Achieving compliance in dispersion modeling can be quite challenging because of the tight National Ambient Air Quality Standards (NAAQS). In addition, AERMOD’s limitations can, in many cases, produce higher than normal concentrations due to the inherent assumptions and simplifications in its formulation. In the case of downwash, the theory used to estimate these effects was developed for a limited set of building types. However, these formulations are commonly used indiscriminately for all types of buildings. This presentation will cover how the basics of wind tunnel modeling can overcome some of these limitations and be used to mitigate downwash induced overpredictions to achieve compliance.

1. www.cppwind.comwww.cppwind.com
Using Physical Modeling to
Refine Downwash Inputs to
AERMOD
Rocky Mountain States Section –
Air & Waste Management Association
Denver, CO
Sergio A. Guerra, PhD
Ron Petersen, PhD, CCM
April 13, 2017

2. Outline
1. Building Downwash in AERMOD
2. Equivalent Building Dimensions Method
3. Potential Benefits
Using Physical Modeling to Refine Downwash Inputs to AERMOD2

3. 3
Compliance?Compliance?
BPIPBuilding Geometry
Meteorological Data
Terrain Data
AERMET
AERMAP
Operating Parameters AERMOD
OtherInputs
Building
Inputs
Traditional AERMOD Modeling
Approach
Compliance may
require taller
stacks and/or
additional
emission controls
Using Physical Modeling to Refine Downwash Inputs to AERMOD

4. Building Downwash
4 Using Physical Modeling to Refine Downwash Inputs to AERMOD
Image from Lakes Environmental Software

5. Building Profile Input Program
(BPIP)
Figure created in BREEZE ® Downwash Analyst
BREEZE is a registered Trademark of Trinity Consultants, Inc.
5 Using Physical Modeling to Refine Downwash Inputs to AERMOD

6. 6
PRIME
AERMOD’s Building Downwash Algorithm
• Used EPA wind tunnel data
base and past literature
• Developed analytical
equations for cavity height,
reattachment, streamline
angle, wind speed and
turbulence
• Developed for specific
building dimensions
• When buildings outside of
these dimensions, theory falls
apart
Using Physical Modeling to Refine Downwash Inputs to AERMOD

7. 7
Overprediction due to Building
Downwash
Using Physical Modeling to Refine Downwash Inputs to AERMOD

8. 8
AECOM Field Study at Mirant Power
Station (Shea et al., 2012)
Shea, D., O. Kostrova, A. MacNutt, R. Paine, D. Cramer, L. Labrie, “A Model Evaluation Study of AERMOD Using Wind Tunnel
and Ambient Measurements at Elevated Locations,” 100th Annual AWMA Conference, Pittsburgh, PA, June 2007.
• Model overpredicted by factor of
10 on residential tower
• Better agreement with EBD, but
still overpredicted by factor of 4
• Best agreement with no
buildings, still overpredicted by
factor of 2.
• In reality, plume is not affected
by building downwash.
Using Physical Modeling to Refine Downwash Inputs to AERMOD

9. What’s Causing These
Problems?
9 Using Physical Modeling to Refine Downwash Inputs to AERMOD
Petersen, R., Guerra, S., Bova, A., ”Critical Review of the Building Downwash Algorithms in
AERMOD”, Journal of the Air & Waste Management Association. Accepted author version:
http://www.tandfonline.com/doi/full/10.1080/10962247.2017.1279088

10. Long Buildings with Wind
at an Angle
Figure created in BREEZE® Downwash Analyst
BREEZE is a registered trademark of Trinity Consultants, Inc.
10 Using Physical Modeling to Refine Downwash Inputs to AERMOD

11. AERMOD Building Wake
AERMOD Overestimates Downwash
Hb = 20 m
Problem even worse for longer buildings
• Wake height
overestimated:
need higher plumes
to avoid downwash.
• Start of maximum
building downwash
farther downwind
than in reality
11 Using Physical Modeling to Refine Downwash Inputs to AERMOD

