portal.azoah.com · VIA E‐MAIL: [email protected] December 15, 2017 Mr.Balaji...

VIAE‐MAIL:[email protected]

December15,2017

Mr.BalajiVaidyanathanManager,FacilitiesEmissionControlSectionArizonaDepartmentofEnvironmentalQuality1110WashingtonStreetPhoenix,AZ85007

RE: ClassIIAirQualityRenewalPermitNo.55223ComprehensiveRequestforAdditionalInformation,RevisedAirDispersionModelingReport

DearBalaji:

InJuly2017,theRosemontCopperCompanysubmittedaClassIISyntheticminorpermitrenewalapplicationtotheArizonaDepartmentofEnvironmentalQuality.Therenewalapplicationincludedanairqualitymodelingreport(ProjectReport,RosemontCopperCompany,PimaCounty,AZ.AERMODModelingReport.July2017)documentingthemethodologyandresultsoftheairqualityanalysespreparedinsupportofAirQualityClassIISyntheticMinorPermit(Permit#55223)renewalandmodificationfortheRosemontCopper(Rosemont)Project.

BasedonADEQ’spreliminaryreviewofthemodelingreport,onSeptember26,2017theagencyprovidedaComprehensiveRequestforAdditionalInformation(hereinafterreferredtoasComprehensiveRequest).OnNovember17,2017,RosemontrespondedtotherequestandprovidedanAmendedAERMODModelingReport,aswellasacoverletterdetailingtheitemsincludedintheComprehensiveRequestalongwithRosemont’sresponsetothoseitems.OnDecember7,2017,aconferencecallwasheldbetweenADEQ,Rosemont,andTrinityConsultants(Trinity),duringwhichADEQrequestedadditionalmodificationstotheAERMODModelingReportandassociatedemissionsinventory.Theadditionalmodificationsincludethefollowingitems.Foreachitem,Rosemont’sresponseorassociatedmodelrevisionhasbeenidentifiedinboldtext

1. MeteorologicalData

IntheNovember2017AmendedAERMODModelingReport,RosemontusedsitespecificmeteorologicaldatacollectedfromMarch2006toFebruary2009.The2006‐2009dataset,however,isnotcontinuousasdatabetweenDecember2006andFebruary2007werelostduetoadataloggermalfunction.Inordertoavoidissuesrelatedtodatareplacementmethodology,ADEQrecommendsusingthesite‐specificmeteorologicaldatacollectedfromMarch2007toFebruary2009forthedispersionmodelinganalyses.RosemontshouldusethemostrecentversionofAERMETtoprocessthemeteorologicaldata.

ThemodelinganalysishasbeenrevisedtousethesitespecificmeteorologicaldatacollectedfromMarch2007toFebruary2009.ThedatawasreprocessedwiththemostrecentversionofAERMET.Detailsregardingthemeteorologicaldata,andrevisedmodelingresultsarepresented

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Mr.BalajiVaidyanathan‐Page2December15,2017

intheDecember2017AmendedAERMODModelingReport,Section5.4–Amended,Section6.7–Amended,andSection9.1‐Amended.

2. On‐siteMeteorologicalMonitorBaseElevation

Thebaseelevationfortheon‐sitemonitorgivenintheAERMETfilesis1591meters;however,thebaseelevationusedintheAERMODfilesis1567meters.Rosemontshoulddeterminewhichelevationiscorrect,andusethatelevationinboththeAERMETandAERMODfiles.

Itwasdeterminedthatthecorrectbaseelevationofthemonitoris1591meters.Themodelinganalysishasbeenrevisedtouseanelevationof1591metersinboththeAERMETandAERMODfiles.

3. DryStackTailingsVolumeSources

ItwasunclearfromthedescriptionprovidedintheAERMODModelingreporthowthedimensionsofthevolumesourcesrepresentingthedrystacktailingsweredetermines.ADEQrequestedRosemontrevisethemodeleddimensionsofthethreevolumesourcesthatarebeingusedtorepresentthedrystacktailingsanddescribethemethodologyinthemodelingreport.

Thevolumesourcesrepresentingthedrystacktailingswerepreviouslychosenbasedontotaltailingsareasize,withemissionsassignedbasedonvolumesourcesize.Thevolumesourceshavebeenrevisedtomoreaccuratelyrepresentthedisturbedtailingsarea(500acres)usingthreeequallysizedvolumesourcesandemissionsdistribution.TherevisedmethodologyisdetailedinSection6.8.2.2oftheDecember2017AmendedAERMODModelingReport.

4. CombinationHaulRoadLengthandSourceAllocation

Thetotallengthofthecombinationhaulroadsusedintheemissionscalculationsandsourceallocationdidnotcorrespondtothelengthofthecombinationhaulroadrepresentedinthemodel.ADEQrequestedRosemontrevisethenumberofvolumesourcesfortheoutofpitcombinationhaulroadinthemodeltoensureitisconsistentwiththeemissionsinventory.

Thehaulroadlengthrepresentedinthemodelinadvertentlyincludedaportionoftheinpitcombinationhaulroad.Thenumberofvolumesourcesfortheoutofpitcombinationhaulroadhasbeenrevisedinthemodel(previously93volumesources,now31volumesources)andtheemissionssourceallocationwasrevised.

5. HaulRoadDimensions

ADEQrequestedthatRosemontcalculatetheinitialverticaldimensionofthehaulroadvolumesourcesusing1.7timesthetruckheightandcalculatetheinitialhorizontaldimensionofthehaulroadsusingthetruckwidthplus6meters.

ThehaulroaddimensionshavebeenupdatedperADEQ’srequest.TherevisedmethodologyanddimensionsaredescribedinSection6.8.2.1oftheDecember2017AmendedAERMODModelingReport.

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Mr.BalajiVaidyanathan‐Page3December15,2017

6. TailingsStorageAreaWindErosionFastestMileCalculation

ADEQrequestedRosemontrevisethecalculationmethodforthefastestmiletoutilizealinearregressionofhourlymeanwindspeedversuspeak2‐minutewindsusingdatafromtheTucsonAirport(Q22007‐Q12009)aswellastoadjusttheacreageforwhichthefastestmilecalculationsarebeingappliedinthemodeledscenarios.

RosemontrevisedthecalculationmethodologytousethelinearregressionproposedbyADEQ.Inaddition,thetotalacreageofthetailingsstorageareausedintheemissionscalculationhasbeenrevised.PerAP‐42,Section13.2.5‐2,emissionsgeneratedbywinderosionaredependentonthefrequencyofdisturbanceoftheerodiblesurfacebecauseeachtimethatasurfaceisdisturbed,itserosionpotentialisrestored.Adisturbanceisdefinedasanactionthatresultsintheexposureoffreshsurfacematerial.Onastoragepile,thiswouldoccurwheneveraggregatematerialiseitheraddedto,orremovedfrom,theoldsurface.DuringYear9,disturbanceswillonlyoccurina500acreportionofthetailingsstoragearea,asopposedtothe1,500acreareausedinthepreviousemissionscalculations.

Inaddition,ADEQrequestedminoradjustmentstodefaultscalingfactorsusedtocalculateemissions.Thesechangeswerefoundtobeinaccurate,andassuchwerenotincorporatedintotheemissionsormodelrevisions.

Ifyouhaveanyquestionsorcommentsabouttheinformationpresentedinthisletter,pleasedonothesitatetocallmeat(208)472‐8837.

Sincerely,

TrinityConsultants

DavidE.B.StrohmIIManagingConsultantAttachments–December,2017AmendmenttoAERMODModelingReport

cc:KatherineAnnArnold,RosemontCopper/HudbayMinerals

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ATTACHMENT 1

PROJECT REPORT Rosemont Copper Project > Pima County, AZ

Amendment to AERMOD Modeling Report

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PROJECT REPORT Rosemont Copper Project > Pima County, AZ

Amendment to AERMOD Modeling Report

PreparedBy:

ShannonK.Manoulian,P.E.‐SeniorConsultantDavidE.B.StrohmII‐ManagingConsultant

TRINITYCONSULTANTS702W.IdahoStreet

Suite1100Boise,ID83702(208)472‐8837

December2017

Project161301.0058

Environmental solutions delivered uncommonly well

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Rosemont Copper Project | Amended Model Report Trinity Consultants i

TABLE OF CONTENTS

1. EXECUTIVE SUMMARY 1-1

2. INTRODUCTION 2-1 2.1.FacilityDescription...............................................................................................................................................2‐1 2.2.SiteDescription......................................................................................................................................................2‐1

3. REGULATORY STATUS 3-1 3.1.SourceDesignation...............................................................................................................................................3‐1 3.2.AreaClassifications...............................................................................................................................................3‐1 3.3.BaselineArea..........................................................................................................................................................3‐1

4. AMBIENT DATA REQUIREMENTS 4-1 4.1.Pre‐ApplicationAirQualityMonitoring.........................................................................................................4‐1 4.2.Post‐ConstructionAirQualityMonitoring.....................................................................................................4‐2 4.3.MeteorologicalMonitoring.................................................................................................................................4‐3 4.4.BackgroundConcentrations..............................................................................................................................4‐4

4.4.1.PM10................................................................................................................................................................................................4‐4 4.4.2.NO2..................................................................................................................................................................................................4‐5 4.4.3.CO.....................................................................................................................................................................................................4‐5 4.4.4.SO2...................................................................................................................................................................................................4‐5 4.4.5.PM2.5................................................................................................................................................................................................4‐6

5. TOPOGRAPHY, CLIMATOLOGY AND METEOROLOGY 5-1 5.1.RegionalTopography...........................................................................................................................................5‐1 5.2.RegionalClimatology............................................................................................................................................5‐1 5.3.On‐SiteMeteorologicalData..............................................................................................................................5‐1 5.4.ModelingMeteorologicalData–Amended....................................................................................................5‐1

5.4.1.On–SiteData..............................................................................................................................................................................5‐1 5.4.2.SkyCoverData...........................................................................................................................................................................5‐2 5.4.3.SurfaceandUpperAirData.................................................................................................................................................5‐2 5.4.4.MeteorologicalDataProcessingforAERMOD.............................................................................................................5‐2

6. MODELING ANALYSIS DESIGN 6-1 6.1.ModelSelection......................................................................................................................................................6‐1 6.2.ModelInputDefaults/Options‐Amended....................................................................................................6‐1 6.3.Rural/UrbanClassification.................................................................................................................................6‐2 6.4.ReceptorNetwork.................................................................................................................................................6‐2 6.5.ReceptorElevations..............................................................................................................................................6‐4 6.6.ModelingDomain..................................................................................................................................................6‐5 6.7.SurfaceCharacteristics‐Amended..................................................................................................................6‐5 6.8.SourceCharacterization‐Amended................................................................................................................6‐6

6.8.1.PointSources..............................................................................................................................................................................6‐9 6.8.2.VolumeSources..........................................................................................................................................................................6‐9

6.8.2.1.RoadSources‐Amended................................................................................................................................................6‐9 6.8.2.2.OtherFugitiveParticulateSources‐Amended.....................................................................................................6‐9 6.8.2.3.GaseousEmissionsDuetoBlasting.........................................................................................................................6‐10

6.8.3.OpenPitSources.....................................................................................................................................................................6‐11 6.8.4.BermedAreas...........................................................................................................................................................................6‐11

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Rosemont Copper Project | Amended Model Report Trinity Consultants ii

6.8.5.PlumeDepletion.....................................................................................................................................................................6‐11 6.8.6.TailPipeEmissions................................................................................................................................................................6‐12

6.9.BuildingDownwash...........................................................................................................................................6‐12

7. EMISSIONS INVENTORY 7-1 7.1.AnnualCriteriaPollutantEmissionsModeling............................................................................................7‐1 7.2.Short‐TermCriteriaPollutantEmissionsModeling...................................................................................7‐1

8. DISPERSION MODELING IMPACT ANALYSIS 8-1 8.1.PrimaryStandards................................................................................................................................................8‐1 8.2.OzoneandSecondaryPM2.5‐Amended..........................................................................................................8‐1

8.2.1.OzoneImpacts............................................................................................................................................................................8‐1 8.2.2.SecondaryPM2.5Formation..................................................................................................................................................8‐4

9. EVAULATION OF DISPERSION MODELING RESULTS 9-1 9.1.CriteriaPollutantImpactResults‐AMENDED.............................................................................................9‐2 9.2.OzoneImpacts‐Amended..................................................................................................................................9‐3 9.3.SecondaryPM2.5Formation‐Amended..........................................................................................................9‐4

APPENDIX A: PM10 QUARTERLY SUMMARY A-1

APPENDIX B: PM10 DATA STATISTICAL ANALYSIS B-1

APPENDIX C: ADEQ BACKGROUND VALUE COMMUNICATIONS C-1

APPENDIX D: NOX IN-STACK RATIO DATA - AMENDED D-1

APPENDIX E: PARTICLE SIZE DISTRIBUTIONS E-1

APPENDIX F: HAUL TRUCK TRAVEL AND VMTS F-1

APPENDIX G: OZONE AND SECONDARY PM2.5 GUIDANCE G-1

APPENDIX H: MODEL SOURCE PARAMETERS H-1

APPENDIX I: DISPERSION MODEL FILES (ELECTRONIC) I-1

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Rosemont Copper Project | Amended Model Report Trinity Consultants iii

LIST OF FIGURES

Figure2‐1.GeneralLocationMap 2‐1

Figure4‐1.Former(Pre‐Application)MeteorologicalandPM10MonitoringSites 4‐2

Figure4‐2.RelocatedMeteorologicalMonitoringStation(MET‐1) 4‐3

Figure6‐1.RosemontProjectReceptorGridNetwork 6‐3

Figure6‐2.SaguaroEastNationalParkReceptorNetwork 6‐4

Figure6‐3.Year9FacilityLayout 6‐7

Figure6‐4.ProcessAreaLayout 6‐8

Figure8‐1.2006PGMDatabaseO&GSourceLocations 8‐3

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Rosemont Copper Project | Amended Model Report Trinity Consultants iv

LIST OF TABLES

Table4‐1.PM10MonitoringResults 4‐4

Table4‐2.SO2MonitoredValues 4‐6

Table6‐1.SurfaceCharacteristics 6‐6

Table8‐1.2005PGMDatabaseO&GSourcesLocationandElevation 8‐2

Table8‐2.PGMDatabaseO&GSourceClimateData 8‐4

Table9‐1ModelResults 9‐2

Table9‐22005FCAQTFEmissionsandDMX8ModelResults 9‐3

Table9‐3UT‐CO2006EmissionsandDMX8ModelResults 9‐3

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Rosemont Copper Project | Amended Model Report Trinity Consultants 1-1

1. EXECUTIVE SUMMARY

ThisamendedairqualitymodelingreportdocumentsthemethodologyandresultsoftheairqualityanalysespreparedinsupportofanArizonaDepartmentofEnvironmentalQuality(ADEQ)AirQualityClassIISyntheticMinorPermit(Permit#55223)renewalandmodificationfortheRosemontCopper(Rosemont)Project.Thisreportseekstofullydocumentandreportthemethodsandtechniquesusedtoperformthemodeling,aswellastheresultsofthemodelinganalysis,insupportoftherenewalapplication.ThisamendedreportaddressesADEQ’sComprehensiveRequestforAdditionalInformation(letterdatedSeptember26,2017)aswellasadditionalquestionsandcommentsdiscussedviaconferencecallbetweenADEQ,RosemontCopperCompany(Rosemont),andTrinityonDecember7,2017.ThespecificitemslistedintheComprehensiveRequestforAdditionalInformationandconferencecallaredescribedindetailintheaccompanyingcoverletter.

Thismodelinganalysiswasdevelopedfollowingapplicableportionsofthe(ADEQ)guidancedocument:AirDispersionModelingGuidelinesforAirQualityPermits,December2015(ADEQGuidance),theEPAGuidelineonAirQualityModels(Guidelines,40CFRPart51,AppendixW,December2016),andrecommendationsfromtheFederalLandManagers.

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2. INTRODUCTION

2.1. FACILITY DESCRIPTION

TheRosemontProjectwillincludeanopen‐pitmineandoreprocessingoperationscomprisedofcrushing,milling,flotation,concentrateandtailingsfilteringaswellaswasterockandtailingsmanagement.Theproductionscheduledevelopedfromminingsequenceplansindicatesaprojectoperatinglifeofapproximately20yearsusingonlyprovenandprobablemineralreserves.Dailyminingratesareestimatedatapproximately420,000tpdoftotalmaterial(oreandwaste)toberealizedinYear9.TheserateswilltaperofftowardthefinalyearsoftheProject.Theshort‐termminingratesfortheProjectwouldroutinelyexceedtheseaverages.

Miningoftheorewillbethroughconventionalopen‐pitminingtechniquesincludingdrilling,blasting,loading,haulingandunloading.Wasterockwillbetransportedbyhaultrucktothewasterockstorageareasaswellastoperimeterbuttressesofthetailingsfacility.Orewillbecrushedandloadedontoaconveyorfortransporttothemill(sulfideore).Thecopperandmolybdenumconcentratesfromthemillingandflotationoperationswillbeshippedoffsiteforfurtherprocessing.

2.2. SITE DESCRIPTION

TheRosemontProjectwillbelocatedinPimaCounty,approximately30milessoutheastofTucson,ArizonaasshowninFigure2‐1.Regionally,thefacilitylocationisintheSonoranDesertSectionoftheBasinandRangePhysiographicProvincewhichischaracterizedbynortherlytrending,faultblockmountainsseparatedbybroad,down‐faultedvalleys(seeFigures2‐1and4‐1).ElevationsintheProjectarearangefromabout4,600toover6,300feetabovemeansealevel.

Figure2‐1.GeneralLocationMap

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3. REGULATORY STATUS

3.1. SOURCE DESIGNATION

TheRosemontProjectwillbeanon‐categoricalstationarysource.ThepotentialtoemitofcriteriapollutantsfromthefacilitywillbebelowtheNewSourceReviewmajorsourcethresholdof250tons/year.Therefore,thefacilitywillnotbesubjecttoPreventionofSignificantDeterioration(PSD)regulations.Additionally,thepotentialtoemitofhazardousairpollutants(HAPs)willbelessthan10tons/yearforanyindividual(HAP),andlessthan25tons/yearforallHAPscombined(fugitiveandnon‐fugitivesources).Therefore,thefacilitywillnotbeamajorHAPsource.ThepotentialtoemitofcriteriapollutantsfromthefacilitywillalsobelessthantheTitleVsourcethresholdof100tonsperyear.Consequently,thefacilitywilloperateunderaClassIIPermitissuedbytheArizonaDepartmentofEnvironmentalQuality(ADEQ).

3.2. AREA CLASSIFICATIONS

TheRosemontProjectareaisclassifiedas“attainment”(betterthannationalstandards)orun‐classifiable/attainmentforparticulatematterlessthan10micronsnominalaerodynamicdiameter(PM10),particulatematterlessthan2.5micronsnominalaerodynamicdiameter(PM2.5),carbonmonoxide(CO),sulfurdioxide(SO2),nitrogendioxide(NO2),andozone(O3)(see40CFRPart81.303).

3.3. BASELINE AREA

TheRosemontProjectislocatedwithinthePimaIntrastateAirQualityControlRegion(AQCR),whichencompassesPimaCounty.ThisAQCRrepresentsthe“baselinearea”forPSDpurposes.TheRosemontProject,however,willnotbesubjecttoPSDregulations.

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4. AMBIENT DATA REQUIREMENTS

4.1. PRE-APPLICATION AIR QUALITY MONITORING

TheprimarypollutantthatwillbeemittedbytheRosemontProjectwillbeparticulatematter.Consequently,Rosemontinitiatedpre‐applicationairqualitymonitoringforPM10inJune2006.MonitoringendedinJune2009.ThelocationofthismonitoringsiteisshowninFigure4‐1.CompletequarterlydatasummaryandauditreportsweresubmittedtothePCDEQatthecompletionoftheinitialmonitoringperiod.ThesereportswereprovidedtoADEQfortheinitialpermitsubmittal.Detailsofthemonitoringprogramcanbefoundinthesequarterlyreports.ThePM10monitoringdatawereusedfortheinitialADEQ(2013)permitandwerere‐usedtodefinebackgroundconcentrationsasexplainedinSection4.4below.

EmissionsfromtheRosemontProjectoperationswillincludetailpipeemissionsfrommobileequipmentconductingminingoperations,andminorfuelcombustionsourcesusedinoreprocessingoperations.Tailpipeemissionsfrommobilesourcesarenotconsideredinapplicationsforairqualitypermits,butareincludedinairimpactanalysesforEnvironmentalImpactStatements.Thisairimpactanalysisconsideredemissionsfrombothprocesssourcesandmobilesources.TailpipeemissionsaregenerallycomprisedprimarilyofNOxandCO.

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Figure4‐1.Former(Pre‐Application)MeteorologicalandPM10MonitoringSites

4.2. POST-CONSTRUCTION AIR QUALITY MONITORING

AirQualityControlPermit#55223,Part“B”ConditionX1V.B,requiresthatwithin90dayspriortothestartupofmineoperationsRosemontmustinstall,operateandmaintainacontinuousparticulatemattermonitorattheProjectsitetomonitorambientconcentrationsofPM10.Themonitormustoperatecontinuouslyandcollectconsecutivehourlyreadings.Themonitormustalsobemaintainedtomeetrequirementssetoutin40CFRParts

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50and58andtheQualityAssuranceHandbookforAirPollutionMeasurementSystems,VolumeII,U.S.EnvironmentalProtectionAgency.

IfthemonitoreddailyaverageofPM10isgreaterthan150μg/m3,RosemontmustnotifytheDirectorbyaFAXcommunicationwithin24‐hoursofdiscovery.ThenotificationmustincludethecauseandanyactionsthatRosemontmusttaketoavoidarepeatoftheexceedance.Thepermitalsohasdatavalidationandreportingrequirements.

