open Loop Tunnel) Full Scale Solution gas flares

8 1. Results: Flare Efficiency Natural Gas – Flare Efficiency is strongly sensitive to cross-wind – Higher exit velocities are less prone to inefficiency Johnson & Kostiuk, Comb. Flame 123: (2000)

9 Results: Flare Efficiency Effect of Fuel Heating Value Nat. Gas / CO 2 – Reducing energy content has a dramatic adverse effect on efficiency – For a 25mm flare, <15 MJ/m 3 is unstable Crosswind Speed, U  (m/s) F l a r e C o n v e r s i o n I n e f f i c i e n c y, ( 1 -  ) Natural Gas d o =24.7 mm, V j = 2m/s 0% CO /33.8 MJ/m 3 20% CO /27.0 MJ/m 3 40% CO /20.9 MJ/m 3 60% CO /13.8 MJ/m 3 EDNXXCXXV02U XXLAM-QORF-present.grf

10 Results: Flare Efficiency Parametric Modelling Experimental Correlations – Data shown includes: – Nat. gas + CO 2 – Nat. gas + N 2 – 2 < U ∞ < 17 m/s – 0.5 < V j < 4 m/s – 12 < d o < 49 mm Experimentally based predictive tool for flare efficiency

11 Results: Flare Efficiency Implications of Efficiency Data: – Flare performance affected by crosswind, exit velocity, fuel composition (heating value), flare diameter – Flares can have quite high efficiencies with clean, high HV fuels in moderate winds – Scientific support for lower heating value limit of MJ/m 3 in Alberta (AEUB Directive 60) & inclusion in World Bank voluntary standard – What about specific emissions and GHG impacts?

12 2. Flare Emissions What is emitted? – Laser sheet imaging of unburned fuel (green) – Inefficiency by “fuel stripping” – Fuel drawn through non-reacting regions of mean flame and ejected on underside without burning – Confirmed with MS/GC analysis Johnson et al., Comb. Sci. Tech. 169: (2002)

13 2. Flare Emissions and GHG Fuel stripping mechanism means principle GHG contributors are CO 2 and methane Other species may be relevant based on IPCC data but do not have accepted GWP values and are not included in Kyoto Accord: – CO and particulate matter (Direct climate forcing) – NOx and SO 2 (Indirect climate forcing) In line with Kyoto, consider CO 2 and CH 4 only

14 2. GHG Calculation Methodology First, calculate flare conversion efficiency Next, calculate instantaneous rate of CO 2 and CH 4 emissions Must accurately determine split, , between CO and unburned fuel in emissions from efficiency model Major part of ongoing work is to develop better model for this split,  Use IPCC global warming potential values to calculate instantaneous GHG emission

15 2. GHG Calculation Methodology Must convert instantaneous GHG emission calculated at one wind speed value to meaningful "average" value Concept of "Yearly Averaged Efficiency" and "Yearly Averaged GHG Equivalent Emission" – Possible to develop using parametric data set and efficiency model P(U  ) = probability dist. function of wind speed, U   ( U ,D, V j, HV  ) = efficiency of flare as function of wind speed and operating parameters where

16 2. Predicting GHG Emissions Conceptual Summary of Current Work: – Combine modelling efforts to quantify GHG emissions and yearly averaged efficiencies Input statistical wind speed data, simple hydrocarbon flare composition Model yearly averaged carbon conversion efficiency and GHG emissions

17 2. Sample GHG Emissions Calculations Scenario #1: Mean Solution Gas Flare – Q = 246,900 m 3 /yr,D = 4 inch – Flare Gas = 95 % Methane, 5 % CO 2 (LHV = 32.2 MJ/m 3 ) – Flare location: Edmonton (Airport weather data) Yearly Averaged Efficiency: 99.4 % Annual CO 2 equivalent GHG emission: 477 tonnes Scenario #2: “Low BTU” Solution Gas Flare – Q = 246,900 m 3 /yr, D = 4 inch – Gas = 50 % Methane, 50 % CO 2 (LHV = 16.9 MJ/m 3 ) – Flare location: Edmonton (Airport weather data) Yearly Averaged Efficiency: 78.9 % Annual CO 2 equivalent GHG emission: 778 tonnes

