Presented at Community Modeling and Analysis System (CMAS) October 2006 Conference

Presents:/slides/1

Use of Advanced Probing Tools in One-Atmosphere Air Quality Models for Model

Evaluation, Culpability Assessment and Control Strategy Design

Presented at Community Modeling and Analysis System (CMAS)

October 2006 ConferenceChapel Hill, North Carolina

Ralph Morris, Bonyoung Koo, Gary Wilson & Greg Yarwood

ENVIRON International Corporation101 Rowland Way, Novato, CA. 94945

([email protected])Presents:slides/

Presents:/slides/2

Introduction• Photochemical grid models (e.g. CMAQ and CAMx) are

used to design emission control strategies to demonstrate attainment of the 8-hour ozone and PM2.5 standards

• Such models are quite complex with full-science representation of transport and diffusion, gas-, aqueous- and aerosol-phase chemistry, cloud processes, gas/particle deposition etc.

• It is difficult and computationally intensive to diagnose why the model obtained its solution, what corrective action is needed to improve model performance and which sources contributed to the high concentrations

Presents:/slides/3

Probing Tools• Both CMAQ and CAMx incorporate “Probing

Tools” that extract additional information:– Process Analysis (PA)

• Identify the chemical processes in the simulation• Perform mass flux closure analysis

– Decoupled Direct Method (DDM)• Sensitivity to emissions categories and regions, BCs,

etc.

– Source Apportionment (SA)• Identify source regions/categories that contribute to

ozone, PM, etc.

Presents:/slides/4

What is a Probing Tool?

Probe verb, probed, prob ing, noun ‧1. to search into or examine thoroughly; question

closely

2. to examine or explore with a probe

3. to examine or explore with or as if with a probe

4. a slender surgical instrument for exploring the depth or direction of a wound, sinus, or the like

5. an investigation, esp. by a legislative committee, of suspected illegal activity.

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Alien Probing

Presents:/slides/6

Process Analysis (PA)• Pioneered out at research group at UNC Chapel Hill

– Chemical PA; Mass Flux (IPRs, IRRs)

• Extensively used for ozone– E.g., identification of VOC- vs. NOx-limited ozone

formation regimes in Houston (Jeffries et, al)– pyPA and pyPASS visualization tools (Vizuete et al.;

http://www.unc.edu/~vizuete/research.htm)

• Recently extended to PM modules in CAMx (CRC Project A-51b, Tonnesen et al., 2006)– Inorganic Aerosol, Organic Aerosol and Aqueous-Phase

Chemistry (http://www.crcao.com)

Presents:/slides/7

Decoupled Direct Method (DDM)• Sensitivity of modeled concentrations to input

parameters– Primarily used for emissions– Georgia Institute of Technology (GIT) implemented 3-D

DDM in CMAQ (URM)• Has assisted in the identification of control strategies (e.g., GIT

SAMI analysis)

– DDM recently extended to PM modules in CAMx (CRC Project A-51a, Koo et al., 2006; http://www.crcao.com)

• Used for inverse modeling to identify potential areas of missing emissions (e.g., Houston ship channel VOC emissions)

Presents:/slides/8

Source Apportionment (SA)• CMAQ

– Tagged Species Source Apportionment (TSSA; UCR)• Implemented for SO4 and NO3 families

– Particle and Precursors Tagging Methodology (PPTM; SAI)

• CAMx– Ozone Source Apportionment Technology (OSAT)

• Used extensively for source culpability and optimal control strategy identification (e.g., NOx SIP Call; CAIR; Ozone SIPs)

– PM Source Apportionment Technology (PSAT)• Just beginning to be used, examples follow

Presents:/slides/9

PM Source Apportionment for WRAP (Western United States for Visibility)

• WRAP Applied CAMx/PSAT and CMAQ/TSSA PM Source Apportionment to WUSA– Identify source categories and states that contribute

to visibility impairment at western US Class I areas– PSAT results available on WRAP RMC and TSS

websites:• http://pah.cert.ucr.edu/aqm/308/cmaq.shtml• http://vista.cira.colostate.edu/tss/Default.aspx?code=1

Presents:/slides/10

WRAP PSAT/TSSA PM SA Source Groups

16 Source Regions

6 Source Categories

= 98 Source Groups

MV_ Mobile SourcesPT_ Point SourcesAR_ Area SourcesANF_ Anthro FiresNTWF_ Nat FiresNWF_ Non-WRAP firesAE_ Area+ Sources

Presents:/slides/11

2002 Ranked SO4 Contributions for W20% Days

1. AR Offshore

2. PT Offshore

3. BCON

4. PT CA

5. MV CA

6. AR CA

7. AR MX

8. PT MX

Presents:/slides/12

2002 2018

2002 vs. 2018 SO4 SA Agua Tibia, CA

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20182002

2002 vs. 2018 NO3 SA Agua Tibia, CA

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PM Source Apportionment for CENRAP

• Regional Haze Rule (RHR) requires States to demonstrate Reasonable Progress toward clean visibility conditions in 2064– Modeled 2018 visibility projections compared with

Uniform Rate of Progress (URP) goal obtained by linear Glide Path from current (2000-2004) Worst 20% conditions to 2064 Natural Conditions

– Modeled URP goal can be important component of a State’s Reasonable Progress demonstration in their December 2007 RHR SIP

Presents:/slides/15

23.0622.26

20.26

18.26

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14.27

12.2711.07

20.36

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17.10 16.4214.73

13.0311.34

9.647.95

6.93

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Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction

Wichita Mtn, OK – Meets URP Goal

Big Bend, TX – Does Not Meet UP Goal

Why WIMO,

OK meets UP goal

but BIBE, TX does

not?

