Technical

Support Document

for the Modeling

Portions

of the District

Of Columbia’s Regional

Haze
State Implementation

Plan (SIP) Entitled “District

of Columbia Regional

Haze State Implementation

Plan (SIP) October

2011” TSD Prepared November,

2011 Todd

A. Ellsworth Office

of Air Monitoring

and Analysis,

3AP40 U.S. Environmental

Protection

Agency,

Region

3 1650 Arch Street Philadelphia, Pennsylvania

19103 ZZ 2— Reviewed

by Andrew

Hass, Acting Associate
Director, Office

of Air Monitoring

and Analysis (3AP40) /1/7

//( Date Signed

1Technical

Support Document

for the Modeling
Portions

of the District

of Columbia’s

Regional

Haze
State Implementation

Plan (SIP) Entitled “District

of Columbia Regional

Haze State Implementation

Plan (SIP) October

2011” Purpose

of the Technical

Support DocumentThisTechnicalSupportDocument(TSD)describesthçEnvironmentalProtectionAgency’s(EPA’s)evaluationofthemodelingportionsoftheDistrictofColumbia’s(D.C.)StateImplementationPlan(SIP)revisionentitled“DistrictofColumbiaRegionalHazeStateImplementationPlan(SIP)RevisedSeptember2011”.ThisSIPrevisionwillhereafterbereferredtoastheD.C.HazeSIP.ThepurposeofthisTSDistoprovidemoredetailedinformationthancanbecontainedintheofficialnoticepublishedintheFederalRegister.ReaderswhoneedmoreinformationthanweprovideinthisTSDorwanttoreviewthemodelinginmoredetailshouldreadtheabovereferencedD.C.HazeSIP. The Regulatory FrameworkInsection169A(a)(1)ofthe1977AmendmentstotheCAA,Congresscreatedaprogramforprotectingvisibilityinthenation’snationalparksandwildernessareas.ThissectionoftheCAAestablishesasanationalgoalthe“preventionofanyfuture,andtheremedyingofanyexisting,impairmentofvisibilityinmandatoryClassIFederalareas1whichimpairmentresultsfrommanmadeairpollution.”OnDecember2,1980,EPApromulgatedregulationstoaddressvisibilityimpairmentinClassIareasthatis“reasonablyattributable”toasinglesourceorsmallgroupofsources,i.e.,“reasonablyattributablevisibilityimpairment”(RAVI).See45FR80084.Theseregulationsrepresentedthefirstphaseinaddressingvisibilityimpairment.EPAdeferredactiononregionalhazethatemanatesfromavarietyofsourcesuntilmonitoring,modelingandscientificknowledgeabouttherelationshipsbetweenpollutantsandvisibilityimpairmentwereimproved.‘AreasdesignatedasmandatoryClassIFederalareasconsistofnationalparksexceeding6000acres,wildernessareasandnationalmemorialparksexceeding5000acres,andallinternationalparksthatwereinexistenceonAugust7,1977(42U.S.C.7472(a)).Inaccordancewithsection169AoftheCAA,EPA,inconsultationwiththeDepartmentofInterior,promulgatedalistof156areaswherevisibilityisidentifiedasanimportantvalue(see44FR69122,November30,1979).TheextentofamandatoryClassIareaincludessubsequentchangesinboundaries,suchasparkexpansions(42U.S.C.7472(a)).AlthoughstatesandtribesmaydesignateasClassIadditionalareaswhichtheyconsidertohavevisibilityasanimportantvalue,therequirementsofthevisibilityprogramsetforthinsection169AoftheCAAapplyonlyto“mandatoryClassIFederalareas.”EachmandatoryClassIFederalareaistheresponsibilityofa“FederalLandManager”(FLM).(42U.S.C.7602(i))2Congress

added section

1 69B

to the CAA

in 1990

to address regional

haze issues.

EPA promulgated

a rule

to address regional

haze

on July

1, 1999

(see

64 FR 35713),

the Regional

Haze
Rule (RHR).

The RHR revised

the existing visibility regulations

to integrate

into

the regulation provisions addressing

regional

haze impairment

and established

a comprehensive

visibility protection

program

for Class

I areas.

The requirements

for regional

haze, found

at 40 CFR 51.308

and 51.309,

are included

in EPA’s visibility protection regulations

at 40 CFR

5 1.300-309. The RHR addressed

the combined visibility

effects

of various pollution

sources

over

a wide geographic

region.

40 CFR 51.308(b)

requires

states

to submit

the first implementation

plan addressing

regional

haze visibility impairment

no later
than December

17, 2007. Consequently,

all

50 states, including

those without

Class

I areas, Washington,

D.C.,

and

the Virgin Islands,

are required

to submit Regional

Haze SIPs 2 . The USEPA designated

five Regional Planning Organizations

(RPOs)

to assist

with

the coordination

and cooperation

needed

to address

the visibility

issue.

