CEscoffier DMUG2013w and some applications

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CALPUFF MODEL OVERVIEW AND SOME APPLICATIONS Dr. Christelle Escoffier 9 December 2013 DMUG meeting, St Martin in the fields, London

Content  CALPUFF model characteristics  CALPUFF validation studies for near-field and longrange applications  CALPUFF applications  Cumulative Impact  Odour nuisance evaluation

REGULATORY STATUS  CALPUFF is used in over 100 countries and it is accepted for use in near-field/far-field applications by many international environmental agencies in Australia, Canada, Chile, China, Iceland, Italy, New Zealand, Saudi Arabia, South Africa and others  CALPUFF is one of the two main USEPA Guideline Models  CALPUFF is the preferred model recommended for BART assessments (EPA,2005)

 CALPUFF is used by United Nations/International Atomic Energy Agency (IAEA, 2010) in its SIMPACTS software package (a simplified approach for estimating impacts of electricity generation) – used worldwide in developing countries  CALPUFF is recommended by  U.S. Federal Land Manager’s Air Quality Related Values Workgroup (FLAG, 2010)  U.S. Interagency Workgroup on Air Quality Modelling – Phase 2 (IWAQM, 1998)

OVERVIEW  Non-steady-state Lagrangian Puff Model  Design for fenceline (~meters) to long-range transport (hundreds of kilometres)  3D-variable meteorological data (to represent complex meteorology events)  Sea breeze, complex terrain, stagnation

 2D-spatial variability of terrain and landuse and their associated parameters  Temporal change of landuse can be modelled (snow, flooding, etc)

OVERVIEW  Averaging time from 1-hour to one+ year  Sub-hourly time steps allowed in version 6 of models

• Point, area, line, and volume sources • Buoyant or non-buoyant sources • Special modules for fires, flares and overwater platforms

 Open source model – can be used for research, development, regulatory applications, etc…  Available at http://www.src.com

 New GUI (windows 7 and 64bit compatible) developed by Exponent (available soon)

CALPUFF IS A NON-STEADY-STATE LAGRANGIAN PUFF MODEL  Allows variable curve trajectory  Follow terrain in valley / variability in wind speed/direction

 Meteorological conditions vary and are not assumed steady-state  Spatial variability due to winds and turbulence fields  Spatial variability of geophysical surface conditions

 Retains information of previous hour  Stagnation, Recirculation, Fumigation

 Allows calm and low wind speeds  Includes causality effects (plume does not extend to infinity, size of plume depends on wind speed)

EXAMPLE: Tall stack point source - coastal area Tall stack = 75 m No building downwash Display: Wind vectors Mixing height (m) Concentrations (μg/m3) Land/Sea breeze is shown on a 2-day period

EXAMPLE: Tall stack point source - coastal area Tall stack = 75 m No building downwash Display: Wind vectors Mixing height (m) Concentration (μg/m3) It shows: Curve trajectory Remember previous hours Spatial variability of wind & landuse Spatial variability of mixing height Causality effects

EXAMPLE OF NON-STEADY-STATE MODELS  Lagrangian Puff models  CALPUFF  SCIPUFF

 Particle Dispersion models  KSP (Kinematic Simulation Particle Model)  TAPM (The Air Pollution Model)  Hysplit (HYbrid, Single-Particle Lagrangian Integrated Trajectory)

 Eulerian grid models  CMAQ  CAMx  CALGRID

CALPUFF DESIGNED FOR NEAR-FIELD  Stack tip downwash  Building downwash (PRIME and ISC)  Dispersion options  PG Dispersion, Dispersion parameters internally calculated

 Plume rise  Boundary layers (different for overwater and overland)  Subgrid scale  For coastline effect  For complex terrain

 Fogging and icing – cooling tower  Visible plume length calculation

CALPUFF DESIGNED FOR LONG-RANGE  Chemistry schemes options  Wet deposition  Aqueous phase oxidation of SO2 in cloud and rainwater  Scavenging coefficient method  Function of precipitation type (rain vs. snow)

 Dry deposition  Resistance-based deposition model  Plume tilt effects (gravitational settling)

 Recirculation, Stagnation, Flow reversal  Boundary conditions  Puff Splitting / Vertical Wind Shear

CHEMISTRY  Secondary Pollutant Formations (NO3, SO4, SOA)  Original Scheme

 MESOPUFF II scheme (NOX, SO2) and RIVAD/ARM3 (NO2, SO2)  User-specified diurnal cycle of transformation rate (NOX, SO2)

 New Schemes  ISORROPIA (as in CMAQ)  Aqueous phase oxidation of SO2  For SOA (CalTech SOA routine from CMAQ-Madrid)

 NO2/NOX ratio (empirical function in CALPOST from NOX/NO2 measurements to estimate NO2 from NOX)

 Time decay

 23 nuclear species  Parent and daughter species  Half life decay (half life values – 2.5 minutes to 2-8 days to > 1 year)

METEOROLOGICAL DATA FOR CALPUFF  Single-met station (same as for AERMOD or ISC) – lit version  Plume will go in a straight line (directed by met station wind), cannot reproduce changes due to changes in valley orientation