18 2. Application of Results AEUB data shows steady reductions in solution gas flaring over past 5 years What are the associated GHG reductions? Can we quantify what is being achieved? Need industry flare composition data

19 3. Quantifying PM Emissions Emission of fine particulate matter (PM) has been linked to serious health effects in humans and animals and environmental damage (US EPA, 2004) In Canada, PM10 and PM2.5 are classed as Criteria Air Contaminants (CAC) and are tracked in the National Pollutant Release Inventory (NPRI) – Lack of methods to meet reporting requirements (especially PM) – Lack of basic data and approaches to manage / control / reduce PM emissions

20 3. Soot / PM Emissions from Flares Formation exceedingly complex; depends on: – Chemical composition of fuel – Turbulent mixing & diffusion of air and fuel species – Rate of heat transfer from flame – Residence time / temperature history through flame Measurement and characterization is difficult No simple formation model exists Research approach: – Develop a quantitative experimental procedure to directly measure soot emissions from fully turbulent, lab-scale flares

21 3. Experimental Setup Sampling enclosure housed at NRC

22 3. New Soot Measurement Protocol Using Laser Induced Incandescence (LII) for high sensitivities We want Soot Yield, Y s : – Need to relate LII measurement data in sample volume to mass of fuel burned: Detailed uncertainty analysis shows protocol accuracy of ~23% with repeatability uncertainty<5% – Much more sensitive and accurate that gravimetric techniques soot volume fraction in sample (ppm) soot yield (mg soot/kg fuel) Full mathematical details in Canteenwalla et al., CI/CS, 2006

23 3. Soot Emissions from Flares Results to date: – High sensitivity, lab-scale, quantitative soot protocol successfully developed and demonstrated Planned Future Directions: – Soot emissions meas. for broad range of conditions Vary flow (exit velocity), diameter, base fuel, mixture components, pipe turbulence – Soot particle property characterization Aggregate size, number densities in emissions, optical properties of soot Continue work toward model development for "soot factors" & PM management strategies

24 4. Novel Optical Soot Diagnostic Searching for a field capable technique to measure soot mass flux from open sources / flares Existing standards still based on qualitative notions of opacity!

25 4. Novel Optical Soot Diagnostic Have developed a proof of concept optical system using a cooled, scientific-grade CCD System is "portable" to facilitate exterior testing Comparisons against proven lab-based collimated light technique Currently quantifying uncertainty & sensitivity limits – Large uncertainties but quantitative (unlike opacity!)

26 4. Novel Optical Soot Diagnostic Results: – Calculated practical sensitivity limits for field measurement – Minimum detectable limit is a function of wind speed, U, & plume diameter, w – Ongoing work to develop technique for field testing – Promising very early results Below detectable limits Quantifiable

27 Summary & Conclusions Quantitative data on efficiency of solution gas flares through extensive windtunnel testing – Flares strongly affected by crosswind, fuel composition (heating value) – Secondary dependence on exit velocity and flare diameter – Scientific support for regulatory guidelines for minimum heating value to be burned in flares (AEUB Directive 60) Have developed quantitative model for yearly averaged solution gas flare efficiency and GHG prediction – Can start to calculate management and regulatory scenarios – Need industry flare composition data to start making comprehensive calculations of emissions inventories and GHG reductions

28 Summary & Conclusions Ongoing work to quantify PM (soot) emissions from flares – Have developed and demonstrated lab-scale sampling protocols based on laser induced incandescence (LII) technique – Soot formation is very complex, but goal is to provide practical management guidelines to quantify soot emissions from flares Promising progress on quantitative field optical technique to estimate soot mass flux in plumes – Still early in development phase but promising early results – Potential significant development over qualitative opacity standards Continuing to work to develop practical tools to help manage and mitigate effects of flaring

29 Research Team Principle Investigators: – Matthew Johnson, Larry Kostiuk, Greg Smallwood, Kevin Thomson, David Wilson Graduate Students: – Eric Bourguignon, Pervez Canteenwalla, Adrian Majeski, Pascal Poudenx, Rob Prybysh, George Skinner, Stephanie Trottier, Chen Yang Technical Staff: – Faz Baksh, Bob Sawchuk, Reg Smith, Glen Thomas, Oleg Zastavniuk

30 Research Partners


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