4.3. METEOROLOGICAL MONITORING

On‐sitemeteorologicalmonitoringwasinitiatedbyRosemontinApril2006.Completequarterlydatasummaryandsemi‐annualauditreportsweresubmittedtothePCDEQfortheperiodof2006to2009.ThesereportsareavailabletoADEQuponrequest.ThelocationoftheinitialmonitoringsiteisshowninFigure4‐1.Detailsofthemonitoringprogramcanbefoundinthequarterlyreports.

AfterJune2009,qualitycontrolchecksatthemeteorologicalmonitoringstationwerereducedsodataqualityatthatstationwasnolongerapplicableforairmodelingpurposes.AseriesofsecurityissuesalsoplaguedthestationandthestationwasmovedtoamoresecurelocationinOctober2015,asshowninFigure4‐2.Althoughregularmaintenanceisperformedattherelocatedstation,thismaintenancedoesnotcurrentlymeettherequirementssetoutinguidanceforMeteorologicalMeasurementSystems.

Figure4‐2.RelocatedMeteorologicalMonitoringStation(MET‐1)

AirQualityControlPermit#55223alsorequiresthatRosemontinstallanewmeteorologicalmonitoringstationwithin90dayspriortothestartupofmineoperations.ThisstationisrequiredtomeetspecificdatacollectionqualityrequirementsassetoutintheQualityAssuranceHandbookforAirPollutionMeasurementsSystems,VolumeIV:MeteorologicalMeasurementsandbeconsistentwithaprotocolapprovedbytheDirector.Therearealsoseveraldatacollectionandvalidationrequirementsspelledoutinthepermit.Thisstationhasnotbeeninstalledyet.

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4.4. BACKGROUND CONCENTRATIONS

CriteriapollutantsforwhichbackgroundconcentrationswereconsideredfortheRosemontProjectmodelingarePM10,PM2.5,NO2,CO,andSO2.

4.4.1. PM10

PM10measurementsinthevicinityoftheproposedRosemontProjectbeganinJune2006andendedinJune2009.Themonitoringprogramhasyieldedalittleovertwelvequartersofdata.ThequarterlysummariesarepresentedinAppendixA.

AsrequiredbytheNovember9,2005RevisiontotheAirQualityModels(40CFR51),the24‐hrPM10backgroundconcentrationwillbebasedontheaverageofthehighest24‐hrconcentrationsrecordedforeachyear.Withrespecttodeterminationofthisvalue,ambientPM10monitoringcommencedatthestartofthe3rdquarterof2006.Annualtimeperiodsarethusconsideredtorepresentthetimeperiod,JulyofoneyeartoJuneofthefollowingyear.Alistingofthehighestandsecondhighestconcentrationsforthethree‐yearperiodistabulatedinTable4‐1.

Table4‐1.PM10MonitoringResults

Year HighestConcentration(µg/m3)

2nd HighestConcentration(µg/m3)

July2006–June2007 71.3 27.0

July2007–June2008 40.3 28.2

July2008–June2009 31.6 21.2

Thelargedifferencebetweenthehighestmeasuredvalue(71.3µg/m3)andthesecondhighestvalue(40.3µg/m3)appearsanomalous.Consequently,astatisticalanalysiswasconductedonalldatatodetermineitsprobabilityofoccurrence.ThisispresentedinAppendixBandindicatesthattheprobabilityofoccurrenceofthe71.3µg/m3is5.5E‐11.Thislowprobabilityindicatesthattheconcentrationof71.3µg/m3isanoutliertothedistributionandshouldnotbeincludedindeterminingthebackgroundconcentrationsasitcannotbeexpectedtorecur.Assuch,duringthepreviouspermittingandmodelingeffort,RosemontrequestedexclusionofthePM1071.3µg/m3value‐suggestingthatthemeasurementwasastatisticaloutlier.However,uponADEQ'srequest,thefinalmodelingreportincludedthevalueintheestimatesofbackgroundambientconcentrationandwasusedtodeterminethe24‐hourPM10ambientimpactanalysis.ThisinformationwasincludedintheJuly2012AERMODModelingReportasafootnotetoTable7.1.

WhenthePM10backgroundconcentrationincludesthevalueof71.3µg/m3,anaverage24‐hrPM10backgroundvalueof47.7µg/m3results.Iftheoutlierisreplacedbythenexthighestreadingof40.3µg/m3,thebackgroundconcentrationwouldbereducedto37.4µg/m3.Although,modelingusesabackgroundof47.7µg/m3forthisanalysis,thisreportalsoincludesthebackgroundvaluesof37.4µg/m3and71.3µg/m3asfootnotesforinformationpurposes.

TheannualPM10backgroundconcentrationisbasedontheaverageoftheannualaveragesforeachoftheyearsasrequiredbytheNovember9,2005RevisiontotheAirQualityModels(40CFR51).Annualmeans,asdeterminedbytheabovereferencedcalendaryears(2006‐2009),are13.2,12and10.4µg/m3.Themeanofthesevalues,11.9µg/m3,isusedastheannualPMbackgroundconcentration.ThesevaluesareusedasthebackgroundPM10concentrationsforthefencelineandnearvicinityimpactanalysis.

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BackgroundconcentrationsfortheimpactanalysisattheSaguaroEastNationalParkarebasedonthe(2013‐2015)aerosoldatafromtheSaguaroEastNationalParkIMPROVEsite.The1sthighest24‐hrvalueof194.5µg/m3wasdeterminedtobeastatisticaloutlier.Therefore,the2ndhighest24‐hourvalueof73.26µg/m3isusedinthemodeling.Thehighestannualaveragebackgroundconcentrationof12.3µg/m3isused.

4.4.2. NO2

NitrogenDioxide,NO2,isformedbytheoxidationofnitricoxide(NO),whichisabyproductofcombustion.TheNO2monitoringsitesinArizonaarelocatedinurbanareas(PhoenixandTucson)andnearmajorcoal‐firedelectricalpowerplants(Springerville,Page,andBullheadCity).TherearenomonitoringsitesintheimmediatevicinityoftheproposedRosemontProject.Forthepreviouspermitmodeling,ADEQrecommendedaNO2backgroundconcentrationof4µg/m3forruralareaswithnomajorsourcesofNO2.ThisvalueisusedastheannualNO2backgroundconcentrationforthecurrentmodelinganalysis.

Ambient1‐hrNO2concentrationsareavailableonlyaturbanareas,nearcoal‐firedpowerplants,andaruralbackgroundsitewhereemissionsareduetominorvehicletrafficandoutboardmotorboats(i.e.,AlamoLakeinArizona).TheRosemontsiteissimilartotheAlamoLakesiteinthattheonlysourcesofNO2areminorvehicletrafficonaroadapproximately2.5milesfromthesite.Thehighestrecordedbackground1‐hrNO2concentrationsattheAlamoLakesite,measuredduringatwoyearmonitoringprogram(2014‐2015),were26.3µg/m3and13.2µg/m3.Thus,thehighestofthetwoyears,26.3µg/m3isusedasthe1‐hrbackgroundNO2concentration.ThisvalueisalsousedforbackgroundattheSaguaroEastNationalPark.

4.4.3. CO

COisproducedbytheincompletecombustionoffuelswithanthropogenicactivities(automobiles,constructionequipment,lawnandgardenequipment,commercialandresidentialheating,etc.)andrepresentsamajorsourceofemissions.Consequently,theCOmonitoringsitesinArizonaarelocatedexclusivelyinurbanareas(Phoenix,TucsonandCasaGrande).Thus,therearenorepresentativemonitoringstationstodeterminebackgroundCOconcentrationsfortheRosemontProjectsite.

Forthepreviousmodelingeffort,andforboththe1‐hourand8‐houraveragingperiods,ADEQrecommendedaCObackgroundconcentrationof582µg/m3forruralareaswithnomajorsourcesofCO(forcommunicationswiththeADEQseeAppendixC).ThisvalueisusedasthebackgroundCOconcentrationforthefenceline,nearvicinity,andfortheSaguaroEastNationalParkImpactanalysis.

4.4.4. SO2

Forthepreviousmodeling,ADEQrecommendedtheuseofSO2backgroundconcentrationsforruralareaswithnomajorsourcesofSO2.ADEQrecommendedthefollowingconcentrationsforthe3‐hour,24‐hour,andannualaveragingperiods:43µg/m3,17µg/m3,and3µg/m3,respectively(forcommunicationswiththeADEQ,seeAppendixC).ThesevaluesareusedasbackgroundSO2concentrationsforthefencelineandnearvicinityimpactanalysisaswellasfortheSaguaroEastNationalParkImpactanalysis.

SulfurdioxideemissionsfromtheRosemontProjectoperationsareproducedfromblastingoperationsandtheuseofultra‐lowsulfurdieselfuel.Emissionsareverysmall.Background1‐hrSO2dataisnotavailableasallhistoricdatahasbeencompiledforcomparisonwithapplicablestandards,i.e.3‐hr,24‐hrandannualSO2standards.TheclosestsourceofSO2emissionsinthevicinityoftheRosemontProjectistheTucsonElectricalPowerStation(TEP).Itisapproximately50KmfromtheproposedRosemontProjectsite.EmissioninformationforTEPiscurrentlyunavailabletoevaluateanyimpacttothebackgroundconcentrationsinthevicinityoftheRosemontProject.Historically,theprincipalsourceofSO2emissionsinArizonahasbeenfromthesmeltingof

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copperandfromcoalfiredpowerplants.UrbanareasalsorepresentamajorsourceofSO2emissions.Thus,theSO2monitoringsitesinArizonaarelocatedinthehistoricalsmeltingareas(Miami,Globe,Hayden),nearpowerplants(Springerville,PageandBullheadCity),andinurbanareas(PhoenixandTucson).AlthoughsourcesinurbanareasarenotrepresentativeofemissionssourcesinthevicinityoftheRosemontProject,theuseofurbanSO2monitoringdatawillrepresentaconservativeestimateofbackgroundconcentrations.

Theaverage99thpercentile1‐hourimpactfromtheChildren’sParkmonitorintheTucsonarea,andtheCentralPhoenix,DurangoComplex,andtheJLGSupersiteinthePhoenixareawereusedtodetermine1‐hourSO2backgroundfortheProject.Themonitoredvaluesfortheyears2013‐2015areshowninTable4‐2below.Thehighestaveragebackgroundof22.6μg/m3isusedinthemodeling.

Table4‐2.SO2MonitoredValues

Site/Monitor 2013

1‐hr99thPercentile(μg/m3)

2014


2015


Average

(μg/m3)

Children’sPark(40191028)

18.3 15.7 13.1 15.7

CentralPhoenix(40133002)

20.9 18.3 18.3 19.2

DurangoComplex(40139812)

23.5 20.9 23.5 22.6

JLGSupersite(40139997)

15.7 13.1 13.1 14.0

4.4.5. PM2.5

IntheabsenceofanyrepresentativePM2.5monitoringstationintheclosevicinityoftheRosemontProjectsite,theChiricahuaNationalMonumentIMPROVEPM2.5monitoringstationdatawasused.The3year(2013‐2015)98thpercentileaverageofthemaximum24‐hrconcentrationswas9.3µg/m3.The3yearaverageoftheannualaverageconcentrationsis3.2µg/m3.ThesevaluesareusedasbackgroundPM2.5concentrationsforthefencelineandnearvicinityimpactanalysis.BackgroundconcentrationsfortheimpactanalysisattheSaguaroEastNationalParkarebasedonthe(2013‐2015)aerosoldatafromtheSaguaroEastNationalParkIMPROVEsite.The24‐hrandannualaveragebackgroundPM2.5concentrationsof11.2µg/m3and4.3µg/m3,respectively,areused.

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5. TOPOGRAPHY, CLIMATOLOGY AND METEOROLOGY

5.1. REGIONAL TOPOGRAPHY

TheRosemontProjectwillbelocatedintheSantaRitaMountainswhichtrendnortheasttosouthwestwithelevationsatthesiterangingfromabout4,600feettoover6,300feetamsl(Figure4‐1).TothewestofthemountainsliesthebroadSantaCruzRiverValleyandtotheeastliesasmallervalleybisectedbyCienegaCreek.

5.2. REGIONAL CLIMATOLOGY

Theclimateoftheareaissemi‐aridwithprecipitationvaryingwithelevationandseason.The30‐yearnormal(1971to2000)annualaverageprecipitationfortheSantaRitaExperimentalRangestation,locatedtothewestoftheProjectsiteandtheSantaRitaMountainRange,is23.41inches(WesternRegionalClimateCenter).Overthis30‐yearperiod,nearlyhalfoftheprecipitationoccurredinthemonthsassociatedwiththeArizonamonsoonofJuly,AugustandSeptember.TheleastamountofprecipitationoccurredduringthemonthsofApril,MayandJune.

Temperaturesregionallyaremoderatetoextremewithmaximumsandminimumsalsovaryingwithelevation.The30‐yearnormalaveragemonthlymaximumtemperaturesattheSantaRitaExperimentalRangestationrangedfromalowof60.4°FinJanuarytoahighof93.3°FinJune.Averagemonthlyminimumtemperaturesrangedfromalowof37.5°FinDecemberandJanuarytoahighof66.8°FinJuly.

5.3. ON-SITE METEOROLOGICAL DATA

Fortheoriginalmodelingeffort,anon‐sitemeteorologicalstationwasinstalledatalocationthatwasnearthecenteroftheproposedopenpit.Whilethislocationwasdeemedtobeappropriateformodelingpurposes,thepublicraisedconcernsbecausethelocationwasseparatedfromthePM10ambientmonitoringstation.Thismeteorologicalstationprovidedinformationsuchaswindspeedanddirection,temperature,precipitation,andsomeevaporationdata.ThedatavalidationandsensormaintenanceprocesswasreducedoncetheoriginaldatasetwascompleteafterJune2009.Asstatedpreviously,maintenanceandsecurityconcernsresultedintheinstallationofanewstationinOctober2015.ThesestationlocationsareshowninFigures4‐1and4‐2.Althoughanewstationwasinstalled,onsitemeteorologicaldatadoesnotmeetauditingordataqualityobjectivesforuseindispersionmodeling.Asaresult,modeledmeteorologicaldatawasdevelopedtoprovideanaccurateassessmentofonsiteconditions.

5.4. MODELING METEOROLOGICAL DATA – AMENDED

Theon‐sitemeteorologicaldatasetusedinthisanalysiswasprocessedusingthemostcurrentversionofAERMET(version16216)toensurecompatibilitywiththeupdatedversionofAERMOD.

5.4.1. On –Site Data

Themodelingwasbasedupontheon‐siteweatherobservationsfromtheRosemontmonitoringsite.ParametersmeasuredattheRosemontmonitoringsiteincludeambienttemperatureat2meters,differentialtemperaturebetween2and10meters,andwindspeedandwinddirectionat10meters.

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Theon‐sitemonitoringbeganinApril2006.Thedatabase,however,isnotcontinuousasdatabetweenDecember2006andFebruary2007werelostduetoadataloggermalfunction.Therefore,themodelingwasconductedbasedupon2fullyearsofon‐sitedata(March2007‐February2009),sothatdatasubstitutionwasnotrequired.Thetwoyearsofon‐sitedatameetsEPA’sAppendixWguideline,whichstatesthat5yearsofNWSmeteorologicaldataoratleastoneyearofsite‐specificdatashouldbeused(Section8.3.1.2,AppendixW).Thedatausedshouldalsobeadequatelyrepresentativeofthestudyarea.

5.4.2. Sky Cover Data

ThemodelingwasconductedusingtheguidelinemodeldevelopedbytheEPAinconjunctionwiththeAmericanMeteorologicalSocietycalledtheAMS/EPARegulatoryModel(AERMOD).AERMODisexplainedfurtherbelow.AERMODrequiresparametersfordeterminingboundarylayerconditions,whichincludeopaqueskycover(ortotalskycover).TheRosemonton‐sitesurfacemeasurementsdonotincludeskycoverdata.Consequently,theconcurrentskycoverdatafortheon‐sitesurfacemeasurementswasobtainedfromtheNWSTucsonAirport(WBAN23160).

5.4.3. Surface and Upper Air Data

AERMODalsorequiresupperairdata.Upperairdataconcurrentwiththeon‐sitedatawasobtainedfromtheNWSTucsonAirportstation(WBAN23160).TheNWSTucsonstationistheclosestNWSstationwithupperairdata,andalsothecloseststationwithNWSAutomatedSurfaceObservingSystem(ASOS)data.BoththesurfaceandupperairdataforTucsonAirportwasprovidedbyADEQwithgapfilling,andnoadditionalmodificationsweremadebyTrinitytothedatasets.

5.4.4. Meteorological Data Processing for AERMOD

TheRosemonton‐sitedataandtheNWSTucsonAirportsurfaceandupperairdatawerecombinedintoAERMODreadysurfaceandupperairinputfilesusingtheEPAAERMETcomputerprogram(User’sGuidefortheAERMODMeteorologicalPreprocessor(AERMET),U.S.EnvironmentalProtectionAgency,OfficeofAirQualityPlanningandStandards,AirQualityAssessmentDivision,AirQualityModelingGroup,ResearchTrianglePark,NorthCarolina,EPA‐454/B‐16‐010,December2016).TheAERMETprogramservesasthemeteorologicalpreprocessorforAERMOD.AERMETisdesignedtocombine,andprovidequalitycontrolof,on‐siteandNWSsurfaceandupperairdataforusebyAERMOD.AdescriptionoftheAERSURFACEdataisprovidedinSection6.7.AllAERMETinputandoutputprocessingfileshavebeenprovidedwiththeelectronicmodelingfilesaccompanyingthisreport(AppendixI).

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6. MODELING ANALYSIS DESIGN

6.1. MODEL SELECTION

AnevaluationofthemaximumambientairqualityimpactsfromtheproposedRosemontProjectwasconductedusingAERMODversion16216r(User’sGuidefortheAMS/EPARegulatoryModel–AERMOD,U.S.EnvironmentalProtectionAgency,OfficeofAirQualityPlanningandStandards,Emissions,Monitoring,andAnalysisDivision,ResearchTrianglePark,NorthCarolina,EPA‐454/B‐03‐001,September2004).TrinityConsultants,Inc.(Trinity)usestheenhancedversionofAERMODfromBREEZESoftware.

6.2. MODEL INPUT DEFAULTS/OPTIONS - AMENDED

TherecommendedregulatorydefaultoptionsforAERMOD,asstatedintheGuidelines,wereusedforthemodelruns.TheregulatorydefaultoptionsinAERMODincludetheuseofstack‐tipdownwash,incorporationoftheeffectsofelevatedterrain,andcalmsandmissingdataprocessingroutines.

ThemissingdataprocessingroutinesthatareincludedinAERMODallowthemodeltohandlemissingmeteorologicaldataintheprocessingofshort‐termaverages.Themodeltreatsmissingmeteorologicaldatainthesamewayasthecalmsprocessingroutine(i.e.,itsetstheconcentrationvaluestozeroforthathourandcalculatestheshort‐termaveragesaccordingtoEPA'scalmspolicy,assetforthintheGuidelines).Calmsandmissingvaluesaretrackedseparatelyforthepurposeofflaggingtheshort‐termaverages.Anaveragethatincludesacalmhourisflaggedwitha'c',anaveragethatincludesamissinghourisflaggedwithan'm',andanaveragethatincludesbothcalmandmissinghoursisflaggedwitha'b'.Ifthenumberofhoursofmissingmeteorologicaldataexceeds10percentofthetotalnumberofhoursforagivenmodelrun,acautionarymessageiswrittentothemainoutputfile,andtheuserisreferredtoSection5.3.2ofOn‐siteMeteorologicalProgramGuidanceforRegulatoryModelingApplications(EPA,1987).

TheDecember2016updatestoAppendixWincludetheincorporationoftheexistingdetailedscreeningoptionoftheOzoneLimitingMethod(OLM)andPlumeVolumeMolarRatioMethod(PVMRM)intotheregulatoryversionofAERMOD.TheOLMwasusedtoevaluatetheimpactofNO2inthenearvicinityofRosemontProjectaswellasatSaguaroEastNationalPark.TheOLMinvolvesaninitialcomparisonoftheestimatedmaximumNOxconcentrationandtheambientozoneconcentrationtodeterminethelimitingfactorintheformationofNO2.IftheozoneconcentrationisgreaterthanthemaximumNOxconcentration,totalconversionisassumed.IftheNOxconcentrationisgreaterthantheozoneconcentration,theformationofNO2islimitedbytheambientozoneconcentration.Themethodalsousesacorrectionfactortoaccountforin‐stackconversionofNOxtoNO2.

HourlybackgroundozonedatafortheperiodMarch2007throughFebruary2009(tocoincidewiththemeteorologicaldataperiodusedforthemodeling)fromtheCASTNETChiricahuaNationalMonumentsitewasused.Withregardtobackgroundozonemonitoringdata,theChiricahuaNationalMonumentsiteisthemostrepresentativeoftheterrainandconditionsattheRosemontsite.ThehourlyozonefilewasprovidedbyADEQandisthesamedatafileusedinthepreviouspermitmodeling.ModelingfortheRosemontProjectwasconductedusinganin‐stackNO2/NOxratioof0.05fortailpipeemissionsfromhaultrucks.ManufacturerdatasuggestingalowerNO2/NOxratiohasbeenprovidedinAppendixD;however,forconservatismandtobeconsistentwithpreviousmodeling,themodelingusedtheratioof0.05.Anin‐stackratioof0.065wasusedforstationaryengines;thisratioisbasedontheaverageofsimilarenginesfoundinEPA’sNO2/NOxIn‐StackRatio(ISR)Database(https://www3.epa.gov/scram001/no2_isr_database.htm).Thedatabasewassortedbyenginetype,fuel,andenginecapacity.TheaverageoftheratiosforreciprocatingICdieselenginesratinginsizefrom400kWtoapproximately1900kWwasusedtocalculatetheaverageforuseinthemodel.ThedatausedtocalculatetheaverageisincludedinAmendedAppendixD.TheNO2/NOxratioforblastingsourcesisbasedon

PNB000760


fieldtestdatapresentedinNOxEmissionsfromBlastingOperationsinOpen‐cutCoalMining(Attalla,etal,2008).Amaximumin‐stackratioof0.08(roundedto0.10forinputinthemodel)wascalculatedbasedonANFOblastingplumemeasurementresultsfromblastingwithANFO.TheAttalla,etalpaperisincludedinAmendedAppendixD.