Use SA to identify source

regions and categories

that contribute to visibility on W20%

days

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-2000

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22 Separate States; rest of West and East US; Canada; Mexico GulfMex ; IC; & BC

Geographic Source Apportionment; 27 Regions

* WIMO

* BIBE

Presents:/slides/17

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BIBE1 GICL1 GUMO1 WIMO1

SOA_B & SOA_A All Sources BCs (Global Transport) Mexico

CENRAP

VISTAS + MANE-VU

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MN IA NE MO KS AK OK LA TX ND SD

WY CO NM West WI IL MI IN KY TN MS

AL East CANADA MEXICO Gulf of MX IC BC SO_Anthro SO_Biog

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Contribution to Visibility Impairment (Mm-1) for W20% Days at Wichita Mtn, OK in 2018

~20% visibility extinction at WIMO due to uncontrollable sources: Mex, Can, BC and SOA_B

Presents:/slides/18

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SOA_B & SOA_A All Sources

BCs (Global Transport)

Mexico

CENRAP States (Texas largest)

~60% of visibility extinction on average of Worst 20% Days due to international

transport

Contribution to Visibility Impairment (Mm-1) for W20% Days at Big Bend, TX in 2018

Presents:/slides/19

Wichita Mtns Oklahoma

Total Visibility Bext

Presents:/slides/20

SO4 Visibility Bext

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NO3 Visibility Bext

Presents:/slides/22

Which Regional AQ Model is Used the Most for Regulatory Decision Making

• CMAQ? CAMx?• UAM? URM? CIT? STEM? REMSAD?

– None of the above – CALPUFF!– CALPUFF SO4 & NOx “chemistry”

– SO4:

– NO3:

k1 = 36 x R0.55 x [O3]0.71 x S-1.29 + k1(aq)

k1(aq) = 3 x 10-8 x RH4 (added to k1 above during the day) k2 = 1206 x [O3]

1.5 x S-1.41 x [NOx]-0.33 k3 = 1261 x [O3]

1.45 x S-1.34 x [NOx]-0.12

CALPUFF recommended long-range transport model

Presents:/slides/23

Photochemical Grid Models (PGMs) Not Used due to Perception they are Too Costly, Difficult and Fail to Treat Plumes

• Development of PGM modeling databases costly– RPOs/EPA developed canned 36/12 km databases for 2001&2002

• Application of PGMs requires expertise– With databases available applications easier and available of Linux

boxes make them easy and cheaper to apply• PGM resolution limited by grid cell size

– New Plume-in-Grid modules treat near-source chemistry and plume dynamics (PinG & APT in CMAQ; PiG in CAMx)

– two-way grid nesting can treat near- to far-field plume resolution• Need 2 runs to get a single source impact

– PM Source Apportionment allows separate tracking of PM impacts from individual sources within one run (TSSA & PPTM in CMAQ; PSAT in CAMx)

Presents:/slides/24

PGM resolution limited by grid cell size:Plume-in-Grid (PiG) and Two-Way Grid Nesting

• Plume-in-Grid (PinG/APT/PiG)– Treats near-source plume chemistry and plume

dynamics using a Lagrangian puff module– When puff size is commensurate with grid cell

resolution, mass in puff is released for further tracking

• Two-Way Grid Nesting– Flexi-nesting allows specification of higher

resolution grids without need for other inputs for better resolution of point source plumes

Presents:/slides/25

Texas BART Point Source Screening Analysis

• Use of CAMx PGM to perform group BART screening exemption modeling– PM Source Apportionment Technology (PSAT) to

obtained source-specific visibility impact at Class I areas from BART Sources

– Two-way 36/12 km grid nesting to better resolve fair-field impacts

– Use of Plume-in-Grid (PiG) with PSAT to resolve near-source plume chemistry and plume dynamics

• Provides full-science chemistry from plume- to regional-scale within 3-D PGM framework

Presents:/slides/26-2736 -1872 -1008 -144 720 1584 2448

-2088

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-792

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504

936

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CENRAP 36 km Domain with Texas 12 km Flexi-Nest Grid

Add 12km grid using flexi-nest

Presents:/slides/27

-936 -816 -696 -576 -456 -336 -216 -96 24 144 264 384 504

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Texas 12 km Flexi-Nest Domain

IMPROVE monitors (circles)

Potential BART-eligible Sources

(triangles)

Treat emissions from BART

sources with PSAT and PiG

Presents:/slides/28

Conclusions: Hybrid PGMs for BART/PSD• Current generation of hybrid PGMs with grid

nesting, Plume-in-Grid and PM Source Apportionment able to treat single source PM, ozone and visibility impacts at all scales– Use of full chemistry– Accounts for three-dimensional winds/dispersion

• Available databases = Ease of use• Better science will result in more accurate and

reliable assessments• Texas BART modeling demonstration:

http://www.tceq.state.tx.us/implementation/air/sip/bart/haze.html

Documents

Presented at Community Modeling and Analysis System (CMAS) October 2006 Conference