The Mid-Atlantic Region

Air Management Association (MARAMA),

the Northeast

States

for Coordinated Air Use Management (NESCAUM)

and

the Ozone Transport Commission

(OTC) established

the Mid-Atlantic/Northeast

Visibility

Union (MANE-VU) 8

regional planning organization

to coordinate

efforts

to address visibility impairment

at seven
Class

I areas located

in the Mid-Atlantic

and Northeast
corridor:

Acadia National

Park,

ME; Brigantine Wilderness,

NJ; Great

Gulf Wilderness,

NH;

Lye Brook Wilderness,

VT; Moosehorn Wilderness,

ME; Presidential

Range— Dry River Wilderness,

NH;

and Roosevelt Campobello International

Park,
New Brunswick.!‘ 2 Albuquerque/Bernalillo

County

in New Mexico

must

also submit

a regional

haze

SIP

to completely

satisfy the requirements

of section

11 O(a)(2)(D)

of the CAA

for
the entire

State

of New Mexico

under

the New Mexico

Air Quality Control

Act (section 74-2-4). Figure

1. Geographical

Areas

of Regional Planning Organizations RéñaI Planning Organizations

3TheDistrictofColumbiaisamemberoftheMid-Atlantic/NortheastVisibilityUnion(MANE-VU)RPO.MembersofMANE—VUarelistedinTable1.Table1MANE-VUMembersConnecticutPennsylvaniaDelawarePenobscotNationDistrictofRhodeIslandColumbiaMaineSt.RegisMohawkTribeMarylandVermontMassachusettsU.S.EnvironmentalProtectionAgency*NewHampshireU.S.NationalParkService*NewJerseyU.S.FishandWildlifeService*NewYorkU.S.ForestService**No1votingmembers4MANE-VU’s

work

is managed

by the Ozone Transport Commission

(OTC)

and carried out

by OTC,

the Mid-Atlantic

Regional

Air Management Association (MARAMA),

and the Northeast

States

for Coordinated

Air Quality Management (NESCAUM).

The states along

with federal agencies

and professional

staff from OTC, MARAMA

and NESCAUM

are members

of the various committees

and workgroups. Since

its inception

on July

24, 2001, MANE-VU established

an active committee structure

to address

both technical

and non-technical

issues related

to regional

haze.

The primary committees

are
the Technical

Support Committee

(TSC) charged

with assessing the nature

and magnitude

of the regional

haze problem

within MANE-VU, interpreting the results

of technical

work,

and report

on such work

to the MANE-VU

Board.

In addition

to the formal working committees,

there

are also three standing working

groups of the TSC. They

are broken

down

by topic

area: Emissions Inventory, Modeling,

and Monitoring/Data

Analysis Workgroups. Introduction

to the District

of Columbia’s

Regional

Haze State Implementation

Plan

EPA promulgated

a rule

to address regional

haze

on July

1, 1999

(see

64 FR 35713),

the RHR.

The RHR addressed

the combined visibility

effects

of various pollution

sources

over

a wide geographic

region.

40 CFR 51.308(b)

requires states

to submit

the first implementation

plan addressing

regional

haze visibility impairment

no later than December

17, 2007. This

SIP was developed

based

on consultations

and work-products

of the MidAtlantic/Northeast

Visibility

Union (MANE-VU)

Regional Planning Organization

(RPO).

It encompasses

1) monitoring

strategies

for evaluating
visibility impacts,

2) baselines

and- trends,

3) long-term strategies

(LTS),

4) how D.C. meets

its fair share

of the “reasonable progress

goals” (RPG) towards reducing visibility impairment

in Class

I areas,

and

5) Best Available

Retrofit Technology

(BART). MANE-VU

states agreed

upon

a

2 percent

sulfate attribution

to

a Class

I area

in order

for

an upwind

state

to meet

the definition

of “significantly contributing”

to visibility impairment

for that Class

I area.

The study results presented

in Table

8.1

of the D.C. Haze

SIP show

that D.C. emission

sources

do not significantly

contribute

to visibility impairment

in any Class

1 area. Therefore,

this

SIP focuses

on how

the D.C. control measures

will help other MANE-VU

states improve visibility. D.C. believes

their Visibility

SIP demonstrates

that D.C.

has met

its BART,

RPG

and LTS obligations

for the first visibility impairment

planning

period through existing D.C./Federal regulations

and on-the-books/on-the-way

federal emission controls.

In addition

to extensive consultation

with

the MANE-VU

states,

D.C.