6.3. RURAL/URBAN CLASSIFICATION

Formodelingpurposes,therural/urbanclassificationofanareaisdeterminedbyeitherthedominanceofaspecificlanduseorbypopulationdatainthestudyarea.Generally,ifthesumofheavyindustrial,light‐moderateindustrial,commercial,andcompactresidential(singleandmultiplefamily)landuseswithinathreekilometerradiusfromthefacilityaregreaterthan50%,theareaisclassifiedasurban.Conversely,ifthesumofcommonresidential,estateresidential,metropolitannatural,agriculturalrural,undeveloped(grasses),undeveloped(heavilywooded)andwatersurfaces,landuseswithinathreekilometerradiusfromthefacilityaregreaterthan50%,theareaisclassifiedasrural.Alternatively,ifthepopulationisgreaterthan750personsperkm2,theareaisalsoclassifiedasurban.

AsshownintheaerialphotographinFigure2‐1andthetopographicmapinFigure4‐1,rurallanduseintheareasurroundingtheproposedRosemontProjectismuchgreaterthan50%.Thus,theruralclassificationwasusedinthemodeling.

6.4. RECEPTOR NETWORK

FollowingtheADEQGuidance,thereceptorgrid(seeFigure6‐1)consistingofthefollowingwasmodeled:

receptorsspacedat25metersalongtheProcessAreaBoundary(PAB); receptorsspacedat100metersfromthePABto1kilometer; receptorsspacedat500metersfrom1kilometerto5kilometers;and receptorsspacedat1000metersfrom5kilometersto10kilometers.

BasedontherecommendationsbytheForest,asecondreceptorgridconsistingofreceptorsattheSaguaroEastNationalParkwasalsomodeled(seeFigure6‐2).ThesereceptorswereobtainedfromtheClassIAreaReceptorDatabasedevelopedbytheForest.

PNB000761


Figure6‐1.RosemontProjectReceptorGridNetwork

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Figure6‐2.SaguaroEastNationalParkReceptorNetwork

*SaguaroEastNationalParkreceptorsdownloadedfromtheNationalParkService(NPS)AirResourcesDivision(ARD)databaseofmodelingreceptorsforalloftheClassIareasintheUnitedStates(https://www.nature.nps.gov/air/maps/Receptors/index.cfm)

6.5. RECEPTOR ELEVATIONS

TheU.S.GeologicalSurvey(USGS)hasdevelopedaNationalElevationDataset(NED).TheNEDisaseamlessmosaicofbest‐availableelevationdata.The7.5‐minuteelevationdataforthecontinentalUnitedStatesaretheprimaryinitialsourcedata.ReceptorelevationsweredeterminedfromtheNED1/3arcseconddata,obtainedfromtheMulti‐ResolutionLandCharacteristicsConsortium(MRLC)inhorizontaldatumofNAD83,andvertical

RosemontProject

SaguaroEastNationalParkReceptors

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datumofNAVD88.The7.5‐minuteDEMprovidescoveragein7.5X7.5‐minuteblocks.Eachfileprovidesthesamecoverageasastandard1:24,000scalequadranglemap.

TheNEDdatawasprocessedwithAERMAP(User’sGuidefortheAERMODTerrainPreprocessor(AERMAP),U.S.EnvironmentalProtectionAgency,OfficeofAirQualityPlanningandStandards,Emissions,Monitoring,andAnalysisDivision,ResearchTrianglePark,NorthCarolina,EPA‐454/B‐03‐003,October2004).AERMAP,likeAERMET,isapreprocessorprogramthatwasdevelopedtoprocessterraindatainconjunctionwithalayoutofreceptorsandsourcestobeusedinAERMOD.Forcomplexterrainsituations,AERMODcapturestheessentialphysicsofdispersionincomplexterrainandtherefore,needselevationdatathatconveythefeaturesofthesurroundingterrain.Inresponsetothisneed,AERMAPfirstdeterminesthebaseelevationateachreceptor.AERMAPthensearchesfortheterrainheightandlocationthathasthegreatestinfluenceondispersionforeachindividualreceptor.Thisheightisreferredtoasthehillheightscale.BoththebaseelevationandhillheightscaledataareproducedbyAERMAPasafileorfileswhicharetheninsertedintoanAERMODinputcontrolfile.ThefilesproducedbyAERMAPforthemodelingareprovidedelectronicallytoADEQaspartofthismodelingreport(AppendixI).Elevationsofon‐sitesourcesandbuildingsarebasedonelevationsfromYear9oftheMinePlan.

6.6. MODELING DOMAIN

TheAERMAPterrainpreprocessorrequirestheusertodefineamodelingdomain.Themodelingdomainisdefinedastheareathatcontainsallthereceptorsandsourcesbeingmodeledwithabuffertoaccommodateanysignificantterrainelevations.Significantterrainelevationsincludealltheterrainthatisatorabovea10%slopefromeachandeveryreceptor.

BREEZE’ssoftwareautomaticallycalculatesthemodelingdomainbasedonthereceptorgridbeingusedandidentifieseach7.5‐minuteDEMquadranglethatmustbeusedinAERMAPtomeetthe10%sloperequirement.AlistingoftheDEMquadranglesdefiningthemodelingdomainforthemodelingproposedhereinisprovidedtoADEQinthisreport.

6.7. SURFACE CHARACTERISTICS - AMENDED

Surfaceconditionsatthemeasurementsite,referredtoassurfacecharacteristics,influencetheboundarylayerparameterestimatesgeneratedbyAERMOD.Obstaclestothewindflow,theamountofmoistureatthesurface,andreflectivityofthesurfaceallaffecttheboundarylayerestimates.Theseinfluencesarequantifiedthroughthesurfacealbedo,Bowenratioandroughnesslength,andareintroducedintoAERMODthroughthefilesgeneratedbyAERMET.

Thealbedoisthefractionoftotalincidentsolarradiationreflectedbythesurfacebacktospacewithoutabsorption.Typicalvaluesrangefrom0.1forthickdeciduousforeststo0.90forfreshsnow.ThedaytimeBowenratio,anindicatorofsurfacemoisture,istheratioofthesensibleheatfluxtothelatentheatfluxandisusedfordeterminingplanetaryboundarylayerparametersforconvectiveconditions.WhilethediurnalvariationoftheBowenratiomaybesignificant,theBowenratiousuallyattainsafairlyconstantvalueduringtheday.MiddayvaluesoftheBowenratiorangefrom0.1overwaterto10.0overdesert.Thesurfaceroughnesslengthisrelatedtotheheightofobstaclestothewindflowandis,inprinciple,theheightatwhichthemeanhorizontalwindspeediszero.Valuesrangefromlessthan0.001moveracalmwatersurfaceto1mormoreoveraforestorurbanarea.Thevaluesforsurfacealbedo,BowenratioandroughnesslengthcanbeenteredintotheAERMETpreprocessorbasedonfrequencyandsector.Thefrequencydefineshowoftenthesecharacteristicschange,oralternatively,theperiodoftimeoverwhichthesecharacteristicsremainconstant.

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Thefrequencydefineshowoftenthesecharacteristicschange,oralternatively,theperiodoftimeoverwhichthesecharacteristicsremainconstant.Thefrequencycanbeannual,seasonal(winter[December,January,February],spring[March,April,May],summer[June,July,August],fall[September,October,November]),ormonthly,correspondingto1,4,or12periods,respectively.

Sectorsrefertothenumberofnon‐overlappingsectorsintowhichthe360°compassisdivided.Aminimumof1andamaximumof12sectorscanbespecified(i.e.,1sectorof360°,upto12non‐overlappingsectorsof30°).Thus,AERMETallowsthevaluesforsurfacealbedo,Bowenratioandroughnesslengthtobeenteredannually,seasonallyormonthlyforeachsector,thenumberofwhichcanrangebetween1and12.AsshowninFigure4‐1,theareasurroundingtheproposedRosemontProjectisundeveloped,andconsistsofpinyon‐junipermountainousterraininalldirections.Consequently,surfacecharacteristicswereenteredforasinglesector.

TheEPAhasdevelopedacomputerprogramcalledAERSURFACEtoaidusersinobtainingrealisticandreproduciblesurfacecharacteristicvaluesforthealbedo,Bowenratio,andsurfaceroughnesslengthforinputtoAERMET.Theprogramusespubliclyavailablenationallandcoverdatasetsandlook‐uptablesofsurfacecharacteristicsthatvarybylandcovertypeandseason.

Thesurfacecharacteristicsthatwereusedinthemodelingvarybyseasonandwindsector.TherangeofvaluesforeachparameterisshowninTable6‐1.ThevalueslistedinTable6‐1weregeneratedbyAERSURFACE.

Table6‐1.SurfaceCharacteristics

SurfaceCharacteristic Spring Summer Autumn Winter

Albedo 0.25 0.25 0.25 0.25

BowenRatio 2.88 3.76 5.70 5.70

SurfaceRoughness 0.153 0.153 0.153 0.152

GeneratedbyAERSURFACE,dated130106CenterUTMEasting(meters):522896.0;CenterUTMNorthing(meters):3521802.0;UTMZone:12,Datum:NAD83Studyradius(km)forsurfaceroughness:1.0Airport?N,Continuoussnowcover?NSurfacemoisture?Average,Aridregion?Y(semi‐arid),Month/Seasonassignments?DefaultLateautumnafterfrostandharvest,orwinterwithnosnow:1212Winterwithcontinuoussnowontheground:0Transitionalspring(partialgreencoverage,shortannuals):345Midsummerwithlushvegetation:678;Autumnwithun‐harvestedcropland:91011

6.8. SOURCE CHARACTERIZATION - AMENDED

AplanviewmapdepictingthefacilitylayoutbyYear9ispresentedinFigure6‐3.Apreliminaryplanviewoftheancillaryoperations,toincludelocationsoftheprimarycrusherandflotationoperations,ispresentedinFigure6‐4.FinaldesigndocumentsfortheRosemontProjectFacilitiesarebeingdevelopedandtherefore,adetailedlistingofallemissionsourcesandtheircorrespondingmodelinginputreleaseparametersandemissionratescannotbeprovidedwiththisreport.Ageneraldescriptionofhoweachsourcetypewastreatedispresentedbelow.

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Figure6‐3.Year9FacilityLayout

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Figure6‐4.ProcessAreaLayout

LABORATORYDUSTCOLLECTORS

N:57207’E:20503’Z:5050’

CHANGEHOUSE/LAB

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6.8.1. Point Sources

PointsourcesattheRosemontProjectincludedustcollectorsandemergencygenerator(s).Emissionsfromthesesourcesweremodeledasindividualpointsources.Stackparametersforthepointsourcesarebasedondesignparametersand/orconservativeestimatedvalues.Emissionsfromemergencygeneratorswereincludedinthemodelingeventhoughmostotheroperationswouldbeshutdownifthegeneratorsareneeded.ThePointsourceemissionsweremodeledusingtheparticlesizedistributionshowninTableE.5ofAppendixE.

6.8.2. Volume Sources

6.8.2.1. Road Sources - Amended

Arefinedroadnetworkwasdevelopedtodepicttheanticipatedhaultruckroutesanddumpinglocationsduringtheyearofthemineplanwiththeestimatedgreatestemissions,whichisthebasisoftheemissionsinventorythatwasusedforallofthemodeling.EmissionsduetohaulroadandgeneralplanttrafficontheunpavedportionoftheroadnetworkweremodeledasvolumesourcesandthemodelingparameterswerebasedonguidancefromADEQandtheAERMODUser’sGuide.Thismethodisconsistentwiththemethodologyusedforthepreviouspermitapplicationandmodeling.Themodelingparametersweresetasfollows:

thevolumeheightwassetequalto1.7timestheheightofthevehiclesgeneratingtheemissions; theinitialverticaldimensionwassetequaltothevolumeheightdividedby2.15; thereleaseheightwassetequaltohalfofthevolumeheight;and theinitiallateraldimensionwassettothewidthofthehaultrucksplus6metersdividedby2.15;theroadwasfurtherdividedintotwolanesrepresenting2‐waytraffic.

Themajorityofemissionsonthehaulroadnetworkareduetolargehaultrucks.Theheightofthehaultrucksobtainedfromthemanufacturer’sdata(frontcanopyheight,Caterpillar793FMiningTruck)is6.6meters(21.6feet).Thus,foreachroadsourcethevolumeheightwassetto11.22meters(1.7timestheheightofthevehiclesgeneratingtheemissions),theinitialverticaldimensionwassetto5.22meters(volumeheightdividedby2.15),andthereleaseheightwassetto5.61meters(halfofthevolumeheight).

Thehaultruckwidthwasestimatedtobe8.31meters(overallcanopywidth,Caterpillar793FMiningTruck).Thus,theinitiallateraldimensionforeachvolumewassetto6.65meters(14.31meters[haultruckwidthof8.31metersplus6meters]dividedby2.15).Theroadsourceswereplacedalongtheroadnetworkatapproximately25‐meterintervals.Thedistributionofhaulroademissionsgeneratedinsidethepitversusoutsidethepitweretakenintoaccountwhilespreadingouthaulroademissionsgeneratedbythehaultrucksamongtheopenpitsourcesandtheroadsources.ThehaulroademissionsweremodeledusingtheparticlesizedistributionshowninTableE.1ofAppendixE.RoadwaybaseelevationsweredevelopedbasedontheYear9mineplanninglayout.ThiscoincideswiththemaximumemissionsyearfortheProjectandthemininginputsusedintheemissionscalculations.

AllocationofemissionstotheroadsourcesfortheshorttermaveragingperiodsisshowninAppendixH.ItshouldalsobenotedthatwasterockhaulingwasallocatedbetweentheportionsofthewasterockhaulroadslocatedbothinandoutofthepitfortheannualNAAQSperiods.Thiswastoensurethatunpavedroadandtailpipeemissionsweredistributedaccuratelyforthelongeraveragingperiods.

6.8.2.2. Other Fugitive Particulate Sources - Amended

Otherfugitiveparticulateemissionsourcesthatweremodeledasvolumesourcesincludethefollowing:

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Fugitiveemissionsfromtruckunloadingattheprimarycrusherwererepresentedbyasinglevolumesource.Thesidelengthwassetto12meters(approximatewidthofdumppocket),therefore,theinitialhorizontaldimensionwassetto2.79meters(12/4.3).Theverticallengthwassetto1meter(verticaldropofdumppocket).Consequently,theinitialverticaldimensionwassetto0.47meters(1/2.15)andthereleaseheightwassetto0meters(dumppocketisatgradelevel).

FugitiveemissionsduetowinderosionfromtheROMstockpilewererepresentedbyasinglevolumesource.Thesidelengthobtainedfromthemapwas318meters(averagewidthofthestockpile),thereforetheinitialhorizontaldimensionwassetto74meters(318/4.3).Theverticalwassetto12meters(averageheightofstockpile).Consequently,theinitialverticaldimensionwassetto5.6meters(12/2.15)andthereleaseheightwassetto6meters(halfofthevolumeheightof12meters).

Fugitiveemissionsduetowinderosionofthetailingsstorageareawererepresentedbythreevolumesourcesinordertomostadequatelyrepresentthepolygonlayoutandorientationoftheactivetailingplacementarea.Asvolumesourcesare‘drawn’inthemodelassquares,theuseofthreevolumesourceswaschosentorepresenttheirregularshapeofthetailingsstoragearea,whichcanbeapproximatedbythreesquareareas.ThetotalactiveareaoftailingsplacementatYear9wasdeterminedtobeapproximately2,023,428m2(500acres).Theareawasthendividedinto3equalsub‐areasof674,476m2each,whicharerepresentedinthemodelasvolumesource‘squares’.Eachvolumesource‘square’hasasidelengthof821.26meters;therefore,theinitialhorizontaldimensionwassetto190.99meters(821.26/4.3).Theverticallengthofallsourceswassetto12meters(approximateheighteachliftofthetailingsstoragearea);therefore,theverticaldimensionwassetto5.58meters(12/2.15).Thereleaseheightforallsourceswassetto6meters(halfofthevolumeheightof12meters).TheactiveYear9tailingsareaislargerthantheactivetailingsareainsubsequentyears.Asthetailingsstoragegrowsverticallyitmustcontracthorizontallyforstability,muchlikeconstructingapyramid.

Fugitiveemissionsfromtransferpointswererepresentedbysinglevolumesources.Thesidelengthwassetto2meters(approximateaveragewidthofthetransferpoints);therefore,theinitialhorizontaldimensionwassetto0.47meters(2/4.3).Theverticallengthwassetto3meters(approximateheightofmaterialdrops).Consequently,theinitialverticaldimensionwassetto0.7meters(3/4.3),andthereleaseheightwassetto3meters(assumedheightofthetransferpoints).

Forallofthefugitiveemissionssources,baseelevations,sourcedimensionsandsourcelocationsweredevelopedutilizingthemineplanningdrawingforYear9oftheminelife.Thiscoincideswiththemaximumemissionsyearfortheprojectandthemininginputsusedintheemissionscalculations.

TheabovematerialtransferemissionsweremodeledusingtheparticlesizedistributionshowninTableE.2ofAppendixE.

6.8.2.3. Gaseous Emissions Due to Blasting

Thegaseousemissionsduetoblastinginthepitweremodeledasvolumesources.Thefugitivegaseousemissionsduetoblastinginthepitwerespaced(arbitrarilyselected)overthepitarea.Thesidelengthofeachvolumesourcewassetat61.0meters(representingtheaveragewidthofablast);therefore,theinitialhorizontaldimensionwassetto14.2meters(61.0/4.3).

Ablastcouldsendemissions20metersintotheair.Consequently,aconservativeverticaldimensionof20meterswasassignedtothevolumesourcesrepresentingtheblastingemissions.Thustheinitialverticaldimensionofeachsourcewassetto9.3meters(20/2.15)andthereleaseheightwassetto10meters(1/2ofthe

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verticaldimensionof20meters).Thebaseelevationforthevolumesourcesinthepitwassettotheelevationoftheterraindefiningthebottomofthepit,basedontheassumptionthattheseemissionsmustriseabovethewallsofthepitbeforebeingdisperseddownwind.SincetheRosemontProjectanticipatesroutineblastingtooccurbetween12PMand4PM,thevariableemissionrateoptionHROFDYinAERMODwasusedtomodeltheemissionsbetweentheabove4‐hourintervalseveryday.ThePM10emissionsfromblastingwerealsomodeledasavolumesourceandusedtheparticlesizedistributionshowninTableE.3,AppendixE.Forevaluatingthe1‐hraveragedimpactsfromNO2,SO2andCO,blastingemissionsweresettooccureveryhourbetween12PMto4PM.Testmodelingrunsfromthepreviousmodelingindicatedthatthemaximumimpactduetoblastingemissionsoccurredat4PMeveryday.Therefore,forallimpactevaluationsgreaterthanthe1‐hraveragedimpacts,blastingwassettooccurat4PMeveryday.TheHROFDYvariableemissionsrateoptioninAERMODwasusedforthis.

6.8.3. Open Pit Sources

Fugitiveparticulateemissionsoccuratonesource,whichischaracterizedasanopenpit.Thisisthemainminepit.

Theopenpitsourceparameters,easterlylength,northerlylengthandvolume,werebasedonthelengthandwidthdimensionsoftherectangledrawntosimulatethepitshapeinthemodelandtheanticipateddepthofthepit.Thereleaseheightwassettozero.

TheopenpitsourceoptionintheAERMODmodelrequiresparticlesizedistributiondataintheformofthemass‐meanparticlediameter,massweightedsizedistribution,andparticledensity.TableE.1ofAppendixEshowstheparticlesizedistributiondevelopedforhaulroademissions.Thisdistributionwasusedfortheopenpitsourcesinceamajorityoftheemissionsinthepitarehaulroademissions.AllocationofemissionstotheopenpitsourcesisshowninAppendixH.

Aparticledensityof2.44gm/cm3,theotherrequiredinputvariable,wasusedinthemodelingasarepresentativevalueoftheaveragedensityofthevariousrockmaterials(overburden,wasterock,ore)thatwillbemined.

6.8.4. Bermed Areas

Thewasterockareaissurroundedbyelevatedbermsthatarebuiltpriortoeachsectionofwasterockbeingplaced.Thisresultsinreducedwindspeedswithinthewasterockstoragearea,whichproducespitemissionretentionjustlikeanopenpit.Asaresult,openpitsourceswereusedforeachoftheseemissionssources.Thisisonlyusedforparticulatepollutantmodeling.

TheopenpitsourceparametersforthewasterockareaweredeterminedasdescribedinSection6.8.3above.

6.8.5. Plume Depletion

OneotheroptionintheAERMODmodelrequiresparticlesizedataasexplainedaboveinSection6.8.3.ThisoptionisknownasDDEP,whichspecifiesthatdrydepositionfluxvalueswillbecalculated.Thisoption,whichwasselectedinthemodeling,automaticallyincludesdryremoval(depletion)mechanisms(knownasdryplumedepletion[DRYDPLT]intheoldISCmodelingprogramandearlierversionsofAERMOD)inthecalculatedconcentrations.

PNB000770


6.8.6. Tail Pipe Emissions

Tailpipeemissionsfrommobilesourcesweredistributedamongroademissionsourcesandtheopenpitsources.Theemissionsassignedtoeachindividualroadsegment,andtothepit,werebasedonanevaluationofthevehiclemilestravelled(VMT)alongeachroadsegmentinsideandoutsidethepit.TailpipeparticulateemissionsweremodeledbothasPM10andPM2.5.

6.9. BUILDING DOWNWASH

Buildingdownwasheffectswereevaluatedbyincorporatingtheappropriatebuilding/structuredimensionsintotheAERMODinputfilesusingBREEZE’scommercialversionofEPA’sBuildingProfileInputProgramforPRIME(BPIPPRM)software.TheBPIPPRMprogramisEPAapprovedandincludesthelatestEPAbuildingdownwashalgorithms.ThedownwashfilesgeneratedbytheBPIPPRMprogramareprovidedelectronicallywiththisreport(AppendixI).