 3D-meteorological data (from CALMET diagnostic model) – recommended way to use the model  Allows full potential of model (including complex terrain modeling)  2D geophysical domain needed (terrain + landuse + parameters)  Input to CALMET  Observations (upper air sounding and weather meteorological stations)  Prognostic models such as WRF, MM5, ETA, RUC, TAPM  Sources for WRF & MM5 (if used as input from CMAQ (already developed) or can be purchased from various data providers as single point meteorological stations)

 Options to run CALMET  Observations only (OBS mode)  Prognostic models outputs only (NOOBS mode)  Observations and Prognostic models outputs (HYBRID mode)

New GUI Interface CALApps: Example CALMET

New GUI Interface CALApps: Example CALMET

New GUI Interface CALApps: Example CALMET

Hourly Meteorological Data: CALMET output (3D) Or ISCMET output (1D) Or AERMET outputs (1D)

CALPUFF DISPERSION MODEL

Emissions: Varying emission files

CALPUFF OUTPUT: Predicted Concentration Fields Predicted Dry Flux Fields Predicted Wet Flux Fields CALPUFF output list File Relative Humidity Data Temperature Data Density Data

Optional Files: -Hourly Ozone - Subgrid Scale Coastal Boundary -Complex Terrain Receptor Data -Complex Terrain Hill Data -Boundary File for Mass Flux Diagnostics -User-Specified Velocities -User-Specified Chemical Conversion Rates -Input Restart File

Postprocessors to extract and view data: CALPOST CALUTIL CALSUM, etc...

NEAR-FIELD VALIDATION Example: Kincaid Tracer • Kincaid Power Plant • Tall stack (187m) located in flat farmland in Illinois • 200 SF6 samplers in arcs of:  7 arcs < 10 km: 0.5, 1, 2, 3, 5, 7, 10 km  5 arcs > 10 km: 15, 20, 30, 40 and 50 km • 171 hours of tracer experiments • Data Quality Index (QI)  QI = 3 (best quality, well-defined maximum observed)  QI = 2 (a maximum is identified, but true max may be different)  QI = 1, 0 – not used

Kincaid SF6 (Development) Ordered by Rank (QI=3) Arc-Max 3 1000

1:1 Line 2x Line (Overprediction)

2.8

2.6 0.5 Line (Underprediction)

Modeled Chi/Q (ns/m3)

2.4

2.2 AERMOD

2 100 CALPUFF v5.8 CTDM CALturb PsvPsw

CALPUFF v5.8 CTDM PG

1.8 CALPUFF w/ turb. disp

AERMOD v07026 NoSVW PsvPsw

ISCSCT3 ISCMET

1.6 CALPUFF w/ PG disp

1.4

1.2

101 1 10

ISCST3

1.2

1.4

1.6

1.8

2 100

2.2

Observed Chi/Q (ns/m3)

2.4

2.6

2.8

3 1000

Kincaid SF6 (Development) Ordered by Rank (QI=2,3) Arc-Max 3 1000

2.8 CALPUFF v5.8 CTDM CALturb PsvPsw

2.6

CALPUFF v5.8 AERMET CALturb PsvPsw

Modeled Chi/Q (ns/m3)

2.4

2.2 AERMOD v07026 PsvPsw

2 100

1.8

1.6

1.4

1.2

101 1 10

ISCSCT3 ISCMET

1.2

1.4

1.6

1.8

2 100

2.2

2.4 3

Observed Chi/Q (ns/m )

2.6

2.8

3 1000

LONG-RANGE VALIDATION Example: European Tracer Experiment (ETEX) • Designed for emergency response model evaluation • PMCH tracer release in Oct and Nov 1994 from north western France • 12-hour release starting on Oct 23, 1994 at 16:00 UTC • 3-hour average samples at various times over 168 samplers in 17 countries

~300 km Source: Scire et al. 2013

300 km x 300 km box

• Most samplers over 300 km away with tracer measured to over 2000 km from release site

ETEX BASE – CALPUFF 36KM MMIF (run with some errors)

ETEX 4 – CALPUFF 12-KM CALMET

- Run on the left was performed by a third-party with some errors in settings and a lower meteorological resolution. Meteorology is an important parameter for long-range applications using lagrangian models - By making setting corrections and properly using wind shear with the 12-km MM5 fields, the model performance is dramatically better and comparable to other models results such as CMAQ, HYSPLIT, FLEXPART (not shown) Source: Scire et al. 2013

A Few Examples of CALPUFF Applications  Regulatory applications (coal-fired, gas-fired, biomass power plants, aluminium smelters, refineries, etc...)  Road traffic modelling (special slug options for nearsource impact)  City-wide modelling / Airport modelling  Cumulative impacts assessment  Forecasting system development (MM5/CALMET/CALPUFF)  Spray dispersion modelling (coupled with AGDISP)  Odour nuisance evaluation

APPLICATION: Cumulative Impact Assessment in the USA Sea Breeze Case – July 7, 1988 – 1:00pm LST 71.5W

72.0W

Site A is considered 70.0W the main source and the location of 43.0Nthe meteorological station used in AERMOD