has consulted

with Federal

Land Managers (FLMs) responsible

for the Class

I areas,

and

the EPA

in the development

of this
SIP. What

Are The Components

Of

A Modeled Regional

Haze Demonstration? Modeling

Process Overview The goal

of the regional

haze program

is

to return

to natural conditions

by 2064,

and

5Statesarerequiredtodemonstrate,bytheendofthefirstplanningperiod(by2018),reasonableprogresstowardmeetingthatgoal.D.C.isamemberoftheMid-Atlantic/NortheastVisibilityUnion(MANE-VU)RegionalPlanningOrganization(RPO).TheMANE-VURPOwastaskedwiththeassignmentofpreparingaPM2.5modelingplatformthatallmemberstatescouldusetomodeltheirLTSstodemonstratereasonableprogressby2018inmeetingtheultimategoalofnaturalvisibilityconditionsby2064.TheNewYorkStateDepartmentofEnvironmentalConservation(NYSDEC)wastheleadagencyforcoordinatingandrunningthemodelingplatformusedbytheMAVE-VURPO.ModelingcentersresponsibleforrunningtheplatformincludedtheNYSDEC,theUniversityofMarylandatCollegePark(UMD),theNortheastStatesforCoordinatedAirUseManagement(NESCAUM),theNewJerseyDepartmentofEnvironmentalProtection(NJDEP),andtheVirginiaDepartmentofEnvironmentalQuality(VADEQ).Eachmodelingcenterwasresponsibleforinstallingthemodelingplatform,conductingdiagnostictestsandcompletingabenchmarkruntoensureaccurateresults.TheMANE-VURPOusedtheCommunityMulti-scaleAirQualitymodel(CMAQ)version4.5.1asitsphotochemicalgridmodel.Themodelusessimulationsofchemicalreactions,emissionofPM2.5andPM2.5precursorsandasophisticatedmeteorologicalmodel(ThePennsylvaniaStateUniversity/NationalCenterforAtmosphericResearchMesoscaleMeteorologicalModel(MM5))toproducespeciatedPM2.5concentrationsovertheeasternUnitedStates.Themeteorologicaldatausedinthemeteorologicalmodelwasforthe2002baseyear.Thephotochemicalgridmodelwasrunwiththebaseyearmeteorologyandbaseyearemissionstodetermineifthemodelperformancewassatisfactory.Oncethemodelperformancewasdeterminedtobeadequate,PM2.5concentrationsweremodeledbyrunningthemodelwithprojectedemissionsfor2018andtheoriginal2002meteorology.Themeteorologywasheldconstantsothattheresultsofchangingtheemissionswouldnotbeinfluencedbychangingmeteorology.TheEPAmodelingguidance3recommendsthatmodelingbeusedtodeveloprelativeresponsefactorsforeachof6componentsofparticulatematterbetweenabaseperiod(2000-2004)andafuture5-yearperiodwhichwillbereviewedin2018.PMcomponentsusedforregionalhaze-relatedapplicationsare:-massassociatedwithsulfates;-massassociatedwithnitrates;-massassociatedwithorganiccarbon;-massassociatedwithelementalcarbon;-massassociatedwithfinesoil(i.e.,crustalmaterial);-massassociatedwithcoarseparticulatematter(i.e.,PMio-PM2.5).GuidanceontheUseofModelsandOtherAnalysesforDemonstratingAttainmentofAirQualityGoalsforOzone,PM2.5,andRegionalHaze,EPA-454/B-07-002,April20076CurrentspeciatedmeasurementsinaClassIareaareusedinanempiricallyderivedequationtoestimatelightextinctionforeachdaywithmeasurements.Daysarerankedaccordingtotheirresultinglightextinction(measuredindeciviews).Thisrankingisusedtoidentifythe20%ofdayswithworstand20%ofdayswithbestvisibilityduringeachyearinthebaseperiod.The20%worstandbestdaysareexaminedtoestimateappropriateobservedconcentrationsforthecomponentsofPMon“best”and“worst”days.Observedcomponentconcentrationsaremultipliedbythecorrespondingrelativeresponsefactorstoestimatefutureconcentrationsforeachcomponenton“best”and“worst”days.Futurecomponentconcentrationsaretheninsertedintotheequationrelatinglightextinctiontoconcentrationsofparticulatematter.Theresultingestimatesforfuturelightextinctionon“best”and“worst”daysarecomparedwithobservationsmadeduringthebaseperiodtoassessthefutureyearvisibilityimprovementanddemonstratereasonableprogressby2018inmeetingtheultimategoalofnaturalvisibilityconditionsby2064.StepsRequiredinModelingFutureYearVisibilityImprovementThemodelingguidancelistsninestepsforpreparingmodelingtodemonstratereasonableprogresstowardvisibilityimprovementgoals.1.Developaconceptualdescriptionoftheproblemtobeaddressed.2.Selectanappropriatemodeltosupportthedemonstration.3.Selectappropriatemeteorologicaltimeperiodstomodel.4.Chooseanappropriateareatomodelwithappropriatehorizontal/verticalresolutionandestablishtheinitialandboundaryconditionsthataresuitablefortheapplication.5.Generatemeteorologicalinputstotheairqualitymodel.6.Generateemissionsinputstotheairqualitymodel.7.Runtheairqualitymodelwithbasecaseemissionsandevaluatetheperformance.Performdiagnosticteststoimprovethemodel,asnecessary.8.Performfutureyearmodeling(includingadditionalcontrolstrategies,ifnecessary)andusetheresultstocalculatefutureyearvisibilityandvisibilityimprovement. How