PNB000771


7. EMISSIONS INVENTORY

EmissionsfromtheRosemontProjectresultfromprocessequipmentandminingoperations.Processequipmentwasmodeledatmaximumcapacityplusasafetyfactor(forinstantaneousmaterialmovementthatwasbuiltintothemineplancalculations).Emissionsfromminingwilldependupontheminingrateandhaultrucktravelnecessarytotransporttheoreandwastefromthepittotheprimarycrusher,thedrystacktailingarea,andthewasterockstoragearea.Apreliminarysummaryofaverageandmaximumminingratesandhaultrucktravel(vehiclemiles)ispresentedinAppendixF.Thissummarymaychangewithrefinementtothemineplan.ThemininginformationinAppendixFindicatesthatthehighestprojectedannualminingrateandhighesthaultrucktravel,bothinandoutsideofthepit,willoccurinYear9.

Sincehaultrucktravelwillbetheprimarysourceofemissions(PM10andtailpipe),Year9wasmodeled.AmbientimpactsfromoperationsduringallotheryearswillhavelowerimpactsthanduringYear9.Inaddition,oreandwasterocktonnageandhaulmileageoffseteachother;therefore,haultruckmileageusedinthemodelingrepresentsaconservativemaximum.Anoreand/orwasterocktonnageincrease(fromtheaveragevalue)willcoincidewithahauldistancedecreaseduringanyparticularphaseofoperations.Asaresult,emissionswouldnotbelikelytoincreaseevenifshort‐termhaultrucktonnagesormileageincreased.Thetotalnumberofhaultrucksintheminefleet,theaveragehaultruckspeedandtheutilizationoffugitivedustcontrolpracticesarethelimitingfactorsforhaultruckemissions.

7.1. ANNUAL CRITERIA POLLUTANT EMISSIONS MODELING

AnnualimpactsofparticulateandgaseousemissionswerebaseduponemissionscalculatedusingtheaveragedailyprocessratesforYear9.

7.2. SHORT-TERM CRITERIA POLLUTANT EMISSIONS MODELING

Short‐termimpacts(1‐hour,3‐hour,8‐hourand24‐hour)werebasedupontheemissionscalculatedusingthemaximumdailyprocessratesforYear9.

PNB000772


8. DISPERSION MODELING IMPACT ANALYSIS

8.1. PRIMARY STANDARDS

ThepurposeofthedispersionmodelingoutlinedinthisreportistodemonstratethatemissionsfromtheRosemontProjectwillnotcauseexceedancesofapplicableNAAQS.Thisfinalimpactanalysisincludesallinformationnecessaryforthisdemonstrationincluding:(a)backgroundconcentrations(asdiscussedinSection4.4);(b)asourcelocationmap;(c)acompletelistofsourceparameters;(d)completemodelinginputandoutputfiles;and(e)graphicpresentationsofthemodelingresultsforeachpollutantshowingthemagnitudeandlocationofthemaximumambientimpacts.

8.2. OZONE AND SECONDARY PM2.5 - AMENDED

ADEQhasrequestedthatanozoneimpactsandsecondaryPM2.5formationanalysisbeprovidedthatfollowstherecommendationsprovidedtoArizonaCleanFuelsYuma(ACFY)inJanuary2016(AppendixG)andalsotheADEQGuidanceforsecondaryPM2.5analysis.Thesemethodsincludetheuseoftechnicallycrediblerelationshipsbetweenprecursoremissionsandasource’simpactsthatmaybepublishedinpeer‐reviewedliterature;developedfrommodelingthatwaspreviouslyconductedforanareabyasource,agovernmentalagency,orsomeotherentityandthatisdeemedsufficient;orgeneratedbyapeer‐reviewedreducedformmodel.Assuch,Rosemontusedthefollowingmethodologyforqualitativeanalysisoftheseimpacts.

8.2.1. Ozone Impacts

AtthetimeADEQpreparedtheACFYmemo,theEPAwasperformingandreviewingsingle‐sourcephotochemicalmodelingstudiesandotherPM2.5andozoneresearchtodevelopModelEmissionsRatesforPrecursors(MERPs)forPM2.5andozone(includingNOxandVOC).OnDecember2,2016,EPAissuedtheGuidanceontheDevelopmentofModeledEmissionRatesforPrecursors(MERPs)asaTierIDemonstrationToolforOzoneandPM2.5underthePSDPermittingProgram(EPA,2016),hereinafterreferredtoasMERPsGuidance.

OneofthestudiesEPAreviewedistheComparisonofSingleSourceAirQualityAssessmentTechniquesforOzone,PM2.5otherCriteriaPollutantsandAQRVs(Environ,2012),whichisincludedinAppendixAofthisdocument.Thepurposeofthatstudywastotestthefeasibilityofusingphotochemicalgridmodels(PGMs)forsingle‐sourceassessmentsofconcentration,visibilityanddepositionatfartherdownwinddistancesandcomparetheresultswithCALPUFF.TheComprehensiveAirQualityModelwithExtensions(CAMx)Plume‐in‐GridModule(PGM)andCALPUFFmodelingwereconductedusingtwoexistingdatabases:

The2005FourCornersAirQualityTaskForce(FCAQTF)12/4kmmodelingdatabasewiththe4kmdomainfocusedontheFourCornersRegion;and

A200612kmmodelingdatabasecoveringeasternUtahandwesternColorado(UT‐CO12kmdomain)thatwasoriginallydevelopedaspartoftheUintaBasinAirQualityStudy.

TestsourceswereselectedfromtheexitingPGMmodelingdatabases,andincludedElectricalGeneratingUnits(EGU)andoilandgas(O&G)productionsources.AllEGUsourcesweremodeledaspointsources,whiletheO&Gsourcesweremodeledasacombinationofareaandpointsourcesandincludedemissionsfromfuelburningequipment,fugitivesandconstructionandproductiontraffic(includingmobileemissionsandroaddust).ThetypesofsourcesincludedintheO&GmodelingmostaccuratelyreflecttheemissionssourcesfromtheRosemontProject.

PNB000773


TheRosemontProjectwillbelocatedinPimaCounty,approximately30milessoutheastofTucson,Arizona.Regionally,thefacilitylocationisintheSonoranDesertSectionoftheBasinandRangePhysiographicProvince,whichischaracterizedbynortherlytrending,faultblockmountainsseparatedbybroad,down‐faultedvalleys.ElevationsintheProjectarearangefromabout4,600toover6,300feetabovemeansealevel.TheapproximateelevationsoftheO&Gsourcesusedinthe2005FCAQTFmodelingareshowninTable8‐1below.Forthe2005oilandgasproductiontestsources,a9x9arrayof4kmgridcellswerechosetorepresentanareasourcecomplexofoilandgasproductionsourcesthatalsoincludesalargeO&Gpointsource,ifavailable.ElevenO&Gtestsourcecomplexeswereselectedforthe2006UT‐COmodelingusingasimilarapproachasusedinthe2005modeling.However,thedifferencebetweenthe2006UT‐COand2005FCAQTFmodelingdatabasesisthatthe2006CAMxemissionswerebasedontheUBAQSmodelingstudy.ThatstudyusedtheCMAQthree‐dimensional(3D)griddedformatversusthe2005CAMxdatabasethatconsistsofapointsourcefileand2‐Dgriddedsurfaceemissions.EachO&Gtestsourcecomplexcoversa3x3arrayof12kmgridcellsandallemissions,includingthoseinthealoftlayers.Theapproximatelocationofthe2006sourcesareshowninFigure8‐1(Figure2‐6fromEnviron,2012).

Table8‐1.2005PGMDatabaseO&GSourcesLocationandElevation

O&GFacility Location Urban/Rural ApproximateElevation(ft)

OG2‐ChacoGasPlant Bloomfield,NM Rural 6200

OG3‐LybrookPlant Cuba,NM Rural 6900

OG4‐GallupCompressorStation Gallup,NM Rural 6000

OG5‐ElPasoNaturalGasWindowRockPlant

WindowRock,AZ

Rural 6300

OG6‐LisbonNaturalGasProcessingPlant LaSal,UT Rural 6900

OG7‐QuestarGasManagement,DoveCreek

DoveCreek,CO Rural 6800

OG8‐IgnacioPlant Durango,CO Rural 6500

OG9‐LagunaCompressorStation Laguna,NM Rural 5800

Source:GoogleEarth

PNB000774


Figure8‐1.2006PGMDatabaseO&GSourceLocations

TheclimateoftheRosemontProjectareaissemi‐aridwithprecipitationvaryingwithelevationandseason.The30‐yearnormal(1971to2000)annualaverageprecipitationfortheSantaRitaExperimentalRange(SRER)station,locatedtothewestoftheProjectsiteandtheSantaRitaMountainRange,is23.41inches(WesternRegionalClimateCenter).Overthis30‐yearperiod,nearlyhalfoftheprecipitationoccurredinthemonthsassociatedwiththeArizonamonsoonofJuly,AugustandSeptember.TheleastamountofprecipitationoccurredduringthemonthsofApril,MayandJune.AverageannualprecipitationrecordedatthesiteislessthantheSRERstationat18inches;however,thepatternofprecipitationissimilar.

Temperaturesregionallyaremoderatetoextremewithmaximumsandminimumsalsovaryingwithelevation.The30‐yearnormalaveragemonthlymaximumtemperaturesattheSantaRitaExperimentalRangestationrangedfromalowof60.4°FinJanuarytoahighof93.3°FinJune.Averagemonthlyminimumtemperaturesrangedfromalowof37.5°FinDecemberandJanuarytoahighof66.8°FinJuly,whichisconsistentwiththesite.

TheclimateforeachoftheO&Gsourcesusedinthemodelingisalsocharacterizedassemi‐arid.Table8‐2presentsaveragetemperatureandprecipitationforeachoftheO&Gsources.

PNB000775


Table8‐2.PGMDatabaseO&GSourceClimateData

O&GFacility

AverageMonthlyMax

Temp,oF(low)

AverageMonthlyMax

Temp,oF(high)

AverageMonthlyMin

Temp,oF(low)

AverageMonthlyMin

Temp,oF(high)

AverageAnnualPrecip(in)

OG2‐ChacoGasPlant 44 92 20 61 9.32

OG3‐LybrookPlant 43 86 9 49 12.93

OG4‐GallupCompressorStation 45 88 13 54 11.54

OG5‐ElPasoNaturalGasWindowRockPlant

43 84 14 54 11.33

OG6‐LisbonNaturalGasProcessingPlant

36 85 16 56 14.11

OG7‐QuestarGasManagement,DoveCreek

39 86 18 58 14.84

OG8‐IgnacioPlant 41 89 13 51 N/A

OG9‐LagunaCompressorStation 46 90 26 66 9.39

Source:https://usclimatedata.com/climate/

TheDecember2016MERPsGuidancepresentsamethodologytoderiveaMERPTier1demonstrationtoolforagivenlocation.TheMERPsforeachprecursormayeitherbebasedoneitherthemostconservative(lowest)valueacrossaregion/areaorthesource‐specificvaluederivedfromamoresimilarhypotheticalsource.

Forthisanalysis,ozoneimpactswereassessedusingtwomethods.Forthefirstmethod,theNOxandVOCemissionsfromtheRosemontProjectwerecomparedtothoseofthevariousO&Gcomplexesmodeled,alongwiththemodeledozoneimpactofeachO&Gcomplex,todemonstratethatozoneimpactswillbebelowaninterim8‐hourozonesignificantimpactlevel(SIL)of1.0ppb.ThesecondmethodfollowsthemethodologypresentedintheMERPsGuidance.

8.2.2. Secondary PM2.5 Formation

PertheEPAPM2.5modelingguidance,theADEQmodelingguidancerecommendsoneoracombinationofthefollowingapproachesforassessingtheimpactsofprecursoremissionsonSecondaryPM2.5formation:

aqualitativeassessment, ahybridofqualitativeandquantitativeassessmentsutilizingexistingtechnicalwork;or afullquantitativephotochemicalgridmodelingexercise.

PNB000776


TheADEQfurtheroutlinesanapproachforahybridqualitative/quantitativeassessmentusingthe“offsetratios”approachestablishedbytheNACAAPM2.5Workgrouptoaddressthesecondaryformationfromaprojectsource.InthisapproachtheSecondarilyFormedPM2.5isestimatedbyapplyinginterpollutant“offsetratios”,asdefinedinEPA’sNSRimplementationruleforPM2.5(73FR28321,2008): NationwideSO2toPrimaryPM2.5offsetratio:40:1 WesternU.S.NOxtoPrimaryPM2.5offsetratio:100:1ThetotalequivalentPrimaryPM2.5emissionscanbeestimated: TotalEquivalentPrimaryPM2.5[TPY] =PrimaryPM2.5[TPY]+SO2[TPY]/40+NOx[TPY]/100ThetotalimpactfromPrimaryPM2.5andSecondarilyFormedPM2.5canbeestimatedbymultiplyingthemodeledconcentrationforPrimaryPM2.5bytheemissionratio:

TotalPM2.5(μg/m3)==PrimaryPM2.5(μg/m3)×{(totalequivalentPrimaryPM2.5[TPY])/(PrimaryPM2.5[TPY])}

Rosemontusedthismethodology,aswellasthemethodologypresentedintheMERPsGuidance,toestimateSecondaryPM2.5impactsfromtheRosemontProject.

PNB000777


9. EVAULATION OF DISPERSION MODELING RESULTS

Thissectionofthereportdiscussesthemodeloutputresults.TheresultsofthemodelingshowthattheProjectisincompliancewithallapplicableNAAQS.ModelsourceparametersareincludedinAppendixH.Modelinputandoutputfilesareincludedelectronically(AppendixI).

PNB000778


9.1. CRITERIA POLLUTANT IMPACT RESULTS - AMENDED

Table9‐1ModelResults

Pollutant AveragingPeriod

ModeledConcentration

(μg/m3)

UTMEasting(m)

UTMNorthing(m)

BackgroundConcentration

(μg/m3)

MaximumAmbient

Concentration(μg/m3)

NAAQS(μg/m3)

PM10 24‐hr1 97.66 526090.00 3519433.60 47.7* 145.4 150

Annual2 Revokedin2006

PM2.5 24‐hr3 9.31 526163.10 3519450.60 9.3 18.6 35

Annual4 2.91 526056.00 3519425.70 3.2 6.11 12

NOx 1‐hr5 127.5 523623.90 3524958.60 26.3 153.8 188.6

Annual6 15.2 527070.40 3521720.20 4.0 19.2 100

SO2 1‐hr7 26.1 521978.80 3523013.20 22.6 48.7 196

3‐hr8 Secondarystandard

24‐hr9 Revokedin2010

Annual9 0.03 527070.40 3521720.20 3 3.03 80

CO 1‐hr8 1,711 523363.00 3524350.10 582 2,293 40,000

8‐hr8 277.6 526163.10 3519450.60 582 859.6 10,000

1.Nottobeexceededmorethanonceperyearonaverageover2years.

2.Annualarithmeticmean,averagedover3years.

3.98thpercentile,averagedover3years.

4.Annualmean,averagedover3years.

5.98thpercentileof1‐hourdailymaximumconcentrations,averagedover3years.

6.Annualmean.

7.99thpercentileof1‐hourdailymaximumconcentrations,averagedover3years.

8.Nottobeexceededmorethanonceperyear.

9.RevokedJune22,2010.

*WhenthePM10backgroundconcentrationincludestheoutliervalueof71.3µg/m3,anaverage24‐hrPM10backgroundvalueof47.7µg/m3

results.Iftheoutlierisreplacedbythenexthighestreadingof40.3µg/m3,thebackgroundconcentrationwouldbereducedto37.4µg/m3.

Rosemontusedabackgroundof47.7µg/m3forthisanalysis(SeeSection4.4.1).

PNB000779


9.2. OZONE IMPACTS - AMENDED

AsdiscussedinSection8.2.1,theNOxandVOCemissionsfromtheRosemontProjectwerecomparedtothoseofthevariousO&Gcomplexesmodeled,alongwiththemodeledozoneimpactofeachO&Gcomplex,todemonstratethatozoneimpactswillbebelowaninterim8‐hourozoneSILof1.0ppb.Tables9‐2and9‐3belowshowtheNOxandVOCemissionfromeachO&Gcomplexalongwiththe1sthighestdailymaximum8‐hour(DMX8)ozoneconcentrationproducedbyeachsourceforthe2005FCAQTFandUT‐CO2006modeling,respectively.OnlythoseO&Gcomplexesthatincludedbothpointandareasourceswereusedforcomparison.

Table9‐22005FCAQTFEmissionsandDMX8ModelResults

O&GComplex NOx(tpy)

VOC(tpy)

NOx+VOC(tpy)

1stHighestDMX8(ppb)

OG2 294,833 668,185 963,017 7.41OG3 11,752 24,818 36,570 1.48OG4 1,983 80.5 2,064 5.96OG5 2,069 40.2 2,109 4.96OG6 1,842 28,832 30,674 2.73OG7 401 359 760 1.16

RosemontProject 220.5 2.37 222.87 n/a

Table9‐3UT‐CO2006EmissionsandDMX8ModelResults

O&GComplex NOx(tpy)

VOC(tpy)

NOx+VOC(tpy)

1stHighestDMX8(ppb)

OG01 5,535 16,063 21,598 2.21OG02 45,033 99,603 144,636 4.48OG03 41,023 271,886 312,909 6.90OG04 6,306 6,197 12,503 1.32OG06 1,923 2,570 4,493 0.85OG07 13,193 4,256 17,449 1.67OG08 76 7 83 0.04OG09 111 3 114 0.11

RosemontProject 220.5 2.37 222.87 n/a

TheNOx+VOCemissionsfromtheRosemontProjectareapproximatelyone‐thirdofthelowestmodeledemissionratefromthe2005FCAQTFmodeling.WiththeexceptionofOG08andOG09,theRosemontemissionsarealsosignificantlylessthantheUT‐CO2006modeledemissionrates.WhiletherelationshipbetweenNOx+VOCemissionsand1sthighestDMX8modeledimpactisnotperfectlylinear,modeledimpactsgenerallyincreasewithincreasesinemissions.Therefore,itisappropriatetoconcludethatemissionsofNOx+VOCfromtheRosemontprojectwouldbewellbelowthe8‐hourozoneSILof1.0ppb.

UsingtheMERPsGuidancemethodology,emissionsofNOxandVOCwerecomparedtothelowest(mostconservative)O3MERPvalueshowninTable7‐1oftheMERPsGuidance(hereinafterreferredtoasMERPsGuidanceTable7‐1;tableprovidedbelow).TheNOxemissionsof220.5tpyfromtheRosemontProjectarelargerthanthelowestNOxMERPfor8‐hourO3inthewesternandotherregionsoftheU.S.suchthatairquality

PNB000780


impactsofO3fromRosemontcouldbeexpectedtoexceedthecriticalairqualitythreshold.TwocomparablehypotheticalsourcesareidentifiedthatmayberepresentativeofRosemont(e.g.WUSregion,sources14and17,withgroundlevelemissionsreleaseasshowninAppendixAoftheMERPsguidance).ThesehypotheticalsourceshavesourcederivedNOxMERPsfor8‐hourO3of406.5tpyand213.7tpy,respectively,whicharelargerorcomparabletoRosemont’sproposedemissions.BasedonmodelingresultsforamoresimilarhypotheticalsourcefromAppendixAoftheMERPsGuidance,theProjectsourceemissionsarelessthanorapproximatelyequalto(Rosemontemissionsare3%greaterthanlowestMERPof213.7tpy)thecalculatedNOxto8‐hourO3MERPsuchthatairqualityimpactsofO3fromtheRosemontProjectareexpectedtobelessthanthecriticalairqualitythreshold.AcompliancedemonstrationisnotrequiredforVOC,sincetheproposedVOCemissionsfromtheProjectarewellbelowtheSignificantEmissionRate(SER).

9.3. SECONDARY PM2.5 FORMATION - AMENDED

AsdiscussedinSection8.2.2,thetotalimpactfromPrimaryPM2.5andSecondarilyFormedPM2.5canbeestimatedbymultiplyingthemodeledconcentrationforPrimaryPM2.5bytheemissionratio:

TotalPM2.5(μg/m3)==PrimaryPM2.5(μg/m3)×{(totalequivalentPrimaryPM2.5[TPY])/(PrimaryPM2.5[TPY])}

AsshowninTable9‐1,themaximummodeled24‐hrPM2.5impactfromtheProjectis9.31μg/m3;themaximummodeledannualimpactis2.91μg/m3.EmissionsofPrimaryPM2.5,SO2andNOxfromtheProjectare178.9tpy,24.20tpy,and220.45tpy,respectively.ThisresultsinaTotalEquivalentPrimaryPM2.5of181.71tpy.Usingtheequationshownabove,theTotalPM2.524‐hrandannualimpactsfromtheProjectarecalculatedtobe9.46μg/m3and2.96μg/m3,respectively.Attheselevels,thefacilityremainsincompliancewiththeNAAQS.Asshownbelow,usingtheMERPsGuidancemethodology,emissionsofNOxandSO2werecomparedtothelowest(mostconservative)PM2.5MERPvalueshowninMERPsGuidanceTable7‐1.BoththeproposedNOxandSO2emissionsfromtheRosemontProjectarewellbelowthelowestPM2.5MERPvalueforthedailyandannualNAAQSshowninMERPsGuidanceTable7‐1ofanysourcemodeledbytheEPAacrossthecontinentalUS.However,theprimaryPM2.5impactsneedtobeaddedtothesecondaryimpactsforanappropriateaccountoftotalPM2.5impactsforcomparisontotheairqualitythresholds.TheprimaryPM2.5shouldbeestimatedusing

PNB000781


AERMODandarepresentativesecondaryimpactaddedtothemodeledprimaryPM2.5impact.ThehighestmodeledPM2.5impactshouldthenbedividedbytheairqualitythresholdtoestimatethepercentcontributionandthendetermineifthatprimarycontributionexceedsthepercentremainingaftersecondaryimpactsareaccountedforusingtheMERPsdemonstrationtool.

