understanding the usepa’s aermod modeling system for environmental managers

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Air Pollution Research Group Understanding the USEPA’s AERMOD Modeling System for Environmental Managers Ashok Kumar University of Toledo [email protected] Model Evaluation

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Understanding the USEPA’s AERMOD Modeling System for Environmental Managers. Model Evaluation. Ashok Kumar University of Toledo [email protected]. Evaluation Studies on AERMOD. USEPA Evaluation using field studies No evaluation using ambient air monitoring network in an urban area. - PowerPoint PPT Presentation

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Page 1: Understanding the USEPA’s AERMOD Modeling System for Environmental Managers

Air Pollution Research Group

Understanding the USEPA’s AERMOD Modeling System for

Environmental Managers

Ashok KumarUniversity of Toledo

[email protected]

Model Evaluation

Page 2: Understanding the USEPA’s AERMOD Modeling System for Environmental Managers

Air Pollution Research Group

Evaluation Studies on AERMOD

USEPA Evaluation using field studies No evaluation using ambient air monitoring

network in an urban area

Page 3: Understanding the USEPA’s AERMOD Modeling System for Environmental Managers

Air Pollution Research Group

Lucas County: Sources and Monitoring Stations

SOURCE AND MONITOR LOCATIONS FOR SO2

4608

4610

4612

4614

4616

4618

4620

286 288 290 292 294 296 298

EASTING (UTM) KM

NO

RT

HIN

G (

UT

M)

KM

MAIN SOURCES SUPERSTACKS MONITORING STATIONS

Page 4: Understanding the USEPA’s AERMOD Modeling System for Environmental Managers

Air Pollution Research Group

Input Data Flow in AERMOD

Page 5: Understanding the USEPA’s AERMOD Modeling System for Environmental Managers

Air Pollution Research Group

Data Requirements for Model Evaluation

Emission Inventory Properties of stacks and super stacks Meteorological data Receptor data Air monitoring data

Page 6: Understanding the USEPA’s AERMOD Modeling System for Environmental Managers

Air Pollution Research Group

AERMET - Input

1. Meteorological Input Parameters – Multi-Level WS, WD, and Temperature, Opaque Cloud Cover, Ceiling Height, RH, Pressure, Surface Heat Flux, Friction Velocity, and Roughness Length, Delta-T , Solar Radiation, Upper Air Data

2. Data Formats - CD144, SCRAM, SAMPSON (surface data)

1. TD 3280 (surface data )

2. TD6201 (upper air data)

3. On-site (site specific data)

Page 7: Understanding the USEPA’s AERMOD Modeling System for Environmental Managers

Air Pollution Research Group

AERMET - Output

Boundary Layer File sensible heat flux surface friction velocity convective velocity scale potential temp. gradient above

mixing height convectively-driven mixing height mechanically-driven mixing height Monin-Obukhov length surface roughness length Bowen ratio albedo 

Profile File Measurement height WD, WS Temperature Standard Dev. of

Lateral WD Standard Dev. of

Vertical WS

Page 8: Understanding the USEPA’s AERMOD Modeling System for Environmental Managers

Air Pollution Research Group

Atmospheric Stability

AERMOD uses Monin-Obukhov length as the stability parameter

You will need friction velocity u*and the flux of sensible heat H to compute L

L is defined to be negative in convective conditions and positive in stable

Page 9: Understanding the USEPA’s AERMOD Modeling System for Environmental Managers

Air Pollution Research Group

AERMAP

Input data needs for AERMAP: DEM formatted terrain data User provided receptors and terrain Design of receptor grid: AERMAP accepts

either polar, cartesian or discrete receptors

Page 10: Understanding the USEPA’s AERMOD Modeling System for Environmental Managers

Air Pollution Research Group

Pathways Used in AERMOD Input Runstream

Control Source Receptor Meteorology Output

Page 11: Understanding the USEPA’s AERMOD Modeling System for Environmental Managers

Air Pollution Research Group

Statistical Evaluation Methods

Fractional Bias (FB)

Normalized Mean Square Error (NMSE)

Page 12: Understanding the USEPA’s AERMOD Modeling System for Environmental Managers

Air Pollution Research Group

Statistical Evaluation Methods

Coefficient of Correlation (COR)

Factor of Two (Fa2)Fraction of data for which 0.5<Cp/Co<2

po cc

pooo CCCCr

))((

Page 13: Understanding the USEPA’s AERMOD Modeling System for Environmental Managers

Air Pollution Research Group

Statistical Evaluation Methods

Confidence LimitsConfidence limits are the lower and upper boundaries / values of a confidence interval, that is, the values which define the range of a confidence interval. The upper and lower bounds of a 95% confidence interval are the 95% confidence limits.

