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Modelled Meteorology - Applicability to Well-test Flaring Assessments

Modelled Meteorology - Applicability to Well-test Flaring Assessments. Environment and Energy Division Alex Schutte Science & Community Environmental Knowledge Fund Forum and Workshop May 29 th , 200 3. Assessing Potential Impacts from Flares.

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Modelled Meteorology - Applicability to Well-test Flaring Assessments

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  1. Modelled Meteorology - Applicability to Well-test Flaring Assessments Environment and Energy Division Alex Schutte Science & Community Environmental Knowledge Fund Forum and Workshop May 29th, 2003

  2. AssessingPotential Impacts from Flares • Objective: To ensure adequate protection of the environment prior to emitting pollutants into the atmosphere • In mountainous terrain - Wind Speed and Wind Direction are the main factors affecting potential impacts.

  3. Overview • Modelled vs Measured Meteorological Data Best data for estimating impacts are measured data – Would need significant amounts to cover every valley Modelled data can provide a potential worst case indication prior to the event • Current WLAP Accepted Dispersion Models require meteorological data from one “location” and assume a uniform wind field (pollutants disperse in a straight line).

  4. Meteorology • The best is on-site observation of wind and temperature for a five year period • Typically - one year observations at another location • topography often very different and off-site weather (wind) not the same as that on the site

  5. Objective • Research comparedmeteorological model outputs with independent site measurements to assess the accuracy of substituting modelled meteorological data for in situ observations

  6. Approach • Stage 1 - The Mesoscale Model Version 5 (MM5)Prognostic meteorological model was compared for use in current models • Stage 2 - The output from MM5 was then coupled with a Diagnostic meteorological model (CALMET) and the resultant meteorological fields similarly assessed.

  7. Approach • Stage 3 - Afew case studys using observed measurements vs the above results were assessed

  8. Climate • Long term Wind Speed and Direction Data available at 4 stations in Northern BC - PG, FSJ, Beatton River, Fort Nelson

  9. Upper Air Stations • Western Canada is limited - Prince George - Fort Nelson

  10. Surface Stations • Environment Canada – No wind data • Forestry – Historically no data collection in winter • WLAP/Industry – few long term records in areas of flaring activities

  11. Stage 1 Table River Tumbler - Denison Observations MM5

  12. Stage 1 - Conclusions • MM5 data at a 20km resolution does not sufficiently resolve the wind field • Finer resolution data may be able to resolve the winds however would require applying the model to a smaller area – (More resources)

  13. Stage 2 • Applied CALMET to a 1km Resolution • Supplemented with actual meteorology except for the station of Interest • Results were compared

  14. Stage 2 • CALMET Extracted (Grid 21, 43) Wind Rose versus Rotated Top – Actual Rotated (33 degrees) Bottom - Tumbler 1993-1994- CALMET • Extraction for Grid Point (21,43)

  15. Stage 2 • CALMET Extracted Grid Point (20,38) Wind Rose versus Rotated Tumbler Top – Actual Rotated (55 degrees) Bottom - Tumbler 1993-1994- CALMET

  16. Illustration of 3-D Wind field

  17. Stage 2 - Summary • CALMET wind fields are more “realistic” than the current assumed uniform wind fields • A 1km resolution was sufficient to provide a reasonable representation • Prognostic (MM5) or UBC (MC2) data should be used as input to the model Avoids the ‘straight impact’ limitation in ISC3

  18. Stage 3 – Case Studies • Current Regulatory Requirements: No in situ meteorological data – use surrogate station. • Both ISC and RTDM must be run and combined into one set of model outputs. • Protocols focus on worst-case concentrations

  19. Stage 3 – Model Results • For each case, WLAP methods were applied and then the CALMET/CALPUFF methods were applied. • Results produced similar maximum worst case concentrations – neither model indicated a propensity to be higher or lower. • The spatial distribution of concentrations were different.

  20. Model Illustration Data (Raw) • Dir Ws • 107.7000 0.5330 • 86.3000 0.7140 • 78.0000 1.7170 • 243.2300 0.4170 • 73.0000 0.0680 • 194.1100 1.4140 • 176.2000 5.4580 • 345.2000 0.5730 • 218.7700 1.9120 • 205.4600 1.4190 • 226.3000 1.8590 • 270.8000 2.6700 • Calms to (1m/s) in ISC3, Dir- Wind “Towards”

  21. Current Shortcomings • Straight-line Gaussian models assume instantaneous dispersion for the hour with a uniform wind field. • When used to predict concentrations, if meteorology is not local, results can be meaningless. • Even if local meteorology is used, results may not be valid - too much reg. focus on max. • Model predictions may indicate unlikely high concentrations in unlikely locations – affects how others may conduct monitoring.

  22. New Approach - Using CALMET/CALPUFF • Among other conclusions in the report: • It is a viable approach that can act as a substitute for collecting long-term meteorological data in the region. • Using a modelled refined data set eliminates the subjectivity of applying/rotating other data sets. • Large modelling domains can be created one time for many flaring locations. • Limited by the availability of prognostic data to a fine enough resolution.

  23. Future Possibilities • Evolve to the point where CALPUFF/CALMET is viable for all locations in addition to the study area • Future Research (perhaps joint with UBC) to evaluate refined data sets (eg. 1km), and perhaps even use as real meteorology? • Evaluate how the more meaningful results compare with ambient sampling, based on actual data • Research better ways to site ambient monitors that do not rely on worst-case ambient predictions (e.g. wind prob. & direction, etc)

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