AdditivesecondaryimpactsondailyPM2.5:(220.45tpyNOxfromsource/1155tpyNOxdailyPM2.5MERP)+(24.20tpySO2fromsource/225tpySO2dailyPM2.5MERP)=0.19+0.11=0.298*100=29.8%

PeakprimarydailyimpactfromAERMODfullimpactanalysis(includingbackground):

9.31μg/m3(sourceimpact)+9.3μg/m3(background)=18.6μg/m3/35μg/m3(NAAQS)=0.53*100=53%

DailyPrimary+Secondaryimpact=53%+29.8%=82.8%

AdditivesecondaryimpactsonannualPM2.5:(220.45tpyNOxfromsource/3184tpyNOxannualPM2.5MERP)+(24.20tpySO2fromsource/1795tpySO2annualPM2.5MERP)=0.07+0.01=0.08*100=8%

PeakprimaryannualimpactfromAERMODfullimpactanalysis(includingbackground):

2.91μg/m3(sourceimpact)+3.2μg/m3(background)=6.11μg/m3/12μg/m3(NAAQS)=0.509*100=50.9%

AnnualPrimary+Secondaryimpact=50.9%+8%=58.9%

SincethetotalsummedforbothdailyPM2.5andannualPM2.5impactisbelow100%,thesourceimpactisexpectedtobebelowthecriticalairqualitythreshold.

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Rosemont Copper Project | Amended Model Report Trinity Consultants A-1

APPENDIX A: PM10 QUARTERLY SUMMARY

PNB000783

Rosemont Modeling Protocol

Table A.1 Summary of 24-Hour PM Concentrations (g/m3)

10

July 2006-June 2007

Time Period

Valid Samples

Arithmetic Mean

Highest 2nd Highest 3rd Highest

3rd Quarter

06

13

24.6

71.3

27.0

26.8

4th Quarter

06

14

8.3

18.7

17.7

10.6

1st Quarter

07

15

2.3

7.0

5.5

4.6

2nd Quarter

07

15

17.6

28.7

27.0

25.6

Average

14.25 13.2 N/A N/A N/A

Highest Overall

N/A N/A 71.3 27.0 26.8

Table A.2 Summary of 24-Hour PM Concentrations (g/m3) 10

July 2007-June 2008

Time Period

Valid Samples

Arithmetic Mean


3rd Quarter

07

13

19.2

40.3

21.7

20.8

4th Quarter

07

15

5.3

11.9

11.9

8.0

1st Quarter

08

16

4.1

13.5

9.6

7.7

2nd Quarter

08

15

19.5

32.6

28.2

25.2

Average

14.75 12.02 N/A N/A N/A

Highest Overall

N/A

N/A

40.3

28.2

25.2

PNB000784


Table A.3 Summary of 24-Hour PM Concentrations (g/m3) 10

July 2008-June 2009

Time Period

Valid Samples

Arithmetic Mean


3rd Quarter

08

14

15.3

24.5

21.2

20.0

4th Quarter

08

15

8.5

31.6

15.1

12.7

1st Quarter

09

15

8.0

17.9

17.8

17.6

2nd Quarter

09

16

10.0

15.4

12.9

12.9

Average

15 10.45 N/A N/A N/A

Highest Overall

N/A

N/A

31.6

21.2

20.0

Table A.4 Summary of Annual PM Concentrations (g/m3) 10

Time Period

Valid Samples

Arithmetic Mean

Highest

2nd Highest

3rd Highest

July 2006-June 2007

14.25

13.2

71.3

27.0

26.8

July 2007- June 2008

14.8

12.0

40.3

28.2

25.2

July 2008- June 2009

15

10.45

31.6

21.2

20.0

Average 14.7 11.9 N/A N/A N/A

Highest Overall N/A N/A 71.3 28.2 26.8

PNB000785

Rosemont Copper Project | Amended Model Report Trinity Consultants B-1

APPENDIX B: PM10 DATA STATISTICAL ANALYSIS

PNB000786


BACKGROUND INFORMATION Ambient monitoring at the Rosemont Project for PM10 concentrations has been performed and

recorded from June 16, 2006 to June 30, 2009. Within this data, there are several concentration

measurements that appear to be outlying data and cannot be explained by any reasonable statistical

distribution. This document analyzes the outlying data points to determine the probability of their

occurrence to determine whether they are reasonable recurring events.

ANALYSIS The PM10 concentration measurements as a function of the date they were recorded are presented in Figure B.1. The possible outlying data points are the concentrations 71.3 and 40.3.

Figure B.1: PM10 Concentration Measurements

In order to statistically analyze the PM10 concentrations, the type of data distribution needs to be

determined. The simplest distribution is called a normal distribution. To test for normal distribution,

the standard normal concentrations (Z) are plotted against the measured PM10 concentrations. If a

linear regression line fits the plotted data points reasonably, a normal distribution can be assumed. The standard normal concentrations are calculated by Equation 1:

X - Z (1)

80

70

60

50

40

30

20

10

0

06/01/06 08/31/06 11/30/06 03/01/07 05/31/07 08/30/07 11/29/07 02/28/08 05/29/08 08/28/08 11/27/08 02/26/09 05/28/09

Date of Measurement

Co

ncen

trati

on

(μ

g/m

3)

PNB000787


y = 0.108x - 1.2551

R2 = 1

0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 7

10

where:

Z = Standard normal random variable

X

μ

=

=

Normal random variable (PM10 concentration measurements)

Mean value of the normal random variables (11.6 μg/m3)

σ = Standard deviation of the normal random variable (9.3 μg/m3)

The plotted PM10 concentrations versus the standard normal concentrations are shown in Figure B.2.

A linear regression trend line with an R2 value of 1 is added to the graph to show the reasonable fit of the data. From this graph, it can be assumed that the PM10 concentration data is normally distributed.

7

4

3

2

1

0

5

-1

-2

PM Concentration (X, μg/m3)

Figure B.2: Probability Plot Showing Normal Distribution

Since the PM10 concentration measurements are normally distributed, the normal distribution

probability density function can be utilized. This function can be plotted with either the normal random variable (the PM10 concentration measurements) or the standard normal random variable (calculated in Equation 1). The function is shown in Equation 2:

f x 1

2

-x-2

e 22

(2)

Sta

nd

ard

No

rmal P

M1

0 C

on

cen

trati

on

(Z

, μ

g/m

3)

PNB000788


10

where:

f(x) = Probability density function

x

μ

=

=

Normal random variable (PM10 concentration measurements)

Mean value of the normal random variables (11.6 μg/m3)

σ = Standard deviation of the normal random variable (9.3 μg/m3)

The normal and standard normal probability density functions for the PM10 concentration

measurements are shown in Figures B.3 and B.4. Both of these figures represent the same function.

The only difference is that Figure 4 is plotted with the standard normal data (Z). This implies that the

mean of the standard normal data is 0 and variance (standard deviation squared) is equal to 1. The

standard normal data and standard normal probability density function will be used in further analysis.

0.05

0.05

0.04

0.04

0.03

0.03

0.02

0.02

0.01

0.01

0.00

0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75

PM Concentration (X, μg/m3)

Figure B.3: Normal Probability Density Function

Pro

bab

ilit

y D

en

sit

y F

un

cti

on

(f(

x))

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0.05

0.05

.04

0.04

0.03

0.03

0.02

0.02

0.01

0.01

10

0.00

-2 -1 0 1 2 3 4 5 6 7

Standard Normal PM Concentration (X, μg/m3)

Figure B.4: Standard Normal Probability Density Function The probability density function (f(x)) also produces the probability of an event occurring in a future

sample. For the PM10 concentration data, this means the probability of the PM10 concentration

occurring during a future measurement. The possible outlier data points and their probability to occur

during a random measurement are shown in Table B.1.

The probability of a future measurement being equal to or exceeding the measured data point is also

shown in Table C.1. This value is calculated using Cumulative Standard Normal Distribution tables.

Based on the standard normal value of a data point, the Cumulative Standard Normal Distribution

tables produce the probability that a future measurement will be less than or equal to the data point.

Since the standard normal probability function is symmetric (centered at a mean of 0), the probability

of the measurement being greater than the data point can be calculated by Equation 3:

PZ z1- PZ z (3)

where:

P = Probability

Z = Future data

z = Current data being analyzed

Pro

bab

ilit

y D

en

sit

y F

un

cti

on

(f(

x))

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Table B.1: Possible Outlier Data Points to be Analyzed

Date

PM10

Concentration

(X, μg/m3)

Standard Normal

PM10 Concentration (z, μg/m3)

Probability

to Occur

P(Z ≤ z)

P(Z > z)

07/16/06 71.3 6.44 4.18E-11 1.00 5.87E-11

07/05/07 40.3 3.10 3.57E-04 1.00 9.81E-04

10/27/08 31.6 2.16 4.21E-03 0.98 0.02

CONCLUSION

The probabilities in Table B.1 show that it is highly unlikely that a PM10 concentration measurement greater than 71.3 or 40.3 μg/m3 will occur in future measurements (0.00000000587% and 0.0981%,

respectively). If the probability equals 5.87E-11, then of the next 100 billion samples taken, the outlier

(or greater values) is expected to occur 5.87 times. Similarly, of the next 10 billion samples taken, it is

not even expected to occur (since it is expected to occur 0.587 times, which is less than 1). A

concentration measurement of 31.6 μg/m3 has a 2% probability of occurring and therefore, the data

point should not be considered an outlier during further PM10 concentration data analysis.

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Rosemont Copper Project | Amended Model Report Trinity Consultants C-1

APPENDIX C: ADEQ BACKGROUND VALUE COMMUNICATIONS

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Rural Arizona Example BackgroundConcentrations

Averaging

Ambient Data

Background

Standard

Pollutant

Time

1999

2000

2001

Value (g/m3)

(g/m3)

NO2 a annual --- --- --- 4 100

CO b 1-hour --- --- --- 582 40,000

8-hour --- --- --- 582 10,000

SO2 c 3-hour 43 14 15 43 1,300

24-hour 17 7 8 17 365 annual 2 1 3 3 80

a Long-term average value (0.002 ppm) of several monitors located near power plants in rural areas of Arizonab Typical continental ambient CO background value (0.5 ppm) used in most regional models c Max. values over 3-year period from Page monitoring station (Coconino County)


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Rosemont Copper Project | Amended Model Report Trinity Consultants D-1

APPENDIX D: NOX IN-STACK RATIO DATA - AMENDED

PNB000796

May 11, 2011

Kathy Arnold Rosemont Copper Company 3031 West Ina Road Tucson, AZ 85741

Re: Response to the Forest Service April 22, 2010 Request for Clarifications

Dear Ms. Arnold:

Presented below please find a citation of the Forest Service Request for Clarification and the corresponding response.

Section 7.1.2: Please provide documentation supporting the NO2/NOx ratios used in the NO2 analysis of the various types of equipment proposed to be used. This information is necessary for us to evaluate the four scenarios offered for NO2 modeling and select the best option.

Documentation and Clarifications:

The one-hour NO2 standard was published in the Federal Register on February 9, 2010 (75 FR 6474-6537), becoming effective April 12, 2010. Following its promulgation, EPA issued memoranda on June 29, 2010 and March 1, 2011 clarifying the applicability of current guidance in the Guideline on Air Quality Models for modeling NO2 impacts. The two memoranda reflect major uncertainties regarding appropriate in-stack NO2/NOx ratios for use by the current AERMOD Model.

Except for emergency generators that operate only during emergency conditions when there is a disruption to mining processes, sources of NOx emissions are comprised of blasting (884 lb/hr), a small boiler (0.876 lb/hr) and mobile sources (315.25 lb/hr). Emergency generators were not included in the modeling analyses because they would not operate when mining operations would be taking place, and are also excluded from consideration by the March 1, 2011 EPA memorandum. The NO2/NOx ratio due to blasting emissions is uncertain, however blasting is constrained to occur only between the hours of 12:00 (noon) and 4:00 P.M (i.e. starting at noon and ending at 5:00 P.M.). The maximum predicted 1-hour NOx impacts due to blasting for any single hour for the three meteorological years that were modeled during these hours is 8.58 μg/m3, or 4.5% of the 1-hour NO2 standard. Because not all NOx emissions will be in the form of NO2, the actual NO2

impact will be lower. Consequently, the overwhelming sources of NOx emissions that can contribute to significant NO2 impacts are mobile sources.

Data of in-stack NO2/NOx ratios for mobile sources (i.e. internal combustion engines) is very limited, if not unavailable. In order to address the information requested by the Forest Service, requests were made to Caterpillar Inc, the major supplier of mobile equipment to Rosemont, and to Leonard Montenegro, former Supervisor of the Air Quality Evaluation Group at the Arizona Department of Environmental Quality, to research and provide such information.

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of 4 A letter from Caterpillar Inc. is attached citing “engine out” NO2 as being 5 to 15% of NOx emissions for engines without an oxidation catalyst or catalyzed DPF. Mobile sources at the Rosemont facility will not be equipped with oxidation catalysts or catalyzed DPF. As indicated below, the NO2/NOx ratio of “engine out” emissions overestimates the in-stack ratio because such measurements have been made after the engine exhaust has been mixed with ambient air and the NO to NO2 conversion has already commenced. In-stack NO2/NOx ratios should thus be less than those cited by Caterpillar Inc.

The research conducted by Mr. Montenegro is attached. The research describes the techniques used to measure emissions from the exhaust of IC engines, the results of measurements designed to determine in- stack NO2/NOx ratios (2-6%), and ratios used by EPA to evaluate the sensitivity of AERMOD’s algorithms for modeling NO to NO2 conversion and exposure assessment studies (5-10%). Mr. Montenegro’s research supports an in-stack NO2/NOx ratio of somewhere around 5%.

Independent of the representativeness of the NO2/NOx ratio used to evaluate potential 1-hour NO2

concentrations, all parties to the EIS should also consider the conservativeness of the modeling. As indicated during past conference calls with the Forest Service and National Park Service, short term standards were evaluated by assuming maximum hourly emissions, i.e. all equipment (except emergency generators) are operating concurrently at all time, i.e. 8760 hours/year. This cannot occur. Haul trucks, for example, have a design annual operating hour capacity of 6600 hours and not 8760 hours. Emissions from haul trucks represent 260.8 lb/hr of the 315.25 lb/hour that were modeled for mobile sources. Use of 6600 hours would reduce hourly emissions from all mobile sources to 250.95 lb/hour, or a 20% decrease in total mobile source emissions. Other equipment will also not be operating on a continuous basis.

Other assumptions that increase the conservativeness of the modeling even further include the following:

The assumption that the highest background NO2 concentration occurs every hour of the year. A

more typical background concentration that would be anticipated to occur would be the average concentration. The highest hourly and average NO2 concentrations at the Alamo background site are 24.5 μg/m3 and 4.9 μg/m3 respectively. The assumption that the highest 1-hour concentration occurs continuously is unrealistic.

All haul trucks are assumed to have Tier 2 engines. Because of delays, however, six of the engines

will not be manufactured until the Tier 4 standards become effective, at which time manufacturers, will be prohibited from manufacturing Tier 2 engines. NOx emissions for Tier 4 engines are 58% of those of Tier 2 engines. EPA’s Final Rule for Nonroad Engines ((69 Fr 38957 -39206) states that the NOx emission reductions for engines used in mobile machinery are based on engine-based emissions control technology rather than after-treatment methods that utilize oxidation catalysts. The net result of 6 haul trucks with Tier 4 engines is a 21 lb/hr reduction in NOx emissions from haul trucks.

Application of these more realistic assumptions in combination with a NO2/NOx in-stack ratio of 5% would result is substantially lower predicted impacts than those presented in the modeling report.

Section 7.1.5: The report indicates that a three-year average was used to determine attainment of the National Ambient Air Quality Standard (NAAQS) for 2.5 micron-diameter particulate matter (PM2.5). According to EPA’s Model Clearinghouse memorandum of February 26, 2010, the use of a three-year average does not preempt the requirement in Appendix W that five years of National Weather Service (NWS) data be used. The five-year average of modeled impacts serves as an unbiased estimate of the three- year average for the purpose of modeling compliance with the NAAQS. Please clarify that this guidance for PM2.5 modeling was followed.

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Clarification:

Section 9.3.1.2.b of 40 CFR 51, Appendix W states the following:

Page 3 of 4

The use of 5 years of NWS meteorological data or at least 1-year of site specific data is required. If one year or more (including partial years), up to five years, of site specific data is available, these data are preferred for use in air quality analyses. Such data should have been subjected to quality assurance procedures as described in subsection 9.3.3.2.

The above citation clarifies that a minimum of 1-year of site specific data is preferred for conducting air impact analyses over 5 years of nearby NWS data. Use of 3-years of site specific data as was conducted in the air impact analyses for the Rosemont project thus exceeds the minimum preferred requirements of Appendix W and does not preempt it.

With regards to the February 26, 2010 memorandum, we have not been able to locate it. We presume, however, that a March 23, 2010 memorandum titled “Modeling Procedures for Demonstrating Compliance with PM2.5 NAAQS” from Stephen D. Page, Director of Office Air Quality Planning and Standards, includes that guidance or a refinement of the guidance provided by the February 26, 2010 memorandum.

This memorandum cites the following in the section titled “Comparison to NAAQS” in the Cumulative Impact Assessment:

For the 24-hour NAAQS analysis, the modeled concentrations to be added to the monitored 24-hour design value should be computed using the same procedure used for the preliminary analysis based on the highest average of the maximum modeled 24-hour averages across 5 years for NWS meteorological data or the maximum modeled 24-hour average for one year of site-specific meteorological data. As noted above, use of the average modeled concentration across the appropriate time period more accurately characterizes the modeled contribution from the facility in relation to the NAAQS than use of the highest modeled contribution, while using the average of the first highest 24-hour averages rather than the 98th percentile (8th highest) values is consistent with the screening nature of PM2.5 dispersion modeling.

The above hypothesizes that the available meteorological data is limited to either five years of NWS data or only one year of site-specific meteorological data. The second highlighted sentence above states that “use of the average modeled concentration across the appropriate time period more accurately characterizes the modeled contribution from the facility than use of the highest modeled contribution”. With regards to the modeling conducted for Rosemont, three years of site-specific data were used. Consequently, averaging of the maximum modeled 24-hour averages across 3 years of site-specific meteorological data more accurately characterizes the modeled contribution than taking only one year of modeled data. The modeling that was conducted for Rosemont thus conforms to EPA’s March 23, 2010 guidance memorandum.

Please call if you have any questions.

Sincerely,

Louis C. Thanukos, Ph.D. Division Manager Applied Environmental Consultants, a JBR Company

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of 4

cc: Shantanu Kongara Dave Strohm Leonard Montenegro

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Leonard Montenegro 1025 E. Sandpiper Dr.

Tempe, AZ 85283

May 10, 2011

Louis C. Thanukos Ph.D. Applied Environmental Consultants, a JBR company 1553 W. Elna Rae Tempe, AZ 85281-6935

Subject: Evaluation of representative primary NO2/NOx ratios for use in modeling haul- truck emissions as part of the Rosemont Copper Project Ambient Impact Analysis.

Dear Dr. Thanukos,

As requested, the following documents provides an abridged overview of AERMOD’s oxidation module, its methodology for estimating NO2/NOx ratios and a basis for selecting appropriate data for the in-stack input parameter. Also provided is a review of literature pertinent to sampling methods used for measuring primary NOx emissions. This document may also be used to provide support for modeling NO2 impacts from Rosemont’s haul-truck emissions, using an in- stack NO2/NOx ratio of 5%.

Cordially,

Leonard Montenegro

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About the author

Leonard Montenegro is an independent consultant who specializes in air quality modeling and air quality

modeling systems. Leonard’s area of expertise is in High Performance Computing (HPC) using air quality

models. He has 10 years of experience in the public sector, with a main focus on air quality modeling.

Other areas include mobile source, emissions and meteorological modeling with models such as MOVES,

SMOKE and the Weather Research and Forecasting Model (WRF). Leonard has developed autonomous

weather forecasting systems for clients worldwide and has developed a variety of web‐based software

tools related to air quality. Leonard’s recent areas of work include predictive analytics and air quality

tools for mobile platforms.

Leonard’s professional and public service includes 6 years with the Center for Environmental Fluid

Dynamics at Arizona State University and 10 years for the Arizona Department of Environmental Quality

where he supervised the Air Quality Evaluation group. The Evaluation group’s responsibilities included

both administering and reviewing modeling and scientific analyses relevant to air pollution permitting

and planning. Leonard has also managed an assortment of air pollution studies relating to, for example:

attainment demonstrations for State Implementation Plans (SIP), public health assessments from

exposure to air toxics and air pollution impacts along the U.S. ‐ Mexico border.

Leonard received his Bachelor’s degree in chemistry from Arizona State University and has co‐authored

papers relating to air pollution science and technology.

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Evaluation of Representative Primary NO2/NOx Ratios for use in Modeling Mobile Source Emissions as Part of the Rosemont Copper Project Ambient

Impact Analysis. Executive Summary

Nitrogen-dioxide (NO2) pollution from industrial sources is a product of two distinct processes— primary NO2 from combustion and the formation of secondary NO2 from oxidation of nitric oxide (NO) by ozone (O3) in ambient air. Dispersion models, like AERMOD (USEPA’s guideline dispersion model), can be used to estimate ambient NO2 impacts from plumes emitted by large industrial stacks, by using stack test data for the in-stack model input parameter. However, data from stack tests does not exist for other source types, such as mobile on- and off- road source categories. Therefore, an in-stack equivalent must be selected from available data.

This document discusses the basis for differentiating among data-sampling methods to determine representative primary, or ―in-stack,ǁ NO2/NOx fractions for modeling mobile sources and presents current research to support an in-stack ratio of 5% for Rosemont’s mobile source NOx

emissions.