12. AERMOD/PRIME
Overestimates
Downwash
Reality
AERMOD Building Downwash
Height of Building Downwash Zone Overestimated in PRIME
12 Using Physical Modeling to Refine Downwash Inputs to AERMOD

13. Refinery Structures Upwind
- Horizontal Flow
Solid BPIP Structure Upwind
No Structures
Streamlines for Lattice Structures
Should be Horizontal
13 Using Physical Modeling to Refine Downwash Inputs to AERMOD

14. How to Minimize the Effect from
these Errors?
14 Using Physical Modeling to Refine Downwash Inputs to AERMOD

15. Solutions to Downwash Overpredictions
– Refine building dimensions with a wind tunnel
study
– Equivalent Building Dimensions (EBDs) are the
dimensions (height, width, length and location)
that are input into AERMOD in place of BPIP
dimensions to more accurately predict building
wake effects
– Guerra, S., Petersen, R. “Using Physical Modeling
to Refine Downwash Inputs to AERMOD”, EM
Magazine, October 2016
http://www.cppwind.com/wp-content/uploads/2016/10/Using-Physical-Modeling-to-
Refine-Downwash-Inputs-to-AERMOD_EMMag-Oct-16_PetersenGuerra.pdf
15 Using Physical Modeling to Refine Downwash Inputs to AERMOD

16. • Equivalent Building Dimensions (EBDs) are the dimensions (height, width, length
and location) that are input into AERMOD in place of BPIP dimensions to more
accurately predict building wake effects
• Guidance originally developed when ISC was the preferred model –
– EPA, 1994. Wind Tunnel Modeling Demonstration to Determine Equivalent
Building Dimensions for the Cape Industries Facility, Wilmington, North
Carolina. Joseph A. Tikvart Memorandum, dated July 25, 1994. U.S.
Environmental Protection Agency, Research Triangle Park, NC
– New guidance currently being developed with EPA
• Determined using wind tunnel modeling
EBD Method
16 Using Physical Modeling to Refine Downwash Inputs to AERMOD

17. BPIP Diagnostic Tool
http://www.cppwind.com/what-we-
do/air-permitting/bpip-diagnostic-tool#/
Likely Overprediction Factor for each Flow Vector
Source 1
17 Using Physical Modeling to Refine Downwash Inputs to AERMOD

18. 18
ComplianceCompliance
CPP’s EBDCPP’s EBD
BPIP Diagnostic
ToolBuilding Geometry
Meteorological Data
Terrain Data
AERMET
AERMAP
Operating Parameters
AERMOD
OtherInputs
Building
Inputs
BPIP Diagnostic Tool
Using Physical Modeling to Refine Downwash Inputs to AERMOD

19. 19
Summary of Approved Projects
• Studies conducted and approved using original guidance for ISC
applications
– Amoco Whiting Refinery, Region 5, 1990
– Public Service Electric & Gas, Region 2, 1993
– Cape Industries, Region 4, 1993
– Cambridge Electric Plant, Region 1, 1993
– District Energy, Region 5, 1993
– Hoechst Celanese Celco Plant, Region 3, 1994
– Pleasants Power, Region 3, 2002
• Studies conducted using original guidance for AERMOD/PRIME
applications
– Hawaiian Electric (Approved), Region 9, 1998
– Mirant Power Station (Approved), Region 3, 2006
– Cheswick Power Plant (Approved), Region 3, 2006
– Radback Energy (Protocol Approved), Region IX, 2010
– Chevron 1 (Study Approved), Region 4, 2012
– Chevron 2 (Study Approved), Region 4, 2013
– On going confidential study in Region X
– On going confidential study in Region X
Using Physical Modeling to Refine Downwash Inputs to AERMOD

