PRIME2: Consequence Analysis and Model Evaluation

PRIME2 Consequence Analysis
and Model Evaluation
Pacific Northwest International
Section of the A&WMA
2017 Annual Conference
Boise, ID.
Sergio A. Guerra, PhD
Ron Petersen, PhD, CCM
November 3, 20171

Outline
1. Background on PRIME2
2. Consequence Analysis
3. Field Evaluation
4. Case studies
2 PRIME2 Consequence Analysis and Model Evaluation

3
Key Features of PRIME2
• Building wake effects decay rapidly back to ambient levels above the
top of the building versus the current theory that has these effects
extending up to 3 building heights.
• Lateral dispersion enhancement in the wake is less than vertical
dispersion enhancement (current PRIME has them identical).
• The approach turbulence and wind speed is calculated at a more
appropriate height versus the current theory where half the wake
height at 15 building heights downwind of the building is used.
• Wake effects for streamlined structures are reduced.
• Wake effects decrease as approach roughness increases.
PRIME2 Consequence Analysis and Model Evaluation

4
Project Summary
• Wind tunnel testing was performed to evaluate downwash effects from
rectangular and streamlined structures.
• CPP developed equations for predicting wind speed and turbulence in
building wakes for rectangular and streamlined structures based on wind
tunnel observations.
• CPP’s updates were compiled into a new AERMOD executable (PRIME2).
• Field versus model comparisons show that PRIME2 predictions are
generally within a factor of two of field observations but have a
overprediction tendency. Predictions also tend to be higher values than
with PRIME.
• Other theoretical problems have been identified. Correcting these may
alleviate the current overprediction tendency in PRIME2.
PRIME2 Consequence Analysis and Model Evaluation

Implementation Process
CPP and ORD
Submittals to
EPA OAQPS
Journal
Articles
Published
OAQPS Codes
CPP and ORD
Enhancements
EPA releases
New PRIME
as Alpha
option
EPA
releases
PRIME as
Beta
option
Notice of
proposed
rulemaking
(NPRM)
New PRIME
is released
as default
regulatory
option
Alpha option needs to meet the alternative refined model requirements in App W, Section 3.2.2
before it can become a Beta option. These requirements include:
1-Model has received a scientific peer review;
2-Model can be demonstrated to be applicable to the problem on a theoretical basis;
3-The data bases to perform analysis are available and adequate;
4-Appropriate performance evaluations show model is not biased toward underestimation; and
5-A protocol on methods and procedures to be followed has been established

Consequence Analysis
PRIME2 Consequence Analysis and Model Evaluation6

PRIME2_v17234a Evaluation
1:10:10 BDG with MakeMet Hs=1.2Hb
PRIME2_v17234a2
AERMOD_v16216r
zo=2cm zo=25cm zo=100cm
Max=173.0 ug/m3
Max=73.5 ug/m3
Max=132.9 ug/m3
Max=72.2 ug/m3 Max=79.0 ug/m3
Max=70.9 ug/m3

PRIME2_v17234a2
AERMOD_v16216r
Max=130.1 ug/m3 Max=97.0 ug/m3 Max=53.2 ug/m3

PRIME2_v17234a2
AERMOD_v16216r

Bowline Point BDGs with Bowline Met Data
PRIME2_v17234a2
AERMOD_v16216r
Hs=1.33Hb=87.8m Hs=1.80Hb=117.4m Hs=2.50Hb=163.1m
Max=1013.1 ug/m3
Max=638.3 ug/m3 Max=279.9 ug/m3
Max=279.9 ug/m3
Max=192.2 ug/m3
Max=192.2 ug/m3
Max Observed = 823.5 ug/m3

Field Evaluation

Bowline Point Field Evaluation for Receptors 1 and 3
Q-Q Plot of Predicted vs. Observed Concs. with BPIP Values
Model Version
Top 25 Mean
X obs
Top 25 Mean
X predict
Top 25
Pre/Obs
Fractional
Bias
R1&3 AERMODv16216r (ug/m3) 422.17 447.71 1.06 0.06
R1&3 PRIME2v17234a (ug/m3) 422.17 684.51 1.62 0.47

Refined BPIP Method Example
Bowline Point

Refined BPIP Method Example: Bowline Point
Merged Tiers
Building
Dimensions
BPIP
(m)
Updated BPIP
(m)
Building Height(Hb) 65.23 65.23
Building Width (W) 121.95 121.95
Building Length (L) 109.93 35.98
XBADJ -127.62 -97.20
YBADJ -2.47 -2.5
Assumption 1:
Tallest tiers combine
(green bdg)
Assumption 2:
BDG WIDTH (W) is
crosswind width of
merged tier.
Assumption 3:
XBADJ starts at the
upwind edge of the
merged tier
Assumption 4:
BDG LENGTH (L) is
calculated by dividing
the area of the
merged tier by W