Did The District

Of Columbia

Address

All

Of The Components

a Modeled Demonstration

Of Future

Year Visibility Improvement?TheD.C.HazeSIPaddresseseachoftherequiredelementsofamodelinganalysisusedtopredictvisibilityimprovementthatisexpectedby2018.ConceptualDescriptionoftheProblemAconceptualmodeldescribeshowweatherpatternsaffecttheformationandtransportofPM25,accountingforemissionsandphotochemistry.TheconceptualmodelfortheD.C.HazeSIPisdescribedinAppendix0oftheD.C.HazeSIPinadocumententitled:TheNatureoftheFineParticleandRegionalHazeAirQualityProblemsintheMid-AtlanticNortheastVisibilityUnion(MANE-VU)Region.AConceptualDescription(NESCAUM),November2006.ThisdocumentwaspreparedbyNortheastStatesforCoordinatedAirUseManagement(NESCAUM)forusebytheOTC7memberStates,anditprovidestheconceptualdescriptionofthefineparticleissuesintheOTCstates,consistentwiththeEPA’sguidance.TheNSCAUMdocumentcontainsaconceptualdescriptionthatexplainshowelevatedregionalPM2.5peakconcentrationsinthesummerdiffersignificantlyfromthelargelyurbanpeakconcentrationsobservedduringwinter.Onaverage,summertimeconcentrationsofsulfateinthenortheasternUnitedStatesaremorethantwicethatofthenextmostimportantfineparticleconstituent,organiccarbon(OC),andmorethanfourtimesthecombinedconcentrationofnitrateandblackcarbon(BC)constituents.EpisodesofhighsummertimesulfateconcentrationsareconsistentwithstagnantmeteorologicalflowconditionsupwindofthePhiladelphia-Wilmington,PA-NJ-DEPM2.5NAAandtheaccumulationofairbornesulfate(viaatmosphericoxidationofS02)followedbylongrangetransportofsulfuremissionsfromindustrializedareaswithinandoutsidethearea.Nationalassessmentshaveindicatedthatinthewinter,sulfatelevelsinurbanareasarehigherthanbackgroundsulfatelevelsacrosstheeasternU.S.,indicatingthatthelocalurbancontributiontowintertimesulfatelevelsissignificantrelativetotheregionalsulfatecontributionfromlong-rangetransport.Anetworkanalysisforthewinterof2002suggeststhatthelocalenhancementofsulfateinurbanareasoftheMANE-VUregionrangesfrom25to40%andthatthelong-rangetransportcomponentofPM2.5sulfateisstillthedominantcontributorinmosteasterncities.Inthewinter,urbanorganiccarbon(OC)andsulfateeachaccountforaboutathirdoftheoverallPM2.5massconcentrationobservedinPhiladelphiaandNewYorkCityareas.NitratealsomakesasignificantcontributiontourbanPM2.5levelsobservedinthenortheasternUnitedStatesduringthewintermonths.WintertimeconcentrationsofOCandnitrateinurbanareascanbetwicetheaverageregionalconcentrationsofthesepollutants,indicatingtheimportanceoflocalsourcecontributions.Thisislikelybecausewinterconditionsaremoreconducivetotheformationoflocalinversionlayerswhichpreventverticalmixing.Undertheseconditions,emissionsfromtailpipe,industrialandotherlocalsourcesbecomeconcentratedneartheEarth’ssurface,addingtobackgroundpollutionlevelsassociatedwithregionallytransportedemissions.Insummary,thepresenceoffineparticulatematterinambientairsignificantlyobscuresvisibilityduringmostpartsoftheyearatsitesacrosstheMANE-VUregion.Particlepollutiongenerally,anditssulfatecomponentspecifically,constitutetheprincipledriverforregionalvisibilityimpacts.Whilethebroadregionexperiencesvisibilityimpairment,itismostsevereinthesouthernandwesternportionsofMANE-VUthatareclosesttolargepowerplantS02sourcesintheOhioRiverandTennesseeValleys.Thepresenceorabsenceofregionalsulfatealmostexclusivelydrivessummervisibilityimpairment,whereaswintervisibilitydependsonacombinationofregionalandlocalinfluencescoupledwithlocalmeteorologicalconditions(inversions)thatleadtotheconcentratedbuild-upofpollution.SulfateisthekeyparticleconstituentfromthestandpointofdesigningcontrolstrategiestoimprovevisibilityconditionsinthenortheasternUnitedStates.Significantfurther8reductions

in ambient

sulfate

levels

are achievable,

though

they

will require

more

than proportional

reductions

in S02 emissions. Long-range

pollutant transport

and local pollutant emissions

are important, especially along

the eastern seaboard,

so one must

also look beyond

the achievement

of further sulfate reductions.

During

the winter months,

in particular, consideration

also needs

to be given

to reducing

urban sources

of S02,

as well

as NOx

and

OC (NARSTO, 2003). Modeling Platforms Currently

two regional-scale

air quality models

have been evaluated

and used

by NESCAUM

to perform

air quality simulations.

These

are
the Community Multi-scale Air Quality modeling

system (CMAQ;

Byun

and Ching,

1999)

and

the Regional Modeling

System

for Aerosols

and Deposition (REMSAD;

SAl, 2002). CMAQ

was developed

by USEPA,

while REMSAD

was developed

by ICF Consulting/Systems Applications International

(ICF/SAI)

with USEPA support.
CMAQ

has undergone extensive community development

and peer review (Amar

et al., 2005)

and

has been successfully

used

in

a number

of regional

air quality studies

(Bell

and Ellis, 2003; Hogrefe

et al., 2004; Jimenez

and Baldasano,

2004;

Mao

and Talbot,

2003; Mebust

et al., 2003). REMSAD

has also

has been
peer reviewed (Seigneur

et al., 1999)

and used

by USEPA

for regulatory applications
(www.epa. gov/otaq/regs!hd2007/frm/r0002

8 .pdf

and www

.epa

gov ‘clearskies’air

quality tech.html)

to study ambient concentrations

and deposition

of sulfate

and other

PM species. Five modeling

centers, worked collectively

to maximize efficiency

of computing resources

in MANE-VU

for SIP modeling.

These centers include

NY DEC,

NJ DEP/Rutgers,

VA DEQ, UMD,

and NESCAUM. Meteorological

Time Periods

Used

in the Modeling All

of 2002, which represents

the baseline

period

from 2000

to 2004,

was included

in CMAQ modeling.

2002

was divided

into
five periods.

UMD

is responsible

for modeling the period

from January

1 to February

28;

NJ DEP/Rutgers

are responsible

for the period from March

ito May

14; NY DEC

is responsible

for the period

from
May

15

to September

30; VA DEQ

is responsible

for the period

from October

1 to October

31; and NESCAUM

is responsible

for the period

from November

1 to December

31. Each period uses

a 15 day spin

up run

to minimize

the impact

of the default

initial concentration fields.

Each group performs

CMAQ simulations

on

its period

for

a series

of scenarios including

2002 Base Case,

2009 Base Case,

2018 Base Case,

2009 Control

Case,

and 2018 Control

Case.

All scenarios

adopt

the same meteorological

field (2002)

and boundary conditions,

varying

only emission

inputs.

