Overview of other rpo modeling work
Download
1 / 38

Overview of Other RPO Modeling Work - PowerPoint PPT Presentation


  • 110 Views
  • Uploaded on

Ralph Morris ENVIRON International Corporation Joint Modeling Forum and Attribution of Haze Workgroup Meeting San Diego, California November 2, 2006. Overview of Other RPO Modeling Work. CENRAP ENVIRON and UCR MRPO LADCO w/ assistance from contractors VISTAS ENVIRON, UCR and Alpine

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about ' Overview of Other RPO Modeling Work' - audra


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
Overview of other rpo modeling work

Ralph Morris

ENVIRON International Corporation

Joint Modeling Forum and Attribution of Haze Workgroup Meeting

San Diego, California

November 2, 2006

Overview of Other RPO Modeling Work


Other rpo modeling

CENRAP

ENVIRON and UCR

MRPO

LADCO w/ assistance from contractors

VISTAS

ENVIRON, UCR and Alpine

MANE-VU

NESCAUM, OTC, MARAMA, States

Other RPO Modeling


Cenrap update

2002 Actual Base Case

MPE CMAQ and CAMx @ 36 km

2002 Typical Base Case (Base F latest)

2018 Base E2 Emissions and CMAQ

Working on 2018 Base F

Preliminary 2018 CAMx/PSAT runs

Identify contributions of International Transport

How to work into Reasonable Progress

2018 Base E2 Visibility Projections

Comparisons with WRAP, MRPO and VISTAS

2018 Base F visibility projections ongoing

Ready in about 4 weeks

CENRAP Update


Treatment of International Transport

  • Modeled Uniform Rate of Progress (URP) test compares against 2018 Goal from Glide Slope 2000-2004 Baseline to 2064 Natural Conditions

    • Modeled 2018 visibility projection includes contributions from International Transport and Natural Sources that are not completely accounted for in 2064 Natural Conditions

    • Regional Haze Rule goal is no man-made visibility impairment in 2064

      • For demonstrating Reasonable Progress does this just apply to US man-made (controllable) sources?

  • CENRAP Visibility Projections found Class I areas on US international border fail to meet URP goal

    • How to treat International Transport in modeled URP test?


How to Treat International Transport in Reasonable Progress

  • Approach 1: Include International Transport with the 2064 Natural Conditions Goal

    • Can use different estimates of International Transport (GEOS-CHEM, PSAT, etc.)

    • Simple to implement

    • Keeps Glide Slope in deciview

    • Inconsistent with Regional Haze Rule 2064 Natural Conditions goal?

    • Not liked by FLMs


How to Treat International Transport in Reasonable Progress

  • Approach 2: Define 2064 goal as Elimination of U.S. Anthropogenic Emissions Contribution to Visibility Impairment

    • Interpretation of the “no man-made impairment” as U.S. man-made impairment

    • Need approach to track U.S. anthropogenic contribution

    • 2064 goal is zero

    • Must use Extinction (Mm-1) to calculate


Intl Transport & Reasonable Progress

  • Approach 3: Adjust modeled 2018 visibility projection to account for International Transport (FLM suggestion)

    • Consistent with Regional Haze Rule

    • How and what to do?

      • (3A) Assume International Transport component is reduced same amount as U.S. anthropogenic emissions component

        • If International Transport is above and beyond Natural Conditions then this seems reasonable

        • Can keep deciview

        • Promotes fairness across States with Class I areas in center versus border of U.S.

      • (3B) Other???


CENRAP PM Source Apportionment

  • PM Source Apportionment Technology (PSAT)

  • 2018 Base D CAMx Database

  • State Level Geographic Regions

    • CENRAP and Adjacent States

  • Track Three Families

    • SO4; NO3 & Primary PM [No SOA or Hg]

  • Use standard model output to split SOA into anthropogenic and biogenic SOA (SOA_A & SOA_B)

    • No geographic source apportionment for SOA



Geographic PSAT GulfMex ; IC; & BC

  • 2018 Base D Emissions Scenario

  • Class I areas for W20% Days

  • Convert to Extinction (Bext) and determine State’s contribution to Visibility Impairment on Worst 20%

    • Can also partition by RPO and split International vs. U.S. Sources

    • Only geographic Source Apportionment at this time

      • Can not Separate Natural from Anthropogenic U.S. (except for SOA_B)


Wichita Mountains, Oklahoma Visibility Extinction (Mm GulfMex ; IC; & BC-1) Source Apportionment for the Worst 20% Days

70

 SOA_B & SOA_A All Sources

 BCs (Global Transport)

 Mexico

 VISTAS + MANE-VU

 CENRAP


 SOA_B & SOA_A All Sources GulfMex ; IC; & BC

 BCs (Global Transport)

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

 Mexico

 CENRAP States (Texas largest)

Big Bend National Park, Texas Visibility Extinction Apportionment Worst 20% Days


22% due to non-US Anthro Sources GulfMex ; IC; & BC

Wichita Mtns Oklahoma

Bext


24% due to non-US Sources GulfMex ; IC; & BC

BSO4


13% due to non-US Sources GulfMex ; IC; & BC

BNO3


International Transport Methods GulfMex ; IC; & BC

  • Use PM Source Apportionment Technology (PSAT) to separately track contributions due to International Transport

    • Initial results for 2018 Base D

  • Zero-Out GEOS-CHEM global chemistry model (eliminate U.S. sources or eliminate International sources)

    • Initial results from EPRI study with Harvard

  • Two “independent” approaches for estimating contributions of International Transport to PM concentrations at Class I areas.