Introduction

The current short-term NAAQS (National Ambient Air Quality Standard) for NO2 (nitrogen dioxide) became effective April 12, 2010. Industrial sources can demonstrate compliance with the standard by using either source-oriented ambient NO2 monitoring data or by relying on estimates provided by air-quality dispersion modeling. NO2 monitors measure ambient hourly NO2 concentrations, which can be compared directly to the NO2 NAAQS. However, industrial- source emissions are reported as total NOx, which is a composite of NO2 and NO. Air-quality models must, therefore, simulate the dispersion and transformation of NOx to NO2 before any comparisons to the NAAQS can be made. Most photochemical models use elaborate chemical transformation schemes to simulate secondary NO2 formation, but they are generally intended for long-range air-quality studies and not for localized air-quality impacts from industrial sources. In any event, model selection is dictated by federal guidance, which generally limits industrial-source permit modeling to AERMOD (which uses a rather simple NO2 oxidation scheme to simulate NOx transformations).

AERMOD is primarily a steady-state plume-dispersion model; therefore, it must rely on built-in oxidation models like OLM (Ozone Limiting Method) and PVMRM (Plume Volume Molar Ratio Method) to estimate ambient ratios of NO2 /NOx, based initially upon representative NO2/NOx data from in-stack NOx emissions. The ambient NO2 ratio is estimated by computing the sum of the fraction of in-stack NO2 formed during combustion—called the primary NO2/NOx

ratio—with the fraction of secondary NO2, transformed from NO in the ambient air by mixing and by oxidation by ozone. At minimum, AERMOD requires a representative estimate for the primary NO2 fraction. Modeling industrial stacks using either OLM or PVMRM is typically straight forward, since in-stack NOx data collected from compulsory EPA stack testing is usually available. To the contrary, modeling NO2 impacts from mobile sources is not straight forward,

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since stack testing does not apply to mobile sources and mobile source plume behaviors is distinctively different from plumes emitted from elevated stacks.

The body of literature from studies pertinent to mobile source NOx emissions is comprised of data collected from a variety of sampling methods. The primary objective of this document is to present representative NO2/NOx estimates, based on only those studies in which primary NO2

was sampled by either direct (in-stack or in-pipe) measurement methods or by methods designed for mitigating oxidation from ambient ozone, via measuring NOx inside of tunnels.

The following reports support a primary NO2 in-stack fraction of 5%

―Nitrogen Oxides Reactions in Diesel Oxidation Catalyst.ǁ – Majewski, et al. Reports a maximum primary NO2 ratio of 5.3%

―The use of tunnel concentration profile data to determine the ratio of NO2/NOx

directly emitted from vehiclesǁ – X. Yao, et al. Reports a primary NO2 range of 2% to 6%

Letter from Caterpillar dated April 27, 2011 States that engine-out NO2 can typically range from 5% to 15%

Sensitivity Analysis of PVMRM and OLM in AERMOD. - USEPA Modeling analysis used an in-stack ratio of 5% for arbitrary sources

Philadelphia Exposure Assessment Case-Study - USEPA Modeling analysis used a 10% in-stack ratio for off-road vehicles

―Risk and Exposure Assessment to Support the Review of the NO2 Primary National Ambient Air Quality Standardǁ - USEPA Modeling analysis used a 10% in-stack ratio for off-road vehicles

Discussion

Traditional NOx measurements from power plants are often derived from in-stack measurements, in accordance with USEPA Test Method 7 (1). Stack test data is ideal for oxidation models, since OLM and PVMRM require, as input, the ratio of primary NO2/NOx—representative of NOx

emissions before the exhaust gases leave the stack (2). However, selecting representative in-stack NO2/NOx data for modeling mobile sources can be complicated. Stack testing does not apply to mobile sources, and established EPA mobile-source test methods are not well suited to provide primary NO2 measurements.

For example, EPA’s continuously integrated test method for NOx emissions samples engine-out exhaust, which has been mixed with ambient air and allowed to cool to near ambient temperature (3). Also, EPA’s bag-sample method, where diluted exhaust gas is collected and analyzed at ambient temperature, also allows cooling and is not a representative measure of ―in-stackǁ primary NO2. Since the model’s in-stack parameter requires measurements that are representative of NOx emissions before they leave the stack, data derived from EPA’s test procedures are inappropriate for model input.

There are alternative data sources for mobile-source emissions, but discretion should be used to differentiate samples that are representative of primary NO2 from combustion, from those that

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may likely include an appreciable degree of oxidation. There are two important considerations for determining appropriate NO2/NOx ratios for off-road diesel vehicles. First, the ratio of NO2/NOx must be representative of primary NO2 formed from combustion—engine-out measurements made inside the tail pipe (in-pipe) are preferred. The second consideration must account for NO2 formed by diesel after treatment technologies, such as Continuously Regenerating Technology (CRT), which reduce particulate emissions but can increase the in-pipe fraction of NO2 by forcing oxidation of NO to NO2 across a catalyst. Most research suggests that diesel engines fitted with CRT can increase the in-pipe NO2 to 30%, on average. However, not all diesel after-treatment technologies have adverse impacts on in-pipe NO2.

The study ―Nitrogen Oxides Reactions in Diesel Oxidation Catalystǁ (4) discussed the influences of platinum and palladium oxidation catalysts on NOx transformations in diesel exhaust from a Caterpillar 3304 mining diesel engine. The apparatus design was comprised of a direct (i.e., in- pipe) sampling method using Fourier Transform Infrared (FTIR) and was set up to allow sampling before and after each catalyst. At a maximum conversion temperature of approximately 380 degrees C, the platinum catalyst increased NO2 from approximately 5 ppm to 25 ppm, while NO was reduced from 625 ppm to 475 ppm. The values are approximations, since the report only provided the data in chart form. However, even with a fourfold increase in NO2, the maximum NO2/NOx ratio was 5.3%. The maximum pre-catalyst NO2/NOx was approximately 3.5% at 150 degrees C, where NO was 200 ppm and NO2 was 7 ppm.

Tunnel sampling methods can also provide an estimate of primary NO2, since the air near the center of long tunnels often has less oxidation potential than ambient air, outside the tunnel. The study ―The Use of Tunnel Concentration Profile Data to Determine the Ratio of NO2/NOx

Directly Emitted from Vehiclesǁ (5) details a procedure for estimating the primary NO2 fraction from NOx measurements made in two separate tunnels; each tunnel was approximately 4 km in length. At the center of each tunnel, atmospheric oxidation potential is limited (albeit not likely entirely absent). Ambient pollutant concentrations are measured inside the tunnel at different locations. Higher NO2/NOx ratios were measured near each tunnel’s entrance and exit. The lowest NO2/NOx ratios (2% to 6%) were measured near the center of each tunnel. Measurements near the tunnels’ centers can be considered very conservative estimates for thermal NO2/NOx, since measurements are made in the open air and at ambient temperatures, yet with very limited oxidation potential.

In a letter provided by Caterpillar, Caterpillar states that emission test procedures for on- and off- road equipment follow applicable regulations. As a general rule, Caterpillar claims that engine- out NO2/NOx can range from 5% to 15% NO2, but that oxidation catalysts and diesel particulate filters can increase the ratio of engine-out NO2. It is unclear, however, if Caterpillar estimates are for engine-out or tailpipe NO2. EPA also suggests that mobile-source NO2 emissions from diesel vehicles with DPF can have elevated NO2/NOx ratios, as compared to non-catalyzed diesel vehicles. In Shorter et al., (6) diesel vehicles fitted with DPF/CRT had an average NO2/NOx ratio of 30%, while ambient measurements from non-catalyzed vehicles were below 10% NO2/NOx.

In section 8.4 of EPA’s ―Risk and Exposure Assessment to Support the Review of the NO2

Primary National Ambient Air Quality Standardǁ (7) AERMOD was set up to model ambient NO2 impacts in Atlanta, GA. OLM was used for roadway and airport emissions, and PVMRM was used for point sources. All sources were modeled with an in-stack ratio of 10%, including

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off-highway diesel airport vehicles. Roadways were modeled as large area sources, with length- to-width ratios of 1:100.

In Appendix B - Supplement to the NO2 Exposure Assessment, Section B-3 Philadelphia Exposure Assessment Case-Study (8), NO2 air-quality impacts were modeled in the Philadelphia area, with AERMOD. OLM was used for roadway, fugitive, and airport emissions, including off- highway diesel vehicles, with an in-stack NO2/NOx ratio of 10%. PVMRM was used to model stacks with an in-stack ratio of 10%.

Conclusions

In-stack data is available for industrial stacks, not mobile sources. In-stack NO2/NOx must be representative of exhaust gases before leaving the stack and

before any mixing or oxidation by ambient air has occurred. Typical mobile-source emissions, which are often measured after mixing with ambient

air, are inappropriate for use with OLM or PVMRM. According to data sampled from in-pipe diesel exhaust, the maximum ratio of NO2/NOx

is 5.3%. According to data sampled from a tunnel study, estimates of the primary NO2 fraction

range from 2% to 6%. Reports of NO2/NOx ratios as high as 30% are often reflective of diesel vehicles fitted

with diesel after treatment devices.

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WorksCited(1) EPA ‐ Method 7. (n.d.). METHOD 7 ‐ DETERMINATION OF NITROGEN OXIDE EMISSIONS FROM

STATIONARY SOURCES.

(2) Hanrahan, P. L. (1999). The Plume Volume Molar Ratio Method for Determining NO[sub2]/NO[subx]

Ratios in Modeling‐‐Part I: Methodology.

(3) USEPA ‐ Part 89 subpart E ‐ Exhaust Emission Test Procedures. (n.d.). Title 40:PART 89—CONTROL OF

EMISSIONS FROM NEW AND IN‐USE NONROAD COMPRESSION‐IGNITION ENGINES Subpart E—

Exhaust Emission Test Procedures.

(4) Majewski, W. A., Ambs, J. L., & Bickel, K. (1995). NItrogen Oxides Reactions in Diesel Oxidation

Catalyst. Society of Automotive Engineers.

(5) X. Yao, N. T. (2005). The use of tunnel concentration profiledata to determine the ratio of

NO2/NOxdirectly emitted from vehicles. Atmospheric Chemistry and Physics Discussions.

(6) Shorter, J. H., Herndon, S., Zahniser, M. S., Nelson, D. D., Wormhoudt, J., Demerjian, K. L., et al.

(2005). Real‐time measurements of nitrogen oxide emissions from in‐use New York City

transitbuses using a chase vehicle. Environ. Sci. Technol.

(7) EPA. (2008). Risk and Exposure Assessment to Support the Review of the NO2 Primary National

Ambient Air Quality Standard: Second Draft. EPA.

(8) EPA. (n.d.). Appendix B. Supplement to the NO2 Exposure Assessment. From Integrated Science

Assessment for Oxides of Nitrogen — Health Criteria.

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PNB000808

NOx emissions from blasting operations in open-cut coal mining

Moetaz I. Attalla*, Stuart J. Day, Tony Lange, William Lilley, Scott MorganCSIRO Energy Technology, P.O. Box 330, Newcastle, NSW 2300, Australia

a r t i c l e i n f o

Article history:Received 1 February 2008Received in revised form 1 July 2008Accepted 7 July 2008

Keywords:NOx

Open-cut miningAustraliaMiniaturised ultraviolet spectrometerMini-DOAS

a b s t r a c t

The Australian coal mining industry, as with other industries is coming under greaterconstraints with respect to their environmental impacts. Emissions of acid gases such asNOx and SOx to the atmosphere have been regulated for many years because of theiradverse health effects. Although NOx from blasting in open-cut coal mining may representonly a very small proportion of mining operations’ total NOx emissions, the rapid releaseand high concentration associated with such activities may pose a health risk. This paperpresents the results of a new approach to measure these gas emissions by scanning theresulting plume from an open-cut mine blast with a miniaturised ultraviolet spectrometer.The work presented here was undertaken in the Hunter Valley, New South Wales, Australiaduring 2006. Overall this technique was found to be simpler, safer and more successfulthan other approaches that in the past have proved to be ineffective in monitoring theseshort lived plumes. The average emission flux of NOx from the blasts studied was about0.9 kt t�1 of explosive. Numerical modelling indicated that NOx concentrations resultingfrom the blast would be indistinguishable from background levels at distances greater thanabout 5 km from the source.

Crown Copyright � 2008 Published by Elsevier Ltd. All rights reserved.

1. Introduction

Open-cut coal mining is widespread in the upperHunter Valley in New South Wales (NSW) with severallarge mines operating within close proximity to the townsof Muswellbrook and Singleton. Consequently, there iscommunity concern about the potential environmentalimpacts of mining on nearby populations.

Blasting, in particular, has the potential to affect areasoutside the mine boundary and accordingly, vibration anddust emission limits are set in each mine’s environmentallicence. However, gaseous emissions of environmentalconcern, such as nitrogen dioxide (NO2) may also bereleased during blasting operations. Currently, there arevery little quantitative data relating to the magnitude ofthese emissions and it is not yet possible to determine ifthey contribute significantly to ambient levels in the mainpopulation centres.

The explosive ammonium nitrate/fuel oil (ANFO) is usedalmost universally throughout the open-cut coal miningindustry. Under ideal conditions, the only gaseous productsfrom the explosion are carbon dioxide (CO2), water (H2O)and nitrogen (N2).

3NH4NO3 þ CH2 / 3N2 þ CO2 þ 7H2O (1)

However, even quite small changes in the stoichiometry(either in the bulk material or caused by localised condi-tions such as moisture in the blast hole, mineral matter orother factors) can lead to the formation of substantialamounts of the toxic gases carbon monoxide (CO) and nitricoxide (NO) as shown.

2NH4NO3 þ CH2 / 2N2 þ CO þ 5H2O (2)

5NH4NO3 þ CH2 / 4N2 þ 2NO þ CO2 þ 7H2O (3)

In addition, some of the NO formed may oxidise in thepresence of oxygen (O2) to produce NO2.

* Corresponding author.E-mail address: [email protected] (M.I. Attalla).

Contents lists available at ScienceDirect

Atmospheric Environment

journal homepage: www.elsevier .com/locate/atmosenv

1352-2310/$ – see front matter Crown Copyright � 2008 Published by Elsevier Ltd. All rights reserved.doi:10.1016/j.atmosenv.2008.07.008

Atmospheric Environment 42 (2008) 7874–7883

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mailto:[email protected]

www.sciencedirect.com/science/journal/13522310

http://www.elsevier.com/locate/atmosenv

2NO þ O2 / 2NO2 (4)

Often in practice, large quantities of NO2 are released fromblasts which are observed as intense orange plumes.

Although these gases are not considered in their envi-ronmental licences, each mine is required to estimateannual emissions of CO, NOx and SO2 for the NationalPollutant Inventory (NPI), compiled each year by theAustralian government. These estimates are made bymultiplying the amount of explosive consumed by anemission factor which is currently 8 kg t�1 for NOx, 34 kg t�1

for CO and 1 kg t�1 for SO2 (National Pollutant Inventory,1999). These emission factors, however, are based onlimited overseas data and are subject to high uncertainty.

Most of the studies which have examined NOx forma-tion from blasting have used blast chambers. The resultsfrom these studies do not necessarily correlate with what isobserved during actual blasts. Few studies have attemptedto measure NOx emissions under actual field conditions,presumably because of the practical difficulties involved.Plumes from blasting lack confinement, can be very large insize and are affected by prevailing weather conditions.There is also a large quantity of dust associated with theblast and these factors combine to make physical samplingof the plume very difficult. There are also the obvious safetyimplications which restrict access to blast sites. Conse-quently, quantitative measurements of plume characteris-tics are generally unavailable. Nevertheless, it is importantfor mine operators, particularly when their operations areclose to residential areas, to have some method forassessing NOx formation and more importantly, predictingthe severity of the NOx plume. At present predictions of NOx

formation are subjective and are based on the blast engi-neer’s knowledge of the area to be blasted (e.g. rock type,area of the mine, presence of water in the holes, etc.) andthe ratings obtained from blasts performed under similarconditions. Quantitative flux estimations of NOx releasedfrom a blast require measurement of concentrationthrough the plume in both the horizontal and vertical axes.

Some of the options available to make these measure-ments are given in the following sections.

1.1. Physical sampling

Sampling of blasting fumes involves taking a sample ofgas from the plume for subsequent analysis, which could beeither on site or in an off site laboratory. Although physicalsampling could in principle provide sufficient informationto characterise a plume, there are a number of seriouslogistical problems with this approach:

� The size of the plume means that a large number ofsample points would be required to sample across thewidth and height of the plume.

� The force of the explosion and the resulting debriswould restrict the proximity of any sampling packagesto the initial gas release.

� The potential toxicity of the plume; personnel cannotmove through it to take samples, hence samplingstations must be fixed prior to the blast. This means

that the path of the plume must be anticipatedbefore the blast.

1.2. Continuous analysis

Another option is to use portable analysers to measureNOx concentrations in real time. There are, however,disadvantages with this approach since a sample of theplume must be presented to the instrument for analysis.Usually a pump draws air through a small diameter tubeinto the instrument, but to achieve the necessary spatialcharacterisation of the plume, sample tubes would need tobe positioned at various points throughout the plume. Thusmany of the problems identified for the physical samplingwould also apply to the use of continuous analysers.

1.3. Optical methods

There are several optical methods of analysis currentlyavailable that may be applicable to field measurements ofNOx. These include open-path Fourier Transform Infra-RedSpectroscopy (FT-IR), Correlation Spectroscopy (COSPEC)and Differential Optical Absorption Spectroscopy (DOAS).FT-IR has often been used in air pollution studies (e.g.Levine and Russwurm, 1994). It has also been used in minesituations to measure fugitive methane emissions. Kirch-gessner et al. (1993) used open-path FT-IR (op-FT-IR) toestimate methane emissions from open-cut coal mines inthe United States. The technique relies on passing a colli-mated infrared beam through ambient air over a pathlength of up to several hundred metres. In the Kirchgessneret al. (1993) study, the concentration of methane across theplume was measured then wind speed data and a Gaussianplume dispersion model were used to estimate themethane emission rate from the mine. These authorssubsequently developed a modification of their methodwhich improved its accuracy (Piccot et al., 1994, 1996). Theimproved method was essentially the same as describedabove except that methane concentrations were measuredat several elevations to better characterise the plume.

In principle, open-path FT-IR could be used to measureNOx in blast plumes since it is sensitive to NO, NO2, and COalong with other gases. Infrared radiation is also stronglyabsorbed in many parts of the spectrum by both CO2 andwater which are very likely to be present in high concen-trations in blast plumes and this may tend to obscure theNOx signal. High resolution instruments may resolve at leastsome of the NOx absorption lines, however, a more seriousdrawback with op-FT-IR is that the infrared beam would besubstantially attenuated by the dust thrown up by the blast.In the period immediately after the blast when the dustlevel is very high it is likely that the IR beam would becompletely blocked thus making measurements impossible.

Another well established optical method is CorrelationSpectroscopy (COSPEC). The system was first described byMoffat and Milan (1971) and was designed to measurepoint source emissions of SO2 and NO2 from industrialplants but found a niche application in the measurement ofSO2 fluxes from volcanoes (Galle et al., 2002). The COSPECsystem utilises a ‘‘mask correlation’’ spectrometer and wasdesigned to measure vertical or slant columns using

M.I. Attalla et al. / Atmospheric Environment 42 (2008) 7874–7883 7875

PNB000810

sky-scattered sunlight. By traversing beneath plumes withthe mobile instrument, the concentration of the column iscalculated and, once multiplied by the plume velocity,produces a source emission rate. These instruments arelimited to detecting only those species where masks areavailable. They also suffer from interferences from otheratmospheric gases and light scattering from clouds oraerosols that can produce errors in column densities(Chalmers Radio and Space Science, website).

The DOAS technique is a relatively new technique that isgaining widespread acceptance as an air pollution moni-toring method. Like the open-path FT-IR method, the DOAScan simultaneously measure concentrations of a number ofspecies over path lengths which typically range fromhundreds of metres to kilometres.

A DOAS, configured as an ‘active system’, Fig. 1, has threemain parts – a light emitter, a light receiver and a spec-trometer. The emitter sends a beam of light to the receiver(in some cases the emitter and receiver are contained in thesame unit and the light beam is reflected off a remotelylocated passive reflector). The light beam contains a rangeof wavelengths, from ultraviolet to visible, althoughinstruments are now available with an infrared source,which extends the range of compounds that can bedetected. Different pollutant molecules absorb light atdifferent wavelengths along the path between the emitterand receiver. The receiver is connected to the spectrometerwhich measures the intensity of the different wavelengthsover the entire light path and through the data systemconverts this signal into concentrations for each of thespecies being monitored.

DOAS instruments are routinely used to measure SO2,NO2 and O3.

More recently, advances in miniaturising UV–vis spec-trometers has lead to the development of much morecompact DOAS units, configured as a passive system (Fig. 1),which have come to be known as ‘‘mini-DOAS’’. The mini-DOAS system has so far been used mainly in the study ofSO2 fluxes in volcanic emissions (McGonigle et al., 2003).

2. Methodology

2.1. Field measurements

A portable DOAS (mini-DOAS) manufactured by Reso-nance Ltd was used in this study. The instrument covers

a spectral range of 280–420 nm and can measure sub-partper million levels of NO2 and SO2. The unit, whichcomprises a telescope, scanning mirrors, calibration cellsand a miniature CCD array spectrometer (Ocean OpticsUSB2000 spectrometer), is housed in a small packagewhich is mounted on a tripod. Calibration of the instrumentwas carried out using the internal calibration cell. Theconcentration of the cell was equivalent 50 ppm m. No SOx

measurements were undertaken.Data collection and processing were performed by

Ocean Optics OOIBase32 software loaded in a laptopcomputer. This results in a more compact system that iseasier to deploy at mine sites and provides greater flexi-bility in positioning the instrument in relation to the blastplume.

Prior to each monitored blast, a dark spectrum wascollected by blocking light from entering the spectrometerand a scan was performed. To produce a reference spec-trum, a further scan was performed in a clear sky back-ground which contained background absorption from NO2.The reference spectrum was required in order to determinethe increase in concentration of NO2 above ambient levelsin the blast plumes.

The plume resulting from each blast was tracked withthe spectrometer until the NO2 concentration was indis-tinguishable from the surrounding sky. During each fieldmeasurement, the mini-DOAS and a video camera werepositioned a safe operating distance from the blast at alltimes.