To ensure consistency

between modeling

groups,

a benchmark

test was conducted

by each group. Meteorological

Data Used

in the Air Quality

Model The MANE-VU

states decided

to use

a prognostic meteorological

model

that provides life-like meteorological

inputs

to the photochemical

grid model.

The Pennsylvania

State University/National

Center

for Atmospheric

Research Mesoscale Meteorological

Model

9(MM5)version3.6waschosenforthemodelinganalysis.TheMM5modelprovidesareasonablerepresentationofweatherconditionsatthesurfaceandaloft.DomainoftheModel,HorizontallVerticalResolutionandtheInitialandBoundaryConditionsMANE-VUhasadoptedtheInter-RPOdomaindescriptionforitsmodelingruns.This36-kmdomaincoversthecontinentalUnitedStates,southernCanadaandnorthernMexico.Thedimensionsofthisdomainare145and102cellsintheeast-westandnorthsouthdirections,respectively.A12-kminnerdomainwasselectedtobettercharacterizeairqualityinMANE-VUandsurroundingRPOregions.Thisdomaincoverstheeasternregion,whichincludesthenortheastern,central,andsoutheasternU.S.,aswellassoutheasternCanada.Itextendsfrom660W-94inlongitudeand290N50inlatitudewith172X172gridcells(Figure3).IVerticalresolutionisthenumberoflayersandthesizeofeachlayerinthemodel.Thelayersinthephotochemicalgridmodelweresetuptobecompatiblewiththemodelthatproducedweatherconditionsforthephotochemicalgridmodel.TheverticalresolutionusedinthemodelingexercisefollowedEPA’smodelingguidanceandthereforeadequatelyrepresentstheatmospherewherePM2.5isemitted,formsandistransported.Figure3.ModelingdomainsusedinMANE-VUairqualitymodelingstudieswithCMAQ.Outer(blue)domaingridis36kmandinner(red)domainis12kmgrid.Thegridlinesareshownat180kmintervals(5x536kmcells/15x1512kmcells).102

4.z ILEasternModelingDomain(12kmgrid) RPO National
Domain

(36km

grid)

-fr10Baseline

and Future

Year Emission Inventories

for Modeling Section

51.3 08(d)(3

)(iii)

of EPA’

s Regional

Haze
Rule requires

the States

to identify

the baseline emission inventory

on which strategies

are based.

The baseline inventory

is intended

to be used

to assess progress

in making emission reductions.

Based

on EPA guidance
entitled,

2002 Base
Year Emission Inventory

SIP Planning:

8-hour Ozone,

PM2.5 and Regional

Haze Programs,

which identifies

2002

as the anticipated

baseline emission inventory

year

for regional

haze, MANE-VU

and

the District

of Columbia

are using

2002

as the baseline

year. Future

year inventories

were developed

for
the years 2009,

2012

and 2018 based

on the 2002

base year. These future

year emission inventories include emissions

growth

due

to projected increases

in economic

activity

as well

as the emissions reductions

due

to the implementation

of control measures. The 2002 emissions

were

first generated

by the individual

states

in the MANE-VU

area. MARAMA

then coordinated

and quality assured

the 2002 inventory

data.

The 2002 emissions

from non-MANE-VU

areas within

the modeling

domain

were obtained

from other Regional Planning Organizations

for their corresponding

areas. These Regional Planning Organizations

included

the Visibility Improvement

State

and Tribal Association of the Southeast (VISTAS),

the Midwest Regional Planning Organization

and

the Central Regional

Air Planning Association. Version

3 of the 2002
base
year emission inventory

was used

in the regional modeling exercise. Technical

support documentation

for the MANE-VU

2002
base inventory

is presented

in Appendix

D of the D.C. Haze

SIP. This document

explains

the data sources, methods,

and results

for preparing

this version

of the 2002
base
year criteria

air pollutant and ammonia emissions inventory. Documentation

for the future

year estimations

of EGUs

is presented

in Appendix

F of the D.C. Haze

SIP. Documentation

for the future year estimations

of the remaining

source sectors (non-EGU

sectors)

is presented

in Appendix

E of the D.C. Haze

SIP. Model Performance
Evaluation NESCAUM

evaluated

the 2002 annual

12 km resolution meteorological

fields generated

by MM5 using ENVIRON’s METSTAT

program.

Model results

of surface

wind speed,

wind direction, temperature,

and humidity

were paired

with measurements

from EPA’s
Clean

Air Status

and Trends Network (CASTNET)

and National

Center

for Atmospheric
Research’s Techniques

Data Laboratory

(TDL) network

by hour

and

by location

and then statistically compared.

Based

on this statistical comparison

between

model prediction

and data from

the two networks

for wind speed,

wind direction, temperature,

and humidity,

MM5 performs well.

An acceptable

small

bias,
high index

of agreement

and strong correlation

with CASTNET

and TDL

data

are shown.

Since MM5

uses TDL

data

for nudging,

the model predictions

are

in better agreement

with TDL

data than with CASTNET

data. MM5 performs better

in Midwest

and Northeast

than Southeastern

US. CMAQ modeling

was conducted

for year 2002

by cooperative

modeling

efforts

from NYDEC,

U’D, NJDEP, Rutgers, VADEP,

and NESCAUM.

CMAQ Performance

for PM 2.5 species

and visibility

was examined

based

on this CMAQ

run

on

a 12 km resolution domain. Measurements

from IMPROVE

and STN networks

were paired

with model predictions

by location

and time

for evaluation.