Refined BPIP Method Example: Bowline Point
Unmerged Tiers
Building
Dimensions
BPIP
(m)
Updated BPIP
(m)
XBADJ -132.56 -127.90
YBADJ -27.17 -4.0
Assumption 1:
Tallest tiers do not
combine (green bdg)
Assumption 2:
BDG WIDTH (W) is
crosswind width of
unmerged tier.
Assumption 3:
XBADJ starts at the
upwind edge of the
tallest tier
Assumption 4:
BDG LENGTH (L) is
calculated by dividing
the area of the tallest
tier by W

Model Version
Top 25 Mean
X obs
Top 25 Mean
X predict
Top 25
Pre/Obs
Fractional
Bias
R1&3 AERMODv16216r (ug/m3) 422.17 447.71 1.06 0.06
R1&3 PRIME2v17234a (ug/m3) 422.17 684.51 1.62 0.47

Model Version
Top 25 Mean
X obs
Top 25 Mean
X predict
Top 25
Pre/Obs
Fractional
Bias
R1&3 AERMODv16216r (ug/m3) 422.17 237.67 0.56 -0.56
R1&3 PRIME2v17234a (ug/m3) 422.17 535.01 1.27 0.24
Q-Q Plot of Predicted vs. Observed Concs. with Modified BPIP Values

Refined BPIP Method Example
Alaska North Slope

Model Version
Top 25 Mean
X obs
Top 25 Mean
X predict
Top 25
Pre/Obs
Fractional Bias
AERMODv16216r 3.13 3.59 1.15 0.137
PRIME2_17234 3.13 7.58 2.42 0.829
Alaska North Slope Field Evaluation

Building
Dimensions
BPIP
(m)
Updated BPIP
(m)
XBADJ -45.24 -43.70
YBADJ 6.58 6.6
Assumption 1:
Tallest tier combine
(green bdg)
Assumption 2:
BDG WIDTH (W) is
crosswind width of
merged tier.
Assumption 2:
XBADJ starts at the
lee edge of the
merged tier
Assumption 3:
YBADJ is calculated
by dividing the area
of the merged tier by
the width of the
artificially created
building
Refined BPIP Method Example: Alaska North Slope
Merged Tiers

Building
Dimensions
BPIP
(m)
Updated BPIP
(m)
XBADJ -28.7 -28.6
YBADJ -11.79 4.8
Assumption 1:
Tallest tier do not
combine (green bdg)
Assumption 2:
XBADJ starts at the
lee edge of the
merged tier
Assumption 3:
YBADJ is calculated
by dividing the area
of the merged tier by
the width of the
artificially created
building
Refined BPIP Method Example: Alaska North Slope
Unmerged Tiers

Model Version
Top 25 Mean
X obs
Top 25 Mean
X predict
Top 25
Pre/Obs
Fractional Bias
AERMODv16216r 3.13 3.59 1.15 0.137
PRIME2_17234 3.13 7.58 2.42 0.829

Model Version
Top 25 Mean
X obs
Top 25 Mean
X predict
Top 25
Pre/Obs
Fractional Bias
AERMODv16216r 3.13 2.78 0.89 -0.120
PRIME2_17234 3.13 6.14 1.96 0.648
Q-Q Plot of Predicted vs. Observed Concs. with Modified BPIP Values

Alaska North Slope: Observed Values
Max: 5.29 µg/m3

Alaska North Slope: AERMODv16216r
Max: 4.48 µg/m3

Alaska North Slope: PRIME2v17234a
Max: 13.20 µg/m3

What Could be Causing Higher PRIME2 Predictions?
• BPIP Building Dimensions Inputs: Building length and upwind and
downwind faces not defined correctly.
• Streamlines: Need to be reviewed and updated as necessary.
• The wind speed used to calculate concentrations. Currently PRIME
and PRIME2 are using the stack height wind speed.

Case Study Comparison

BPIP Values: AERMODv16216r
H1H 24-hr avg = 78.9ug/m3

BPIP Values: PRIME2_17234a2

EBD Values: AERMODv16216r

Conclusions
• PRIME2 includes a superior theory to account for building
downwash effects for rectangular and streamlined structures.
• Benefits from improved theory cannot be fully realized due to
outstanding issues in the model.
• Work from EPA ORD complements the work performed by
CPP.
• Plan is to continue EPA collaboration to address model
improvements to AERMOD related to building downwash.

Sergio A. Guerra, PhD Ron Petersen, PhD, CCM
sguerra@cppwind.com rpetersen@cppwind.com
Mobile: + 612 584 9595 Mobile:+1 970 690 1344
wwww.SergioAGuerra.com
CPP, Inc.
2400 Midpoint Drive, Suite 190
Fort Collins, CO 80525
+ 970 221 3371
www.cppwind.com @CPPWindExperts
Questions?

PRIME2: Consequence Analysis and Model Evaluation

Recommandé

Recommandé

Contenu connexe

Tendances

Tendances (20)

Similaire à PRIME2: Consequence Analysis and Model Evaluation

Similaire à PRIME2: Consequence Analysis and Model Evaluation (20)

Plus de Sergio A. Guerra

Plus de Sergio A. Guerra (6)

Dernier

Dernier (20)

PRIME2: Consequence Analysis and Model Evaluation