NO2 concentrations in the plume were calculated bysubtracting the dark spectrum from the measured spec-trum and the reference spectrum using the suppliedsoftware.

The results obtained from the mini-DOAS are a path-averaged NO2 concentration profile measured in units ofparts per million metre (ppm m). The mini-DOAS resultsmust be divided by the path length through the plume toyield a concentration. To estimate the amount of NO2

released from each blast it was necessary to multiply theconcentration by the volume of the plume. Hence it wasnecessary to estimate the dimensions of each plume.

All of the blasts monitored were video-taped using atleast one, and sometimes two, video recorders. Thedistances between the cameras and the blast weremeasured by locating their positions with a handheld GPSreceiver.

Fig. 1. Schematic diagram of DOAS systems operating in both active and passive modes.

M.I. Attalla et al. / Atmospheric Environment 42 (2008) 7874–78837876

PNB000811

Wind speed and directional data used to plot thedirectional path of the plume were obtained from a seriesof meteorological stations located around the mining lease.Simple trigonometry was employed to determine thedistance from the video camera to the plume at thecorresponding time intervals.

A rudimentary method of photogrammetry was thenused to estimate the size of the plume based on still imagesextracted from the videos. Ratios of the plume to picturesize in both the vertical and horizontal planes were made.

Once the plume to camera distance and the constrainingangle for the plume is known, a crude three-dimensionalestimate of the plume dimension was calculated using basictrigonometric functions. An example of the dimensionsdetermined for a plume using this method is shown in Fig. 2.

Ground level measurements were carried out usinga Greenline 8000 portable gas analyser. This instrument iscapable of continuous, simultaneous analysis of O2, CO2,CO, SO2, NO and NO2. It is battery powered and can operateunattended for up to about 2 h. The instrument wascalibrated against a standard gas mixture before each use.Data were logged on a laptop computer connected to theinstrument.

For each experiment, the instrument was set updownwind of the blast in a location where the plume wasexpected to pass, but far enough away to avoid flying debris.The inlet probe was fixed at about 2 m above ground level.

It must be noted that selecting an appropriate locationfor the instrument was often difficult. In many cases,the wind conditions were quite variable, especiallywithin the pit so it was not always possible to correctlyanticipate the path of the blast plume. As well, the layout ofthe mine pit and safety considerations imposed constraintson where the instrument could be placed. Because of theseproblems, the plumes from many of the blasts did not passover the analyser and data was not recorded.

2.2. Modelling

A simple modelling exercise was undertaken for thisstudy to determine if the release of NO2 from a blast couldbe of detriment to persons exposed to the plume within

5 km of the release. The results of this study are indicativeand based on the assumption that the model used isappropriate. Modelling generally relies on local observa-tional data to confirm the performance of the model. Thedifficulty in measuring emissions from mining blasts hasmeant that in this case the model is used as an indicatorrelying on the verifications used in the development of thechosen model. For this reason we have modelled concen-trations directly downwind of theoretical blasts with AFTOX(Kunkel, 1991), a USEPA approved dispersion model (http://www.epa.gov/scram001/dispersion_alt.htm#aftox). Theoriginal DOS based QuickBasic code was transformed intoExcel macros to enable many scenarios to be run.

AFTOX is a Gaussian Puff model developed for theUnited States Air Force to assess real time toxic chemicalreleases. The model uses information from US Air WeatherService (AWS) stations to calculate dispersion based onmeasured atmospheric conditions. As for all Gaussianmodels, the spread of pollutants is governed by dispersioncoefficients in the horizontal (sy) and vertical (sz) direc-tions. These coefficients depend on the atmosphericstability derived from the AWS data. In this study, thescenarios were modelled by predefining the wind speedand atmospheric stability classes. The wind speedsmodelled ranged from very low (0.5 m s�1) to moderate(10 m s�1). Stability was modelled in six steps representingthe standard Pasquill-Gifford stability classes, i.e. A–F,where A, B and C represent unstable conditions (where A isthe most unstable), D is neutral and E and F are stableconditions. These stability classes are used to categorise therate at which a plume will disperse. Unstable conditionsmight be found on a sunny day with light winds leading torapid plume dispersion while the stable conditions mayoccur in clear skies with light winds and perhapsa temperature inversion present. Plume spread is slow inthese circumstances.

AFTOX is operated by assuming an emission releasefrom a single location. The emissions can be eithercontinuous or instantaneous. In this study AFTOX was usedto describe an area source by representing it as a largenumber of individual points. The area of the emission (i.e.the area over which the explosives were distributed) was

Fig. 2. Blast plume with estimated dimensions.


PNB000812

http://www.epa.gov/scram001/dispersion_alt.htm%23aftox

http://www.epa.gov/scram001/dispersion_alt.htm%23aftox

assumed to be 100 m� 200 m based upon sizes commonlyobserved during the field measurements. The area wassubdivided into 10 m� 10 m units. Each square was rep-resented by a point source with its source at the centre. Intotal, the area was modelled as 231 separate point sources(see Fig. 3). The total flux of emissions for the source was setat 100 kg. To estimate the maximum concentration andpollutant exposure values, the values should be multipliedby an appropriate scaling factor.

One hundred and twenty scenarios were modelled inwhich the 100 kg of emissions were spread randomlythroughout the source area. A multi-stage process wasemployed for this task. In the first step, the total maximumnumber of points emitting was determined. This wasdefined by a random number between 20% and 80% of themaximum number of sources (in this case 231). The rangechosen was an estimate from the portion of blasts thatappeared to fume in conditions witnessed during this study.The total emission was then divided by this number. Eachportion of the total emission was then placed randomlywithin the emission area. This process allowed certainpoints to receive multiple portions of the total emissionsenabling the formation of hot spots. An example of oneemission grid (Scenario 1 of 120) is displayed in Fig. 4.

Concentrations were determined for each of the 120emission scenarios at distances of 200 m, 300 m, 400 m,500 m, 750 m, 1 km, 1.25 km, 1.5 km, 2 km, 2.5 km, 3 km,4 km and 5 km from the origin of the source. A concen-tration was determined for a number of discrete times thatencompassed the complete plume travelling past thereceptor. Further the concentrations were determined at 21locations 10 m apart in a plane parallel and directlydownwind of the source area (see Fig. 3). An averageconcentration from each of the receptors was determined;in this case with N equal to 21.

C� ¼ 1

N

XN

i¼1

Ci (5)

The average for each scenario was then used to create anensemble average and standard deviation for the entire run(i.e. N¼ 120).

C ¼ 1N

XN

j¼1

C�

j (6)

sC ¼1N

XN

j¼1

�C�

j � C�2

(7)

Cmax ¼ maxNk¼1½Ck� (8)

A dosage expressed in ppm s was determined from thetimes when the ensemble average plume travelled past thereceptors located at each distance downwind of the source.Again N represents each discrete time step (dt) whereC 0 s 0.

Cdose ¼XN

k¼1

ðCkÞdt (9)

The relative variation for the dosage is provided bysimilarly treating the ensemble standard deviation.

sdose ¼XN

k¼1

ðsCkÞdt (10)

3. Results and discussion

3.1. Field measurements

Plume measurements were made using the mini-DOASspectrometer at two open-cut mine sites located inthe Hunter Valley. The combination of the spectral analysisand the plume estimation technique allowed for NO2

concentration and mass flux estimates to be maderemotely, totally eliminating the requirement of physicalsampling.

An example of the spectral output produced by themini-DOAS is shown in Fig. 5. The spectral output consistsof the NO2 concentration (ppm m) as a function of time. Thefigure also contains a series of photographs depicting theformation of a blast plume at time intervals of 70, 110, 163,250 and 350 s post-blast initiation. It is worth noting thechange in intensity of the colour of plume and size asa function of time.

Reliable concentration measurements with the mini-DOAS may only be made when the spectrometer is aimedinto a sky background above the horizon from the point ofobservation. In this example, a peak concentration of580 ppm m was achieved in 163 s post-blast initiation(third image from the left). At this time the plume has risenabove the horizon from the point of observation. The plumeto mini-DOAS distance at this stage is approximately500 m, with an estimated plume depth of 105 m. Thisresults in a NO2 concentration of 5.6 ppm at that particularstage of the plumes’ dispersion.

After 350 s, the plume is barely visible and is now esti-mated to be approximately 650 m from the mini-DOASunit. The plume depth has increased to 125 m with

(0,0)

(200m)

(300m)

(5000m)

Fig. 3. Emission grid and receptor array setup.


PNB000813

a corresponding increase in plume volume by a factor oftwo. This expansion of the plume corresponds to a decreasein NO2 concentration to 2.8 ppm.

At 360 s the plume was no longer visible to the eye andwas lost for a short period of time to the mini-DOAS. This,however, was rectified with scanning of the sky with thespectrometer until the invisible plume was tracked fora further period.

Results for all plumes monitored during field work atboth mine sites are given in Table 1. The table gives the peakNO2 concentration as measured by the mini-DOAS abovethe horizon. Also given in the table is the plume volume atpeak concentration and the calculated mass of NO2

released from the blast. The mass of ANFO typically used ina blast was on average 210 tonnes, ranging from 60 to

565 tonnes. The explosive was distributed over an area oftypically 200 m� 100 m containing approximately 200bole holes with 200 mm diameter and to a depth of 25 m.

From the table the maximum NO2 concentrations werefound to range from 0 to about 7 ppm. This range ofconcentrations translated to 0–63.3 kg of NO2 in the plume.However, no correlation can be made between blast chargeand NO2 levels.

During the measurements with the mini-DOAS groundlevel measurements were also carried out using a portablecombustion gas analyser (Greenline 8000) to augment theairborne measurements made by the mini-DOAS. For NO2

the ground level measures were higher than thoseobserved using the mini-DOAS at higher altitudes. Whenthe results of both measurement methods were applied to

-100 -80 -60 -40 -20 0 20 40 60 80 100

Crosswind distance (m)

0

20

40

60

80

100

Dow

nwin

d di

stan

ce (

m)

02468

10121416182022242628303234363840

Fig. 4. Example of emission grid for 1 of the 120 scenarios modelled (the scale on the right hand side refers to NO2 concentration in ppm).

0

50

100

150

200

250

300

350

400

450

500

550

600

650

-150 -100 -50 0 50 100 150 200 250 300 350 400 450 500 550 600

NO

2 c

once

ntra

tion

(pp

m m

)

Elapsed time from shot initiation (s)

50 ppm mcalibration

backgroundmeasurement in clear sky

70 110 163 250 350

Fig. 5. Typical NO2 spectrum demonstrating plume colour characteristics relative to concentration level.


PNB000814

dispersion modelling techniques strong agreement wasobserved.

Point measurements which were made on Greenline8000 indicated that a loose relationship existed between

NO and NO2 concentration. Although a strong correlationwas not found, there is a general trend of increasing NO2

with increasing NO. It was generally found that the relativeproportion of NO to NO2 from our data set was 27 to 1. This

Table 1Through plume measurement results

Date Total ANFOcharge (t)

Peak NO2

Conc (ppm)Plume volume(m3� 10�6)

Mass ofNO2 (kg)

Emission flux (kg t�1 ANFO)

NO NO2 NOx

12/12/2005 281 3.7 1.4 9.9 0.5 0.03 0.613/12/2005 150 0.4 5.3 3.7 0.4 0.03 0.414/12/2005 119 0.0 0.0 0.0 0.0 0.00 0.021/12/2005 229 1.0 4.4 7.9 0.6 0.04 0.622/12/2005 211 0.0 0.0 0.0 0.0 0.00 0.023/12/2005 222 0.0 0.0 0.0 0.0 0.00 0.05/01/2006 177 1.0 0.2 0.4 0.0 0.00 0.06/01/2006 275 1.1 15.3 30.6 1.8 0.12 1.912/01/2006 225 1.6 6.2 18.3 1.3 0.08 1.418/01/2006 169 1.3 1.7 0.2 0.4 0.02 0.423/01/2006 139 2.1 4.2 16.7 1.9 0.12 2.025/01/2006 155 0.4 4.4 2.9 0.3 0.02 0.430/01/2006 132 0.7 5.3 7.1 0.8 0.05 0.922/02/2006 224 0.0 0.00 0.0 0.0 0.00 0.01/03/2006 194 1.6 20.6 63.3 5.0 0.32 5.312/05/2006 362 6.5 1.9 23.3 1.0 0.06 1.115/05/2006 131 0.3 3.2 1.7 0.2 0.01 0.219/05/2006 168 0.0 0.00 0.0 0.0 0.00 0.030/05/2006 100 0.8 0.00 1.0 0.0 0.00 0.01/06/2006 365 0.7 3.5 4.9 0.2 0.01 0.26/06/2006 145 0.8 11.5 17.5 1.9 0.12 2.015/06/2006 60 0.0 0.00 0.0 0.0 0.00 0.026/06/2006 254 4.3 0.3 2.1 0.1 0.01 0.227/06/2006 212 5.6 0.9 10.0 0.7 0.04 0.728/06/2006 241 0.0 0.00 0.0 0.0 0.00 0.06/07/2006 565 2.8 2.7 14.0 0.4 0.03 0.413/07/2006 184 7.0 1.0 12.6 1.1 0.07 1.2

Table 2Maximum calculated NO2 concentrations downwind of source

200 m 300 m 400 m 500 m 750 m 1000 m 1250 m 1500 m 2000 m 2500 m 3000 m 4000 m 5000 m

WSPD¼ 0.5 m s�1

Stab A 83.0 30.0 14.4 7.9 2.5 0.9 0.4 0.2 0.1 0.0 0.0 0.0 0.0Stab B 145.8 69.3 40.8 25.4 10.1 4.8 2.6 1.6 0.7 0.4 0.2 0.1 0.1Stab C 219.4 122.0 80.8 55.9 26.8 14.3 8.6 5.6 2.8 1.6 1.0 0.5 0.3Stab D 321.1 201.5 146.0 113.1 64.6 40.2 26.1 18.6 10.5 6.7 4.5 2.4 1.4Stab E 390.2 267.4 204.3 165.5 109.6 75.9 54.6 41.3 26.4 17.9 12.7 7.1 4.5Stab F 464.1 339.8 269.0 222.6 154.5 114.9 88.6 69.7 50.4 37.0 27.8 16.7 11.0

WSPD¼ 3 m s�1


WSPD¼ 7.5 m s�1


WSPD¼ 10 m s�1



PNB000815

relationship enabled the estimation of the NO fluxes in theblast plume with a reasonable level of confidence.

The results obtained in this study are the only publishedquantitative data available on blast plume gas compositionthat the authors are aware of and it is useful to comparethem to the emission factors currently used for NPIestimates.

Based on the NO2 measurements and estimates of NO,the flux for NOx was calculated to be in the range of 0.04–5.3 kg t�1 ANFO. The average flux level for all the blastplumes measured was 0.9 kg t�1. This figure is considerablylower than the current NPI emission factor which is 8 kg t�1.

3.2. Modelling

Results of the modelling runs are summarised in Table 2and show the peak NO2 concentrations (ppm) at variouspoints downwind of the blast for the six atmosphericstability classes considered.

Examples of the modelled data are plotted in Fig. 6 andFig. 7. In Fig. 6 a plot is displayed for the concentrationestimate of one scenario at a distance of 200 m from thesource origin and for a wind speed of 2 m s�1 and a stabilityclass C. In this plot 21 lines are shown representing the dosereceived directly downwind of the source at the locationsdisplayed in Fig. 3. In this figure it is apparent that there isa considerable difference in the concentration predicted ateach of the 21 receptors. It should be noted that thedistance of 200 m is defined from the origin of the sourcearea (0, 0) as displayed in Fig. 3. At this distance emissionsources at 100 m will cause significantly higher concen-trations than those occurring at positions toward theorigin. In comparison the concentrations predicted at thereceptor array 1 km from the source show more normallydefined distributions with maxima occurring towards themiddle receptors as a result of crosswind diffusion.

Receptors toward the edge of the sample array receive lesscrosswind influence and are, therefore, smaller in concen-tration. Also apparent in these two figures is the consid-erable difference in the predicted peak concentrations withthe values at 1 km up to 25 times lower than at 200 m.When viewing Table 2, the peak values at 5 km approachambient levels for all but the most stable conditions whichare quite commonly over predicted with Gaussian models.For future studies it is recommended that a long pathtechnique on a mining lease boundary may provide botha measure of the model accuracy as well as a direct measureof the impact in areas directly surrounding the mining area.

The data presented in this study represent a dose directlydownwind of the source and as such are a worst casescenario for exposure. The averages of the 21 receptors (i.e.the average concentration directly downwind of the source)for each of the 120 scenarios modelled were used to deter-mine the selected data. The number of scenarios modelledwas arbitrarily chosen to allow 10 scenarios to be run oneach machine in a cluster of 12 computers. The maximumconcentration in Table 2 is the maximum ensemble averageobtained from the average of the 21 receptors for the 120scenarios modelled. Maximum concentrations at individuallocations directly downwind of hot spots are obviouslyhigher than the values reported in this table.

When viewing Table 2 it is apparent that the peakconcentrations drop dramatically as the receptor movesaway from the source. It is also apparent that the peakconcentrations vary little as a function of wind speedalthough the plume width will vary. In AFTOX a downwindconcentration is determined in two steps. In the first stepthe size of the initial plume envelope is estimated. In itsdefault mode AFTOX determines the size of the envelope(assumed to be a cylinder of equal height and width) fromthe magnitude of the emission rate. In this report the size isset at 10 m to match the grid structure used for the area

0

50

100

150

200

250

300

350

400

450

500

0.5 0.75 1 1.25 1.5 1.75 2 2.25 2.5

Time since blast (min)

Con

cent

rati

on (

ppm

)

Receptor_1

Receptor_2

Receptor_3

Receptor_4

Receptor_5

Receptor_6

Receptor_7

Receptor_8

Receptor_9

Receptor_10

Receptor_11

Receptor_12

Receptor_13

Receptor_14

Receptor_15

Receptor_16

Receptor_17

Receptor_18

Receptor_19

Receptor_20

Receptor_21

Fig. 6. Calculated NO2 concentration profiles 200 m from source.


PNB000816

source. AFTOX in this regard ignores the effect of windspeed on the size of the initial envelope and as such theinitial concentration of the plume is identical irrespectiveof wind speed by ignoring longitudinal (i.e. downwind)spread of the initial release. In the second step theconcentration downwind of the initial release is deter-mined by estimating the growth of a puff in three dimen-sions which in this case explicitly includes longitudinalplume spread which is assumed to be equal to the degree ofcrosswind spread. The degree of this spread is determinedsolely from the prescribed atmospheric stability classwhich ignores any wind speed dependence.

While the peak concentrations are similar, the dosereceived at a receptor is linearly dependent on wind speed.Emissions released into an atmosphere with higher windspeeds result in a receptor receiving doses for a smallerperiod of time. It should be noted that some of the differ-ences in the peak concentrations displayed in Table 2 resultfrom the number of discrete time steps used to calculatethe concentrations. This was set at 25 intervals between theonset and finish of a plume as it passes by the receptor. Thistime is dependent on atmospheric stability and thedistance from the source. In AFTOX, the puffs are assumedto disperse in the direction of plume travel proportionallywith the degree of crosswind spread. As such, portions ofthe plume arrive before and after the main bulk of theemissions and the effect clearly demonstrated in Figs. 6 and7. The moderate number of discrete times modelled tocapture this effect while generally adequate may have ledto a degree of variation particularly at larger distances fromthe source.

Again it should be noted that the modelled figuresassume an area wide flux of 100 kg which is larger thanobserved in the blast recorded during this study. It shouldalso be noted that while some of the concentrations arehigh close to the source the concentration at a particular

location occurs for a brief period of time which is deter-mined by the wind speed.

4. Conclusions

A portable open-path spectroscopic method was foundto be effective for measuring NO2 emissions from blasting.Overall this technique was found to be simpler, safer andmore successful than other approaches that in the pasthave proved to be ineffective in monitoring these shortlived plumes.

Quantitative measurements of NO2 in plumes fromblasting were made at two open-cut mines. The resultsshowed that NO2 was present in most of the plumes but inrelatively low concentrations (typically ranging between0 and 7 ppm). The highest concentration measured duringall the field campaigns was about 17 ppm at ground level.

Based on field measurements, the emission factorcurrently used in compiling the Australian NationalPollutant Inventory was found to be approximately eighttimes greater than that observed in our investigation. Thiswould suggest that an over estimation of NOx is made if thecurrent factor is used.

Numerical modelling of the behaviour of plumesresulting from blasting was made to assess the possibledownwind concentrations of NO2. These results werecompared to ambient NOx measurements made inMuswellbrook.

� Modelling results were consistent with concentrationmeasurements within the plumes at relatively shortdistances from the blast (i.e. up to about 1 km).

� Ambient monitoring did not detect NOx events thatcould be attributed to individual blasts. Modellingsuggested that these emissions would be very low at

0

2

4

6

8

10

12

14

16

18

20

5 6 7 8 9 10 11

Time since blast (min)

Con

cent

rati

on (

ppm

)

Receptor_1

Receptor_2

Receptor_3

Receptor_4

Receptor_5

Receptor_6

Receptor_7

Receptor_8

Receptor_9

Receptor_10

Receptor_11

Receptor_12

Receptor_13

Receptor_14

Receptor_15

Receptor_16

Receptor_17

Receptor_18

Receptor_19

Receptor_20

Receptor_21

Fig. 7. Calculated NO2 concentration profiles 1 km from source.


PNB000817

distances greater than 5 km from the blast and may beindistinguishable from background levels; typically ofthe order of several parts per billion, in most cases.

Acknowledgements

We gratefully acknowledge the financial support of theAustralian Coal Association Research Program (ACARP) andthe staff at the Hunter Valley mine sites.

References

Chalmers Radio, Space Science. The optical remote sensing group. Avail-able from: <http://www.rss.chalmers.se/ors/ >.