    • How do PSAT and GEOS-CHEM results compare?


CAMx/PSAT GulfMex ; IC; & BC

Sulfate (SO4) Annual Average International Transport by CAMx/PSAT and GEOS-CHEM models

Excellent to Good Agreement of Two Methods

Not truly “independent” evaluation since CAMx/PSAT runs used GEOS-CHEM BCs, but results encouraging

GEOS-CHEM


CAMx/PSAT GulfMex ; IC; & BC

Organic Carbon Mass (OCM) Annual Average International Transport by CAMx/PSAT and GEOS-CHEM models

Reasonably Good Agreement of Two Methods, As much as a Factor of Two Different (LYBR), but most fairly close

Larger differences in OCM. CAMx/PSAT includes OCM from Biogenic Sources so expected to be higher, but frequently lower?

GEOS-CHEM


CAMx/PSAT GulfMex ; IC; & BC

Elemental Carbon (EC) Annual Average International Transport by CAMx/PSAT and GEOS-CHEM models

Differences in fires may be affecting results. Large Quebec fires in 2002 affect CAMx/PSAT. Mex fires in GEOS-CHEM?

GEOS-CHEM


Accounting for International Transport GulfMex ; IC; & BC

  • Run PSAT for 2002 and 2018 separating controllable and uncontrollable (or US vs. International Transport) components

    • Approach 1: Add “International Transport” component to Natural Conditions for 2064 goal and redefine 2018 URP goal from 2000-2004 Baseline to new 2064 goal (in deciviews)

    • Approach 2: Redefine URP goal based on Controllable haze only. 2064 endpoint would be zero (no man-made impairment)

  • Examples of these approaches using current 2018 PSAT run follows

    • International Transport = Uncontrollable = Mex+Can+BCs+SOA_B


Big Bend: GulfMex ; IC; & BCStandard URP Calculation = 31% of URP goal


Big Bend: GulfMex ; IC; & BCApproach 1 IntlTrans in 2064 Natural Conditions = 62%


Big Bend: GulfMex ; IC; & BCApproach 2 URP Based on Controllable Haze = 31%


Big Bend Example GulfMex ; IC; & BC

  • Standard URP = 31%

  • Intl Trans in 2064 = 62%

  • Controllable URP = 31% (???)

    • Could not do this correctly since only had geographic PSAT for 2018 and natural emissions were included in US portion

      • Also need 2002 source apportionment

      • CENRAP intends to correct this with Base F modeling


CENRAP PSAT Next Steps GulfMex ; IC; & BC

  • International Transport and Natural Conditions Analysis combined with Control Strategy Design Analysis

    • Source Regions: CENRAP States and Nearby WRAP, MRPO and VISTAS States

    • Source Categories: EGU, Non-EGU Point, On-Road Mobile; Off-Road Mobile; Natural Emissions (Biogenics, Wildfires, Non-Ag WBD); Remaining Anthropogenic (e.g., area, Ag WBD)

    • 2002 and 2018 Base Case emissions


Cenrap psat source regions
CENRAP PSAT Source Regions GulfMex ; IC; & BC


Midwest rpo modeling

MM5 Meteorology GulfMex ; IC; & BC

2001, 2002, 2003 36-km for regional haze & PM2.5

2002 12-km for 8-hour ozone

EMS Emissions (Base K)

Starting to Migrate to CONCEPT

CAMx Air Quality Model

CMAQ may be used for corroborative analysis

Update model for SOA treatment

Using PSAT and OSAT

Aggressive Movement to 2005 Modeling Year

Driven by 8-hour ozone and PM25 issues

Midwest RPO Modeling


Midwest rpo soa updates

Update Biogenic Emissions Model to MEGAN and Generate all SOA precursor Species

E.g., sesquiterpenes

Update CAMx SOA Module

Treat new SOA precursors

Separate emissions for SOA species from gas-phase chemistry species

Slightly different than VISTAS SOAmods update that is plug and play with current biogenic emissions