The goal

and

the criteria

for PM2.s evaluation

11suggestedbyBoylanandBaker(2004)wereadoptedbyeveryRPOforSIPmodeling.Theperformancegoalsare:MeanFractionalError(MFE)+50%,andMeanFractionBias(MFB)±30%;whilethecriteriaareproposedas:MFE+75%,andMFB±60%.CMAQpredictionofPM2.5speciesfrom40STNsitesand17IMPROVEsiteswithintheMANE-VURegionwerepairedwithmeasurementsandstatisticallyanalyzedtogenerateMFEandMFBvalues.ConsideringCMAQperformanceintermsofIVIFEandMFBgoals,sulfate,nitrate,OC,BC,andPMisallhadthemajorityofdatapointswithinthegoalcurve,somewerebetweenthegoalandacceptablecriteria,andonlyafewwereoutsidethecriteriacurve.Onlyfinesoilhasthemajorityofpointsoutsidethecriteriacurve,butthereweresomesitesstillwithinthegoal.FortheMANE-VUregion,CMAQperformsbestforPM25sulfate,followedbyPM2.5,EC,nitrate,OC,andthenfinesoil.RegionalhazemodelingalsorequiresCMAQperformanceevaluationforaerosolextinctioncoefficient(Bext)andthehazeindex.ModeleddailyaerosolextinctionateachimprovesitewascalculatedfollowingtheIMPROVEformulawithmodeleddailyPM2.5speciesconcentrationandrelativehumidityfactorsfromIMPROVE.TheapproachusednaturalbackgroundvisibilityestimatesandthehazeindexfollowingEPAGuidance.ThemodeledBextshowedanear1:1linearrelationship(slopeof0.78androf0.46)withIMPROVEobservedBext.TheregressionexcludedthreepointsfromJuly7,2002;themonitorsweredirectlyimpactedbyCanadianfireswhoseemissionswerenotmodeled.UniformRateofProgressThekeydifferencebetweenSIPsfromStateswithClassIareasandthoseStateswithoutClassIareas,butmayhavesourcesthatimpactvisibilityonClassIareas,isthecalculationofthebaselineandnaturalvisibilityfortheirClassIareasandthedeterminationofuniformrateofprogressgoals-expressedindeciviews-thatprovideforreasonableprogresstowardsachievingnaturalvisibilityby2064.ItistheClassIstatesresponsibilityassessthesecalculations.TheClassIStatesmustalsoconsultwiththoseStates,whichmayreasonablybeanticipatedtocauseorcontributetovisibilityimpairmentintheirClassIareas(40CFR51.308(d)(1)(i-vi)).Thebaselinevisibilityconditionsarecalculatedforthebaselineperiodbetween2002and2004.Theaverageimpairmentforthe20mostand20leastimpaireddaysaredeterminedforeachcalendaryearandcompiledintotheaverageofthreeannualaverages(40CFR51.308(d)(2)(i)).Thenaturalvisibilityconditionsaredeterminedforthesamebaselineperiodwiththemostandleastimpaireddaysdeterminedbyavailablemonitoringdataoranappropriatedataanalysistechnique(40CFR51.308(d)(iii-iv)).U.S.EnvironmentalProtectionAgency(EPA)releasedguidanceonJune7,2007touseinsettingreasonableprogressgoals.Thegoalsmustprovideimprovementinvisibilityforthemostimpaireddays,andensurenodegradationinvisibilityfortheleastimpaireddaysovertheStateImplementationPlan(SIP)period.TheStatemustalsoprovideanassessmentofthenumberofyearsitwouldtaketoattainnaturalvisibilityconditionifimprovementcontinuesattheraterepresentedbythereasonableprogressgoal.Figure4illustratesanexampleofhowUniformRateofProgressiscalculated.12Figure

4. Example calculation

of Uniform

Rate

of Progress Uniform

Rate

of Progress Uniform

Rate al 8 dV

l4yr of Progress

60

yr— 4.2

dv Over

First Planning

Penod Natural Conditions—*,10—,.,,,,.. 2004

2024

2034

2044

2054

2064 Year Reasonable

Progress

Goals Since
there

are

no Class

I areas within

the District

of Columbia,

the District

is not required

to establish reasonable

progress

goals

for any Class

I areas. Under

40 CFR Section 51.308(d)(1)(iv),

States

with Class

I areas must consult

with other States

as they develop

goals

for their Class

I areas.

As

a member

of MANE-VU,

the District worked

in cooperation

with MANE-VU

Class

I states

as those states established reasonable

progress goals

for their Class

I areas. MANE-VU

also sponsored meetings

and conference

calls

to facilitate consultation

with states

in the VISTAS

RPO, including
Virginia

and West Virginia. Modeled Visibility Projections

for 2018 The CMAQ

air quality
model

was used

to simulate

base period emissions

and future emissions.

The modeling

results

for the base
year period (2002)

and

the year representing

the end

of the first planning

period (2018)

are used

to develop relative response

factors
(RRF)

for each component

of particulate

matter identifie&previously

in this TSD.

The relative response

factors

are multiplied

by the measured

species concentration

data during

the base period

(for

the measured

20%
best

and worst days). This results

in daily future

year species concentrations

data.

The projected concentrations are then used

to derive

daily visibility

in deciviews

and

are averaged

across

all best

and worst

days

to create

the projected

future visibility.

The results

of this procedure

are plotted

along

with

the uniform progress

glide slope

in Figure

3-1 through

Figure

3-7

in Appendix

I of the D.C. Haze

SIP. 30 Baseline

—a.