70.5W

71.0W

4760

Sea 4740

Breeze

Land

UTM North (km)

Breeze

C

B

4720

Sites B and C are the locations of the background sources to be added to the 42.5N cumulative impact Assessment

1

2

4700

A

Wind vectors display from CALMET model

3

4680

4660

4640 260

280

300

320

340

UTM East (km)

360

380

400

Within the PSD program, 42.0N if Source A’s impact is above SILs, a cumulative impact assessment is required 420

APPLICATION: Cumulative Impact Assessment in the USA: Sea Breeze Case – July 7, 1988 – 1:00pm LST 71.5W

72.0W

70.5W

71.0W

70.0W

UTM North (km)

43.0N

CALPUFF plumes from 3 sources

4760

Project facility in land breeze area (A)

4740

Two background sources in sea breeze area (B & C)

C

B

4720

1

42.5N

2

4700

AERMOD model using meteorological observations (A) close to project facility

A 3

4680

4660 42.0N 4640 260

280

CALPUFF plume direction

300

320

340

UTM East (km)

360

380

400

AERMOD plume direction

420

To be applied for all sources (A, B & C) in the cumulative application

APPLICATION: Odour Nuisance Evaluation in NSW, Australia Most odours are a complex mixture of many odorous compounds

Odour is a Nuisance: Odour detection is frequently below the health standard

Dynamic Dilution Olfactometry is the preferred method of measuring odour and is endorsed worldwide

Compound

Workplace standard (ug/m3)

Odour Threshold (ug/m3)

Odour strength is quantified in terms of odour units, a measure of odour concentrations

Ethyl mercapton

43

0.075 – 2.5

Hydrogen sulfide

470

0.7 – 7

Methyl mercapton

33

0.04 - 4

APPLICATION: Odour Nuisance Evaluation, NWS Australia Why modelling odour with CALPUFF?

Description

Steady-State plume models

Non-Steady-State puff model ‘Memory’ of previous emissions allows build-up of odours under stagnant conditions which occur typically through the night

Stagnation and retention

No ‘memory’ of previous hours emissions

Treatment of calms

Unable to treat calms Assume non-zero wind

Well-suited to treating calms. Puffs are able to diffuse without being advected.

Causality effects

Straight line trajectories, plume travels to infinity even after 1-hour

Allows variable/curved trajectories

Spatial and temporal variability

Spatially constant met. Conditions

Spatially varying met. conditions

Recirculation / flow reversal

Not suitable

3D circulation through combination of prognostic model data

Note: When high resolution meteorology is available , sub-hourly time steps could be modelled with CALPUFF

APPLICATION: Odour Nuisance Evaluation in NSW, Australia Example: sewage treatment plant

-point sources, volume sources and area sources are modelled -Species modelled: Odour (in OU) -2 OU and 7OU plotted POPULATION DENSITY OF AFFECTED COMMUNITY (PERSONS PER KM2)

IMPACT ASSESSMENT CRITERIA (ODOUR UNITS) NOSE RESPONSE TIME AVG.

Urban areas (≥~ 2000) and/ or schools and hospitals

2.0

~ 500

3.0

~ 125

4.0

~ 30

5.0

~ 10

6.0

Single residence (≤ ~ 2)

7.0

Source: Approved Methods for the Modelling and Assessment of  Air Pollutants in NSW, DECCW 2005

Odour impact assessment (1-second averaging time (nose response time) ) Concentrations predictions are in 1-h average (if meteorological data are hourly) A ‘peak to mean ratios’ method is applied to the 1-hr averaging period predictions of CALPUFF Predictions are interpreted as one second averaging period values

APPLICATION: Odour Nuisance Evaluation in NSW Adjustment to 1-hr averaging period to sub-hourly period 1/5th Power Law The 1/5th power law is frequently used to estimate < 1-hour odour concentrations. C1 = C0 * ( t0 / t1 ) p where :

C0 = the initial (1-hour average) concentration C1 = the concentration at the desired avg. period t0 = the initial (60-minute) averaging period t1 = the desired averaging period (minutes) p = power law exponent (0.2)

OR Peak-to-Mean ratio (PtM) The PtM takes into account the ratio of the peak smelled by the nose over a short-period and the average dispersion model result over 1-hour

Tables with variable Peak-to-Mean ratios as a function of type of source, stability and near-field/far-field are available in DECCW (2005). CALPUFF has settings options to handle the variable peak-to-mean ratios

CONCLUSION  CALPUFF is used in over 100 countries and it is accepted for use in near-field/far-field applications by many international environmental agencies  CALPUFF is designed to model concentrations at a few meters from sources and for long-range transport  It is has been evaluated and validated for all ranges

 Inputs are 3D-variable meteorological data  to represent complex meteorology events and complex terrain (flow in valleys, slopes flow, sea breeze in coastal area, etc...)

 Because of its characteristics, it is a good tool for applications involving (but not limited to)  Sea breeze, complex terrain, stagnation, cumulative impact analysis with background sources, odour modelling, etc...

THANK YOU FOR YOUR ATTENTION

Contact Information: Dr. C Escoffier [email protected]