Considering directly emit Condensable Gases (CG) from mobile sources

Midwest RPO SOA Updates


Midwest rpo controls

Need to address 8-hr ozone and PM2.5 as well as regional haze

BART for non-EGUs

Beyond CAIR scenario for EGUs

Fuel scenarios for urban ozone/PM2.5

Combined with Northeast to look at regional diesel retrofit controls

Midwest RPO Controls


Vistas modeling

2002 36/12 km MM5 haze

SMOKE 36/12 km

CMAQ 2002 36/12 km

Looked at CAMx early on but dropped due to resource and time constraints

Led to addition of biogenic SOA treatment

Just finished Base G (final) Modeling

2009 8-hour ozone and PM25 projections under ASIP

Visibility projections 36-km vs. 12-km similar

Using both 36 km and 12 km grid for 2009 and 2018 projections

VISTAS Modeling


2018 Base G Visibility Projections haze

  • 2018 36/12 km Base G OTB Base Case

    • With CAIR but Without BART

  • New and Old IMPROVE equation

    • New Natural Conditions for New IMPROVE from VIEWS

  • Previously presented preliminary 2018 36 km Base G visibility projections

    • Data substitution updates since then


Data Substitution Updates haze

  • New data substitution database received from ARS on October 19, 2006

    • Add one more site (CADI1) to New IMPROVE equation database

      • Old IMPROVE still not supporting CADI1

    • Update MING1 with latest data from UC Davis

    • Other minor updates (BRET1, etc.)

  • Always use newest data when available

    • Still using old substitution data for CHAS1 as missing data in 2003 & 2004 not in new database

  • Display using “DotPlots”, percentage of achieving 2018 URP goal


CMAQ 2018g1a/Typ02g Method 1 predictions for VISTAS+ sites haze

200%

CMAQ New IMPROVE Algorithm 12km

CMAQ Old IMPROVE Algorithm 12km

180%

CMAQ New IMPROVE Algorithm 36km

CMAQ Old IMPROVE Algorithm 36km

160%

140%

120%

Percent of target reduction achieved

100%

80%

60%

40%

20%

0%

JARI1

SIPS1

LIGO1

CADI1

BRIG1

MING1

BRET1

OKEF1

HEGL1

EVER1

SHEN1

CHAS1

UPBU1

CACR1

SAMA1

SHRO1

MACA1

DOSO1

COHU1

GRSM1

ROMA1

SWAN1

VISTAS

non-VISTAS


Comparison of VISTAS 2018 36/12 km Base G New/Old IMPROVE projections with CENRAP 36 km New/Old and MRPO 36 km Old IMPROVE projections

CMAQ Method 1 predictions for VISTAS+ sites Across RPOs

VISTAS New Algo 12km (baseG)

200%

VISTAS Old Algo 12km (baseG)

VISTAS New Algo 36km (baseG)

180%

VISTAS Old Algo 36km (baseG)

CENRAP New Algo 36km (18e2 SOA)

CENRAP Old Algo 36km (18e2 SOA)

160%

MwRPO Old Algo 36km (R4s1a)

140%

120%

Percent of target reduction achieved

100%

80%

60%

CENRAP/MRPO Visibility Projections Now Much More Consistent with VISTAS

40%

20%

0%

JARI1

LIGO1

CADI1

SIPS1

CACR1

HEGL1

OKEF1

COHU1

SHRO1

DOSO1

CHAS1

EVER1

SHEN1

MACA1

GRSM1

ROMA1

SAMA1

SWAN1

BRIG1

MING1

BRET1

UPBU1


Likely to meet projections with CENRAP 36 km New/Old and MRPO 36 km Old IMPROVE projections(>110%)

May meet (90-110%)

Likely not meet (<90%)

VISTAS 2018 Base G Uniform Rate of Progress Assessment

Using New IMPROVE equation to calculate visibility

.

.

Hercules Glade, MO

.

.

.

.

.


Vistas next steps

QA/QC of 2009 and 2018 projections projections with CENRAP 36 km New/Old and MRPO 36 km Old IMPROVE projections

Area of Influence (AOI) analysis

Identify sources within AOI

BART control definitions

2018 strategy runs and projections

States perform local PM2.5 and 8-hour ozone modeling

VISTAS Next Steps


Mane vu modeling

NESCAUM, OTC, MARAMA, UMD, States mainly in-house analysis projections with CENRAP 36 km New/Old and MRPO 36 km Old IMPROVE projections

Contribution Report – look at various methods for where PM came from

Back Trajectories -- Residence Time

PMF Receptor Modeling

REMSAD Tagged Species

CMAQ

Joint study with MRPO on regional diesel retrofit controls

MANE-VU Modeling


Potential effects on wrap

2018 visibility projections across RPOs starting to converge projections with CENRAP 36 km New/Old and MRPO 36 km Old IMPROVE projections

WRAP may want to consider processing existing WRAP 2002/2018 PSAT results to look at International Transport/Natural Emissions issues at WRAP Class I areas

CENRAP 2018 visibility projections consistent with WRAP

Potential Effects on WRAP


ad