2014

13ThemodelingresultspresentedinAppendixIoftheD.C.HazeSIPshowallMANE-VUsitesandsitesinShenandoahNationalParkandDollySodsWildernessAreaareprojectedtomeetorexceedtheuniformrateofprogressgoalsfor2018onthe20percentworstdays.Inaddition,nositeanticipatesincreasesinvisibilityimpairmentrelativetothebaselineonthe20percentbestdays.ShenandoahNationalPark(Virginia)andDollySodsWildernessArea(WestVirginia),bothwithintheVisibilityImprovementStateandTribalAssociationoftheSoutheast(VISTAS)region,wereincludedinMANE-VU’stechnicalanalysisduetotheirproximitytotheDistrictofColumbia.SummaryofPhotochenticalGridModelingResultsInsummary,thephotochemicalgridmodeling,presentedintheD.C.HazeSIP,followEPA’smodelingguidanceandisacceptabletoEPA.AllsitesincludedintheMANE-VUanalysisareprojectedtomeetorexceedtheuniformrateofprogressgoalfor2018onthe20percentworstdays.Inaddition,nositeanticipatesincreasesvisibilityimpairmentrelativetothebaselineonthe20percentbestdays. Contribution AssessmentThe1999RegionalHazeRulerequiresStatesandTribestosubmitStateImplementationPlans(SIPs)totheU.S.EnvironmentalProtectionAgency(USEPA)forapprovalbyJanuary2008atthelatest.ThehazeSIPsmustincludea“contributionassessment”toidentifythosestatesorregionsthatmaybeinfluencingspeciallyprotectedfederallandsknownasFederalClassIareas.4ThesestatesorregionswouldthenbesubjecttotheconsultationprovisionsoftheHazeRule.TheHazeRulealsorequiresa“pollutionapportionment”analysisaspartofthelong-termemissionsmanagementstrategyforeachsite.AsdescribedintheConceptualDescriptionportionofthisTSD,sulfatealoneaccountsforanywherefromone-halftotwo-thirdsoftotalfineparticlemassonthe20percenthaziestdaysatMANE-VUClassIsites.AsaresultofthedominantroleofsulfateintheformationofregionalhazeintheNortheastandMid-Atlanticregion,MANE-VUconcludedthataneffectiveemissionsmanagementapproachwouldrelyheavilyonbroad-basedregionalS02controleffortsintheeasternUnitedStates.AreaofInfluenceforMANE-VUClassIAreasThekeydifferencebetweenSIPsfromStateswithClassIareasandStateswithoutClassIareasisthecalculationofthebaselineandnaturalvisibilityfortheirClassIareas,andthedeterminationofreasonableprogressgoals.ClassIStatescalculatebaselinevisibilityconditionsfortheperiodbetween2002and2004.TheaverageimpairmentforthemostandleastimpaireddaysaredeterminedforeachcalendaryearandcompiledintotheClassIdesignationappliestonationalparksexceeding6,000acres,wildernessareasandnationalmemorialparksexceeding5,000acres,andallinternationalparksthatwereinexistencepriorto1977.IntheMANE-VUarea,thisincludes:AcadiaNationalPark,Maine;BrigantineWilderness(withintheEdwinB.ForsytheNationalWildlifeRefuge),NewJersey;GreatGulfWilderness,NewHampshire;LyeBrookWilderness,Vermont;MoosehornWilderness(withintheMoosehornNationalWildlifeRefuge),Maine;PresidentialRange—DryRiverWilderness,NewHampshire;andRooseveltCampobelloInternationalPark,NewBrunswick.14average

of three annual averages

(40 CFR 51.308 (d)(2)(i)).

The natural visibility conditions

are determined

for
the same baseline

period

with

the most

and least impaired days determined

by available monitoring

data

or

an appropriate

data analysis technique (40 CFR 51.308 (d)(iii-iv)).

In contrast,

States without

Class

I areas

are responsible

for doing

their

fair share

to help meet

the reasonable

progress

goals established

by the impacted

Class

I States,

and

for maintaining

their emissions monitoring

network. There

are seven
Class

I areas located

in the Mid-Atlantic

and Northeast.

The District

of Columbia

does

not have

a Class

I area located
within

its borders.

As

a result,

the Rule requires

D.C.,

in consultation

with MANE-VU

and others,

to identify

where

its emissions are most likely

to influence visibility

in Class

I areas.

In order

to identify

states whose emissions

are most likely

to influence visibility

in MANE-VU

Class

I areas, MANE-VU prepared

the Contributions

to Regional

Haze

in the Northeast

and Mid-Atlantic

United States (Contribution Assessment).

The

full report

can

be found

in Appendix

K of the D.C. Haze

SIP. Based

on that work, MANE-VU
concluded

that

it was appropriate

to define

an “Area

of Influence”

(AOl) including

all

of the states participating

in MANE-VU
pjjother

states outside MANE-VU

for which modeling indicated

they contributed

at least

two percent (2%)

of the sulfate

ion

in MANE-VU

Class

I areas

in 2002.

The Visibility Improvement State

and Tribal Association

of the Southeast (VISTAS) 5

also conducted

an AOl analysis, which

used

a level

of one percent

(1%)

to assess whether

an upwind

state significantly contributed. The primary contribution assessment

tool used

in the D.C. Haze

SIP was

the Regional Modeling

System

for Aerosols

and Deposition (REMSAD)

(SAl, 2002).

A significant feature

of the REMSAD

work
used

to evaluate regional contributions

is that NESCAUM reprocessed

the S02 emission

data from
each
state

to take advantage

of REMSAD’s tagging capabilities.