20. 20 Using Physical Modeling to Refine Downwash Inputs to AERMOD
How to Use EBD for Regulatory Purposes?
Step 1: Develop a protocol outlining the EBD study
Step 2: Submit EBD protocol for approval to regulatory agency. Also need to
involve Model Clearinghouse
Step 3: Perform wind tunnel testing
Step 4: Use building geometry from EBD study in AERMOD to show compliance
Step 5: Submit final report for agency review and approval

21. General EBD Methodology
• Specify model operating
conditions
• Construct scale model
• Install model in wind tunnel and
measure concentrations
• Determine EBD
21 Using Physical Modeling to Refine Downwash Inputs to AERMOD

22. 22
Measure Ground-level Concentrations
Data taken until good fit and max obtained Automated Max GL Concentration Mapper
Using Physical Modeling to Refine Downwash Inputs to AERMOD

23. 23
Measure Ground-level Concentrations
With Site Structures Present
Tracer
from stack
Max ground-level concentrations measured versus x
Using Physical Modeling to Refine Downwash Inputs to AERMOD

24. 24
Measure Ground-level Concentrations with
Various EBD in Place of Site Structures
Tracer
from stack
Max ground-level concentrations measured versus x
Using Physical Modeling to Refine Downwash Inputs to AERMOD

25. 25
Measure Ground-level Concentrations with
no Structures
Tracer
from stack
Max ground-level concentrations measured versus x
Using Physical Modeling to Refine Downwash Inputs to AERMOD

26. 26
Specify Wind Tunnel Determined EBD that
Matches Dispersion with Site Structures Present
Wind
Tunnel EBD
much
smaller
than actual
building
No building
works best
for this
case
Site Structures in Wind TunnelEBD in Wind Tunnel
Using Physical Modeling to Refine Downwash Inputs to AERMOD

27. 27
Typical Result
Wind Tunnel EBD
Using Physical Modeling to Refine Downwash Inputs to AERMOD

28. 28
Downwash Based on EBD and BPIP
Figures created in BREEZE® Downwash Analyst
BREEZE is a registered trademark of Trinity Consultants, Inc.
Using Physical Modeling to Refine Downwash Inputs to AERMOD

29. 29 Using Physical Modeling to Refine Downwash Inputs to AERMOD
Potential Benefits from use of EBD

30. 30 Using Physical Modeling to Refine Downwash Inputs to AERMOD
Past CPP Project
Stack S_XXX From Industrial Facility
Stack height = 27 m
Q = 2 g/s
Building height = 17 m
Building width/length > 200 m
5 years of meteorological data
AERMOD Results With Wind
Tunnel EBD
wide/Long/Short Buildings
Description
AERMOD Maximum
Predicted
Concentration
(µg/m3)
Compliance
BPIP Building Dimension Inputs 258.2 No
Wind Tunnel Determined Building Inputs (EBD) 54.9 Yes
PM10 24-hr Standard 150

31. 31 Using Physical Modeling to Refine Downwash Inputs to AERMOD
AERMOD Results With Wind Tunnel EBD
Very wide/narrow building
Stack height: 47 m
Building height: 31 m
Property line in Red
Emission rate: 20 g/s
AERMOD RESULTS
Five years of met data Description
AERMOD Maximum
Predicted
Concentration
(µg/m3)
Compliance
BPIP Building
Dimension Inputs
303.8 No
Wind Tunnel
Determined Building
Inputs (EBD)
79.9 Yes
NO2 1-hr Standard 188

32. Sergio A. Guerra, PhD Ron Petersen, PhD, CCM
sguerra@cppwind.com rpetersen@cppwind.com
Mobile: + 612 584 9595 Mobile:+1 970 690 1344
CPP, Inc.
2400 Midpoint Drive, Suite 190
Fort Collins, CO 80525
+ 970 221 3371
www.cppwind.com @CPPWindExperts
Questions?
32 Using Physical Modeling to Refine Downwash Inputs to AERMOD