Q-Q PlotsThe quantile-quantile (Q-Q) plot is a graphical technique for determining if two data sets come from populations with a common distribution.

Page 14: Understanding the USEPA’s AERMOD Modeling System for Environmental Managers

Air Pollution Research Group

Results & Discussion

Model is evaluated in the following ways: Performance measures and confidence limits for3-hr average for SO2

Stable Condition Convective Condition

24-hr average for SO2

Plots of NMSE vs.FB Q-Q plots for 3-hr average for S02

Q-Q plots for 24-hr average for S02

Page 15: Understanding the USEPA’s AERMOD Modeling System for Environmental Managers

Air Pollution Research Group

NMSE vs FB plots (3-hr average)

Plot of NMSE VS. FB (Main Street Station - Stable Case)

0

0.5

1

1.5

2

2.5

-1.5 -1 -0.5 0 0.5 1 1.5

FB

NM

SE

NMSE CURVE NMSE VERSUS FB

Page 16: Understanding the USEPA’s AERMOD Modeling System for Environmental Managers

Air Pollution Research Group

NMSE vs. FB plots(3-hr average)

Plot of NMSE VS. FB (Main Street Station - Convective Case)

0

1

2

3

4

-1.5 -1 -0.5 0 0.5 1 1.5

FB

NM

SE

NMSE CURVE NMSE VERSUS FB

Page 17: Understanding the USEPA’s AERMOD Modeling System for Environmental Managers

Air Pollution Research Group

NMSE vs. FB plots (3-hr average)

Plot of NMSE VS. FB (Collins Park Station - Stable Case)

0123456

-2 -1.5 -1 -0.5 0 0.5 1 1.5 2

FB

NM

SE

NMSE CURVE NMSE VERSUS FB

Page 18: Understanding the USEPA’s AERMOD Modeling System for Environmental Managers

Air Pollution Research Group

NMSE vs. FB plots (3-hr average)

Plot of NMSE VS. FB (Collins Park Station - Convective Case)

0

1

2

3

4

-1.5 -1 -0.5 0 0.5 1 1.5

FB

NM

SE

NMSE CURVE NMSE VERSUS FB

Page 19: Understanding the USEPA’s AERMOD Modeling System for Environmental Managers

Air Pollution Research Group

NMSE vs. FB plots (24-hr average)

Plot of NMSE VS. FB

0

0.5

1

1.5

2

2.5

-1.5 -1 -0.5 0 0.5 1 1.5

FB

NM

SE

NMSE CURVE NMSE VERSUS FB (Main Street)

NMSE VERSUS FB (Collins Park)

Page 20: Understanding the USEPA’s AERMOD Modeling System for Environmental Managers

Air Pollution Research Group

Q-Q plots (3-hr average)

70 7080 8090 90

100 100

Q-Q plot for 3-hr average for Main Street Station - Stable Case

0

50

100

150

0.00 20.00 40.00 60.00 80.00 100.00 120.00

Observed Concentrations (μg/m3)

Pre

dic

ted

C

on

cen

trat

ion

s (μ

g/m

3)

Q-Q plot Reference line

Page 21: Understanding the USEPA’s AERMOD Modeling System for Environmental Managers

Air Pollution Research Group

Q-Q plots (3-hr average)

Q-Q plot for 3-hr average for Main Street Station - Convective Case

0

50

100

150

0.00 20.00 40.00 60.00 80.00 100.00 120.00 140.00

Observed Concentrations (μg/m3)

Pre

dic

ted

C

on

ce

ntr

ati

on

s

(μg

/m3

)

Q-Q plot Reference line

Page 22: Understanding the USEPA’s AERMOD Modeling System for Environmental Managers