Thus,

all SO 2 emissions
included

in the model

for
the eastern

half

of the country

were tagged according

to state

of origin,

and emissions

from Canada

and

the boundary conditions

were

also tagged.

This allowed

for

a rough estimation

of the total contribution

from elevated

point sources

in each
state

to simulated

sulfate concentrations at eastern receptor

sites. Using identical emission

and meteorological

inputs

to those prepared

for the CMAQ

SIP modeling platform, described

earlier

in this TSD, REMSAD was used

to simulate

the annual average
impact

of each state’s

SO 2 emission

sources

on the sulfate fraction

of PM

over

the northeastern

United
States.

A more in-depth2.5 description

of the REMSAD modeling

used

for contribution assessment

can

be found

in Appendix

K of the D.C. Haze

SIP. The REMSAD contribution assessment
modeling contained

in the D.C. Haze

SIP conforms

to EPA modeling requirements

and

is acceptable

to EPA.VISTASiscomprisedofthefollowingstates:Alabama,Florida,Georgia,Kentucky,Mississippi,NorthCarolina,SouthCarolina,Tennessee,Virginia,WestVirginia,theEasternBandofCherokeeIndians,andKnoxCounty,TN

15REMSADContributionAssessmentResultsMANE-VUStatesdecidedthatanystateorregionthatcontributedatleast2percentoftotalsulfateobservedon20percentworstvisibilitydaysin2002iscontributingsignificantlytothehazeprobleminthatparticularClassIarea.BasedontheMANE-VUContributionAssessmentandtheapplicationofthe“2%SO2rule,”theDistrictdoesnotcontributegreaterthan0.1Ig/m3ortwopercentsulfatecontributiontoanynearbyClassIareas(seeTable8.1oftheD.C.HazeSIP),whichisthethresholdestablishedbyMANEVUstateswithClassIareasforcontributingtomeetthereasonableprogressgoalsfor2018.Withrespecttosulfate,theContributionAssessmentestimatedemissionsfromwithinMANE-VUin2002wereresponsibleforabout25-30percentofthesulfateatClassIareaslocatedwithinandnearbytotheMANE-VUregion(seeChapter8ofAppendixKoftheD.C.HazeSIP).ThecontributionofsulfateattheseClassIareasfromotherregions,Canada,andoutsidethemodelingdomainwerealsosignificant.AsdescribedinTable8.1oftheD.C.HazeSIP,theDistrictemissionsdonotsignificantlycontributetovisibilitydegradationinanyClassIarea.BARTOnJuly6,2005(70FR39104)EPAfinalized40CFR51—RegionalHazeRegulationsandGuidelinesforBestAvailableRetrofitTechnology(BART)DeterminationsaddressingtheissuesfromtheCircuitCourtdecisions.TheBARTrequirementsweremostrecentlyupdatedonOctober5,2006.BARTisdefinedasanemissionlimitationbasedonthedegreeofreductionachievablethroughtheapplicationofthebestsystemofcontinuousemissionreductionforeachpollutant,whichisemittedbyaBART-eligiblesource.ThechangestotheruleincludedhowtheStateswouldidentifythebestsystemofcontinuousemissioncontroltechnologyandbywhichStatescanconsideranindividualfacility’scontributiontoregionalhazewhendeterminingtorequirecontrols,andwhatthelevelofcontrolshouldbemet.TherulechangesalsoclarifiedtherequirementsassociatedwithdemonstratinghowemissionstradingoralternativeprogramsmaybeusedasanalternativetoapplyingBestAvailableRetrofitTechnology(BART)Requirements.CongressdefinedsourcespotentiallysubjecttoBART-asmajorstationarysources,includingreconstructedsources;fromoneof26identifiedsourcecategorieswhichincludedutilityandindustrialboilers,andlargeindustrialplantssuchaspulpmills,refineriesandsmelters;whichhavethepotentialtoemit250tonsperyearormoreofanyairpollutant,andwhichwereplacedinoperationbetweenAugust1962andAugust1977.[CAA169A(b)(2)(A)&(g)(7)].DistrictofColumbiaSourcesSubjecttoBARTBenningRoadGeneratingStation(BRGS)16Is BRGS Subject

to BART? On August

18, 2011,

PES formally committed

to accept

a permit condition

to shut down EGU Units

15 and

16
no later than December

17, 2012, without alternative conditions

in lieu

of shutting

down.

This means

that

the plant

is exempt

from

all BART requirements for S02, NON,

and
PM because

the EGUs

will

no longer

be BART-eligible.

The final permit

is an enforceable

assurance

that

the District

will meet BART requirements. Summary

of EPA’s Technical
Findings The technical
analyses

and modeling

used

to assess uniform

rate

of progress

and

to support

the LTS were successfully
developed consistent

with EPA’s interim

and final modeling guidance.

All MANE-VU

sites

are projected

to meet

or exceed

the uniform rate

of progress

goal

for 2018

on the

20 percent

worst

days.

In addition,

no site anticipates
increases visibility impairment

relative

to the baseline

on the

20 percent

best days.

EPA finds

the MANE-VU

technical modeling
analyses presented

in the D.C. Haze SIP

to be acceptable

because

the models

that were
used were applied according

to EPA modeling guidance.

17Attachments:Attachment1:TheNatureoftheFineParticleandRegionalHazeAirQualityProblemsintheMid-AtlanticNortheastVisibilityUnion(MANE-VU)Region:AConceptualDescription(NESCAUM),November2006.18