Air Pollution Research Group

Q-Q plots (3-hr average)

Q-Q plot for 3-hr average for Collins Park Station - Stable Case

02040

6080

0 10 20 30 40 50 60 70

Observed Concentrations (μg/m3)

Pre

dic

ted

C

on

ce

ntr

ati

on

s

(μg

/m3

)

Q-Q plot Reference line

Page 23: Understanding the USEPA’s AERMOD Modeling System for Environmental Managers

Air Pollution Research Group

Q-Q plots (3-hr average)

Q-Q plots for 3-hr average for Collins Park Station - Convective Case

02040

6080

0 20 40 60 80

Observed Concentrations (μg/m3)

Pre

dic

ted

C

on

ce

ntr

ati

on

s

(μg

/m3

)

Q-Q plot Reference line

Page 24: Understanding the USEPA’s AERMOD Modeling System for Environmental Managers

Air Pollution Research Group

Q-Q plots (3-hr average) Observed Concentrations

< 20µg/m3Q-Q plots for 3-hr average for Main Street Station - Stable Case

0

5

10

15

20

25

0.00 5.00 10.00 15.00 20.00 25.00

Observed Concentrations (µg/m3)

Pre

dic

ted

Co

ncen

trati

on

s(µ

g/m

3)

Page 25: Understanding the USEPA’s AERMOD Modeling System for Environmental Managers

Air Pollution Research Group

Q-Q plots (3-hr average) Observed Concentrations

< 20µg/m3Q-Q plots for 3-hr average for Main Street Station - Convective

Case

0

5

10

15

20

25

0.00 5.00 10.00 15.00 20.00 25.00

Observed Concentrations (µg/m3)

Pre

dic

ted

Co

ncen

trati

on

s (

µg

/m3)

Page 26: Understanding the USEPA’s AERMOD Modeling System for Environmental Managers

Air Pollution Research Group

Q-Q plots (3-hr average) Observed Concentrations

< 20µg/m3Q-Q plots for 3-hr average for Collins Park - Stable Case

0

5

10

15

20

25

0 5 10 15 20 25

Observed Concentrations (µg/m3)

Pre

dic

ted

Co

ncen

trati

on

s (

µg

/m3)

Page 27: Understanding the USEPA’s AERMOD Modeling System for Environmental Managers

Air Pollution Research Group

Q-Q plots (3-hr average) Observed Concentrations

< 20µg/m3Q-Q plots for 3-hr average for Collins Park - Convective case

0

5

10

15

20

25

0 5 10 15 20 25

observed concentrations (µg/m3)

Pre

dic

ted

co

ncen

trati

on

s (

µg

/m3)

Page 28: Understanding the USEPA’s AERMOD Modeling System for Environmental Managers

Air Pollution Research Group

Q-Q plots (24-hr average)

Q-Q plot for 24-hr average for Main Street Station

0

1020

30

40

5060

70

0 10 20 30 40 50 60 70

Observed Concentration (µg/m3)

Pre

dic

ted

Co

nc

en

tra

tio

n

(µg

/m3

)

Q-Q plot Reference line

Page 29: Understanding the USEPA’s AERMOD Modeling System for Environmental Managers

Air Pollution Research Group

Q-Q plots (24-hr average)

Q-Q plot for 24-hr average for Collins Park Station

0

1020

30

40

5060

70

0 10 20 30 40 50 60 70

Observed Concentration (µg/m3)

Pre

dic

ted

Co

nc

en

tra

tio

n

(µg

/m3

)

Q-Q plot Reference line

Page 30: Understanding the USEPA’s AERMOD Modeling System for Environmental Managers

Air Pollution Research Group

Confidence Limits (3-hr average)

The values of NMSE and FB were significantly different from zero in the stable case. COR was not significantly different from zero.

The values of NMSE, FB, and COR were not significantly different from zero for the convective case.

Page 31: Understanding the USEPA’s AERMOD Modeling System for Environmental Managers

Air Pollution Research Group

Confidence Limits (24-hr average)

The values of NMSE and FB were significantly different from zero. COR, was not significantly different from zero.

Note: 24-hr data were not divided according to stability classes.