Galle, B., Oppenheimer, C., Geyer, A., McGonigle, A.J.S., Edmonds, M.,Horrocks, L., 2002. A miniaturised ultraviolet spectrometer for remotesensing of SO2 fluxes: a new tool for volcano surveillance. Journal ofVolcanology and Geothermal Research 119, 241–254.

Kirchgessner, D.A., Piccot, S.D., Chadha, A., 1993. Estimation of methaneemissions from a surface coal mine using open-path FTIR spectro-scopy and modelling techniques. Chemosphere 26, 23–44.

Kunkel, B.A., 1991. AFTOX 4.0 – The Air Force Toxic Chemical DispersionModel – A User’s Guide. PL-TR-91-2119, Environmental ResearchPapers No. 1083, Phillips Laboratory, Directorate of Geophysics, AirForce Systems Command, Hanscom AFB, MA 01731-5000, p. 62.

Levine, S.P., Russwurm, G.M., 1994. Fourier transform infrared opticalremote sensing for monitoring airborne gas and vapour contaminantsin the field. Trends in Analytical Chemistry 13, 263–266.

Moffat, A.J., Milan, M.M., 1971. The applications of optical correlationtechniques to the remote sensing of SO2 plumes using sky light.Atmospheric Environment 5, 677–690.

McGonigle, A.J.S., Thomson, C.L., Tsanev, V.I., Oppenheimer, C., 2003. Asimple technique for measuring power station SO2 and NO2emissions. Atmospheric Environment 38, 21–25.

National Pollutant Inventory, 1999. Emission Estimation TechniqueManual for Explosives Detonation and Firing Ranges. EnvironmentAustralia. Available from: <http://www.npi.gov.au/handbooks/approved_handbooks/fexplos.html>.

Piccot, S., Masemore, S., Ringler, E., Srinivasan, S., Kirchgessner, D.,Herget, W., 1994. Validation of a method for estimating pollutionemission rates from area sources using open-path FTIR spectroscopyand dispersion modelling techniques. Journal of the Air & WasteManagement Association 44, 271–279.

Piccot, S., Masemore, S., Ringler, E., Bevan, W.L., Harris, D.H., 1996. Fieldassessment of a new method for estimating emission rates fromvolume sources using open-path FTIR spectroscopy. Journal of the Air& Waste Management Association 46, 159–171.


PNB000818

http://www.rss.chalmers.se/ors

http://www.npi.gov.au/handbooks/approved_handbooks/fexplos.html

http://www.npi.gov.au/handbooks/approved_handbooks/fexplos.html

Site Name

State

(facilit

y) Facility Description Equipment class Equipment description Fuel Type

Equipment

capacity

Control

Equipment 1

Control

Equipment 2 Test date

Load (% of

capacity)

Operation

mode

Output

units Avg. NO2 Avg Nox Ratio

Reporting

entity

Peter Pan Seafoods King Cove Facility Ak Seafood Processor Reciprocating IC Engine Detroit Diesel 16V149TI Diesel/Kerosene 1,000 kW Uncontrolled Uncontrolled 10/25/2012 35 Routine ppmv 26.2 438 0.0598174 ADEC

Peter Pan Seafoods King Cove Facility AK Seafood Processor Reciprocating IC Engine Detroit Diesel 16V149TI Diesel/Kerosene 1,000 kW Uncontrolled Uncontrolled 10/26/2012 48 Routine ppmv 26.7 628 0.0425159 ADEC



Tok Power Generation Station AK Power Plant Reciprocating IC Engine Caterpillar 3512C Diesel/Kerosene 1,050 kW Uncontrolled 4/13/2012 30 Routine ppmv 15 415 0.0361446 ADEC

Tok Power Generation Station AK Power Plant Reciprocating IC Engine Caterpillar 3512C Diesel/Kerosene 1,050 kW Uncontrolled 4/13/2012 60 Routine ppmv 12.3 559 0.0220036 ADEC

Tok Power Generation Station AK Power Plant Reciprocating IC Engine Caterpillar 3512C Diesel/Kerosene 1,050 kW Uncontrolled 4/14/2012 90 Routine ppmv 19.4 726 0.0267218 ADEC

Dillingham Power Plant AK Power Plant Reciprocating IC Engine Caterpillar 3512B Diesel/Kerosene 1,050 kW‐e Uncontrolled Uncontrolled 10/2/2012 100 Routine ppmv 66.9 1056 0.0633523 ADEC




Peter Pan Seafoods King Cove Facility Ak Seafood Processor Reciprocating IC Engine Caterpillar 3516 Diesel/Kerosene 1,100 kW Uncontrolled Uncontrolled 10/24/2012 47 Routine ppmv 164.2 1665 0.0986186 ADEC

Peter Pan Seafoods King Cove Facility AK Seafood Processor Reciprocating IC Engine Caterpillar 3516 Diesel/Kerosene 1,100 kW Uncontrolled Uncontrolled 10/24/2012 65 Routine ppmv 165.2 1860 0.0888172 ADEC



Tok Power Generation Station AK Power Plant Reciprocating IC Engine Caterpillar 3516 Diesel/Kerosene 1,135 kW Uncontrolled 4/14/2012 40 Routine ppmv 128.4 1534 0.0837027 ADEC



Tok Power Generation Station AK Power Plant Reciprocating IC Engine Caterpillar 3516B Diesel/Kerosene 1,285 kW Uncontrolled 4/11/2012 30 Routine ppmv 54.7 901 0.0607103 ADEC



Peter Pan Seafoods King Cove Facility Ak Seafood Processor Reciprocating IC Engine Caterpillar 3606 Diesel/Kerosene 1,500 kW Uncontrolled Uncontrolled 10/23/2012 100 Routine ppmv 147 1861 0.0789898 ADEC




Tok Power Generation Station AK Power Plant Reciprocating IC Engine Caterpillar C175‐16 Diesel/Kerosene 1,930 kW Uncontrolled 4/12/2012 60 Routine ppmv 14.5 503 0.028827 ADEC



DU‐JBER‐Electric, Gas, Drinking Water and SaAK LFG Power Plant Reciprocating IC Engine Jenbacher JGS 420 EnginDiesel/Kerosene 1,966 bhp Not listed ‐ providUncontrolled 11/26/2012 100 Routine ppmv 21 95 0.2210526 ADEC

Dillingham Power Plant AK Power Plant Reciprocating IC Engine Caterpillar 3512B Diesel/Kerosene 1.050 kW‐e Uncontrolled Uncontrolled 10/4/2012 100 Routine ppmv 59.3 1003 0.0591226 ADEC

Peter Pan Seafoods King Cove Facility AK Seafood Processor Reciprocating IC Engine Caterpillar 3412 Diesel/Kerosene 1.54 MMBtuUncontrolled Uncontrolled 10/28/2012 100 Routine ppmv 34.8 657 0.052968 ADEC

Dutch Harbor Power Plant AK Power Plant Reciprocating IC Engine Caterpillar C‐280 Diesel/Kerosene 4,400 kW‐e Centrifugal CollecUncontrolled 8/8/2012 100 Routine ppmv 48 1066 0.0450281 ADEC

Tok Power Generation Station AK Power Plant Reciprocating IC Engine Caterpillar 3516 Diesel/Kerosene 440 kW Uncontrolled 4/15/2012 30 Routine ppmv 79.9 1186 0.0673693 ADEC

Tok Power Generation Station AK Power Plant Reciprocating IC Engine Caterpillar 3516 Diesel/Kerosene 440 kW Uncontrolled 4/15/2012 70 Routine ppmv 133.3 1914 0.0696447 ADEC

Tok Power Generation Station AK Power Plant Reciprocating IC Engine Caterpillar 3516 Diesel/Kerosene 440 kW Uncontrolled 4/16/2012 100 Routine ppmv 167 2241 0.0745203 ADEC

Dutch Harbo Power Plant AK Power Plant Reciprocating IC Engine Wartsila Model 12V32C Diesel/Kerosene 5211 kWe Uncontrolled Uncontrolled 2/2/2011 50 Routine ppmv 62.1 1125 0.0552 ADEC

Peter Pan Seafoods King Cove Facility Ak Seafood Processor Reciprocating IC Engine Caterpillar 3512 Diesel/Kerosene 810 kW Uncontrolled Uncontrolled 10/27/2012 99 Routine ppmv 146.5 1842 0.0795331 ADEC

Peter Pan Seafoods King Cove Facility AK Seafood Processor Reciprocating IC Engine Caterpillar 3512 Diesel/Kerosene 810 kW Uncontrolled Uncontrolled 10/27/2012 84 Routine ppmv 155 1875 0.0826667 ADEC

Peter Pan Seafoods King Cove Facility AK Seafood Processor Reciprocating IC Engine Caterpillar 3512 Diesel/Kerosene 810 kW Uncontrolled Uncontrolled 10/27/2012 69 Routine ppmv 163.9 1857 0.0882606 ADEC

Peter Pan Seafoods King Cove Facility AK Seafood Processor Reciprocating IC Engine Caterpillar 3512 Diesel/Kerosene 810 kW Uncontrolled Uncontrolled 10/28/2012 49 Routine ppmv 171.5 1789 0.0958636 ADEC

avg 0.065471

max 0.221053

min 0.022004

median 0.064939

PNB000819

Rosemont Copper Project | Amended Model Report Trinity Consultants E-1

APPENDIX E: PARTICLE SIZE DISTRIBUTIONS

PNB000820


1. PARTICLE SIZE DISTRIBUTIONS The following sections describe the methodology used to estimate the particle size distributions for

various emission sources.

1.1 Haul Roads Section 13.2.4 of AP 42 lists the emission factors for emissions from unpaved roads. These emission

factors were used to determine the distribution of emissions for particles with nominal diameters less

than 30, 10 and 2.5 m. Figure E.1 shows the distribution.

Figure E.1 Average size distribution for air borne dust generated by haul trucks for entire

study period.

A 2nd degree polynomial equation was used to fit the data and determine particle size distributions for

use with haul road emissions from the Rosemont mine. Table A.1 shows the calculated particle size

distribution that will be used for haul road emissions.

PNB000821


Table E.1 Particle Size Distribution ‐ Haul Road Emissions

Diameter (microns) Mass Fraction

Density (gm/cm3)

2.2 0.069 2.44

3.17 0.128 2.44

6.1 0.385 2.44

7.82 0.224 2.44

9.32 0.194 2.44

1.2 Material Transfer Section 13.2.4 of AP 42 lists the emission factors for Aggregate Handling process. These emission

factors were used to determine the distribution of emissions for particles with nominal diameters less

than 30, 15, 10, 5 and 2.5 m. Figure E.2 shows the distribution.

Figure E.2 Material Transfer Emissions (tpy) vs Particle Size (m)

A 2nd degree polynomial was used to fit this data and determine the size distribution for other particle

sizes. Table E.2 shows the calculated particle size distribution that will be used for material transfer

emissions.

PNB000822


Table E.2 Particle Size Distribution ‐Material Transfer Points Diameter (microns) Mass Fraction

Density (gm/cm3)

2.2 0.188 2.44

3.17 0.122 2.44

6.1 0.347 2.44

7.82 0.188 2.44

9.32 0.155 2.44

1.3 Blasting Table 11.9-1 from section 11.9 of AP 42 lists the emission factors for Western Surface Coal Mining

processes. The Blasting emission factors were used to determine the distribution of emissions for

particles with nominal diameters less than 30, 10 and 2.5 m. Figure E.3 shows the distribution.

Figure E.3 Blasting Emissions (tpy) vs Particle Size (m)

A 2nd degree polynomial was used to fit this data and determine the size distribution for other particle

sizes. Table E.3 shows the calculated particle size distribution that will be used for material transfer

emissions.

PNB000823


Table E.3 Particle Size Distribution ‐ Blasting Emissions Diameter (microns) Mass Fraction

Density (gm/cm3)

2.2 0.015 2.44

3.17 0.153 2.44

6.1 0.426 2.44

7.82 0.225 2.44

9.32 0.181 2.44

1.4 Point Sources Page B.2-6, Appendix B.2 of AP 42 lists the collection efficiency of fabric filters used in baghouses for

various particle sizes. These collection efficiencies were used along with particle size fractions for

Aggregate handling processes (Section 13.2.4 of AP 42) to the calculate particle size distribution that

will be used for point source emissions. Figure E.4 shows the distribution.

Figure E.4 Point Source Emissions (tpy) vs Particle Size

A 2nd degree polynomial was used to fit this data and determine the size distribution for other particle sizes. The obtained size distribution was then used along with the collection efficiency of the

PNB000824


baghouses for various sizes of particles. Table E.4 shows the collection efficiencies of fabric filters

used in baghouses.

Table E.4 Collection Efficiency of Fabric FiltersDiameter (microns)

Collection Efficiency (%)

0 ‐ 2.5 99.0

2.5 – 6 99.5

6 ‐ 10 99.5

Table E.5 shows the calculated particle size distribution that will be used for point source emissions.

Table E.5 Particle Size Distribution – Point Source Emissions

Diameter (microns) Mass Fraction

Density (gm/cm3)

2.2 0.317 2.44

3.32 0.103 2.44

6.1 0.292 2.44

7.8 0.158 2.44

9.32 0.130 2.44

PNB000825

Rosemont Copper Project | Amended Model Report Trinity Consultants F-1

APPENDIX F: HAUL TRUCK TRAVEL AND VMTS

PNB000826

Rosemont Project

Emissions Inventory For Haul Trucks

Hudbay, RP16Aug

Year Yr ‐1 Yr01 Yr02 Yr03 Yr04 Yr05 Yr06 Yr07 Yr08 Yr09 Yr10 Yr11 Yr12 Yr13 Yr14 Yr15 Yr16 Yr17 Yr18 Yr19 TOTALTotal Truck Fleet RP16Aug 23 25 25 28 33 34 38 38 38 34 33 33 33 18 18 14 14 13 5 5

Trucks ‐ metered hours per shift RP16Aug 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9

Truck Shifts Ore to Crusher RP16Aug 0 2,696 4,548 5,200 5,774 5,868 6,939 6,615 7,043 6,942 6,370 4,561 6,648 5,836 9,481 8,020 8,000 4,774 0 0

Truck Shifts Ore to Stockpile RP16Aug 1,331 550 1,801 2,316 466 1,161 1,497 417 857 0 0 0 0 0 0 0 0 0 0 0

Truck Shifts Waste RP16Aug 12,193 13,650 11,611 12,337 16,806 16,955 18,588 19,943 19,497 16,801 16,823 18,081 16,588 7,005 3,276 1,312 1,974 2,250 0 0

Truck Shifts Stockpile to Crusher RP16Aug 0 398 0 0 0 0 0 0 0 0 0 389 0 0 0 0 0 1,398 2,748 457

Quantity of ore mined per year 0 24,511,335 32,850,000 32,850,000 32,850,000 32,850,000 32,850,000 32,850,000 32,850,000 32,850,000 32,850,000 29,328,784 32,850,000 32,850,000 32,850,000 32,850,000 32,850,000 16,107,532 0 0 529,847,651 tons/year Quantity of sulfide ore mined per yearMaximum quantity of sulfide ore mined per day (based on the maximum mill throughput rate) after ramp up in year 1

0 67,154 90,000 90,000 90,000 90,000 90,000 90,000 90,000 90,000 90,000 80,353 90,000 90,000 90,000 90,000 90,000 44,130 0 0 tons/day Maximum quantity of sulfide ore mined per day (based on the maximum mill throughput rate) after ramp up in year 1

Maximum quantity of sulfide ore mined per hour. Based on maximum hourly mill capacity 0 3,039 4,073 4,073 4,073 4,073 4,073 4,073 4,073 4,073 4,073 3,636 4,073 4,073 4,073 4,073 4,073 1,997 0 0 tons/hour Maximum quantity of sulfide ore mined per hour. Based on

maximum hourly crusher capacityType of transfer to the haul trucks In the Pit In the Pit In the Pit In the Pit In the Pit In the Pit In the Pit In the Pit In the Pit In the Pit In the Pit In the Pit In the Pit In the Pit In the Pit In the Pit In the Pit In the Pit In the Pit In the Pit -- Type of transfer to the haul trucks

Type of transfer from the haul trucks Unprotected from Wind

Unprotected from Wind


















Unprotected from Wind -- Type of transfer from the haul trucks

Quantity of waste rock mined per year 93,773,245 99,621,858 86,691,359 85,961,582 96,329,501 93,340,715 92,656,213 97,334,850 95,041,646 99,150,000 99,150,000 99,150,000 61,571,506 25,316,744 8,418,470 3,601,958 5,772,588 5,671,243 0 0 1,248,553,478 tons/year Quantity of waste rock mined per yearMaximum quantity of waste rock mined per day, including oxide heap. Entire fleet operating at 100% efficiency, 2 shifts/day

256,913 272,937 237,511 235,511 263,916 255,728 253,853 266,671 260,388 271,644 271,644 271,644 168,689 69,361 23,064 9,868 15,815 15,538 0 0 tons/dayMaximum quantity of waste rock mined per day, including oxide heap. Entire fleet operating at 100% efficiency, 11.5 metered hours per shift, 2 shifts/day

Maximum quantity of waste rock mined per hour, including oxide ore (based on the maximum daily mining rate divided by 24 hours/day)

10,705 11,372 9,896 9,813 10,997 10,655 10,577 11,111 10,850 11,318 11,318 11,318 7,029 2,890 961 411 659 647 0 0 tons/hourMaximum quantity of waste rock mined per hour, including oxide ore (based on the maximum daily mining rate divided by 23 hours/day)

Type of transfer to the haul trucks (same as the Old MPO) In the Pit In the Pit In the Pit In the Pit In the Pit In the Pit In the Pit In the Pit In the Pit In the Pit In the Pit In the Pit In the Pit In the Pit In the Pit In the Pit In the Pit In the Pit In the Pit In the Pit -- Type of transfer to the haul trucks (same as the Old MPO)

Type of transfer from the haul trucks (same as the Old MPO)




















Unprotected from Wind -- Type of transfer from the haul trucks (same as the Old MPO)

Quantity of ROM ore mined per year. Low Grade ore to stockpile 11,226,755 4,264,392 12,458,641 13,188,418 2,820,499 5,809,285 6,493,787 1,815,150 4,108,354 0 0 0 0 0 0 0 0 0 0 0 62,185,280 tons/year Quantity of ROM ore mined per year. Low Grade ore to stockpile

Maximum quantity of ROM ore mined per day. Low Grade Ore. Enitire fleet operating at 100% efficiency, 2 shifts/day

30,758 11,683 34,133 36,133 7,727 15,916 17,791 4,973 11,256 0 0 0 0 0 0 0 0 0 0 0 tons/dayMaximum quantity of ROM ore mined per day. Low Grade Ore. Enitire fleet operating at 100% efficiency, 11.5 metered hours per shift, 2 shifts/day

Maximum quantity of ROM ore mined per hour (based on the maximum daily ROM mining rate divided by 24 hours/day)

1,282 487 1,422 1,506 322 663 741 207 469 0 0 0 0 0 0 0 0 0 0 0 tons/hour Maximum quantity of ROM ore mined per hour (based on the maximum daily ROM mining rate divided by 23 hours/day)

Quantity of ROM ore reclaimed per year. Year 1 from High Grade Stockpile 0 3,602,415 0 0 0 0 0 0 0 0 0 3,521,216 0 0 0 0 0 16,742,468 32,850,000 5,469,180 62,185,280 tons/year Quantity of ROM ore reclaimed per year. Year 1 from High Grade

StockpileMaximum quantity of ROM ore reclaimed per day. Year 1 High Grade ore 0 9,870 0 0 0 0 0 0 0 0 0 9,647 0 0 0 0 0 45,870 90,000 14,984 tons/day Maximum quantity of ROM ore reclaimed per day. Year 1 High

Grade ore

Maximum quantity of ROM ore reclaimed per hour (equal to the maximum hourly capacity of the Primary Crusher) 0 411 0 0 0 0 0 0 0 0 0 402 0 0 0 0 0 1,911 3,750 624 tons/hour Maximum quantity of ROM ore reclaimed per hour (equal to the

maximum hourly capacity of the Primary Crusher)

Type of transfer to the haul trucks (same as the Old MPO) Unprotected from Wind



















Unprotected from Wind -- Type of transfer to the haul trucks (same as the Old MPO)

Maximum quantity of Tier 2 trucks used during the year 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 trucks Maximum quantity of Tier 2 trucks used during the yearMaximum quantity of Tier 4F trucks used during the year. (Number of trucks in fleet) 23 25 25 28 33 34 38 38 38 34 33 33 33 18 18 14 14 13 5 5 trucks Maximum quantity of Tier 4F trucks used during the year. (Number

of trucks in fleet)Total fleet size (Tier 4F trucks) 23 25 25 28 33 34 38 38 38 34 33 33 33 18 18 14 14 13 5 5 -- Total fleet size (Tier 4F trucks)Empty weight of trucks MSD bodies are assumed 175.0 175.0 175.0 175.0 175.0 175.0 175.0 175.0 175.0 175.0 175.0 175.0 175.0 175.0 175.0 175.0 175.0 175.0 175.0 175.0 tons Empty weight of trucks MSD bodies are assumedCapacity of trucks (from equipment list emailed by David on 04/16/14) 260 260 260 260 260 260 260 260 260 260 260 260 260 260 260 260 260 260 260 260 tons Capacity of trucks (from equipment list emailed by David on

04/16/14)Horsepower rating (from equipment list emailed by David on 04/16/14) 2,650 2,650 2,650 2,650 2,650 2,650 2,650 2,650 2,650 2,650 2,650 2,650 2,650 2,650 2,650 2,650 2,650 2,650 2,650 2,650 hp Horsepower rating (from equipment list emailed by David on

04/16/14)

hours/yearhours/dayhours/hour

Hours of operation per year for the Tier 4F fleet (hours from IMC truck fleet estimate, metered hours) 118,308 151,291 157,113 173,668 201,611 209,810 236,410 235,974 239,668 207,702 202,896 201,480 203,275 111,093 110,351 80,734 86,284 72,853 23,770 3,957 hours/year Hours of operation per year for the Tier 4F fleet (hours from IMC

truck fleet estimate, metered hours)Maximum hours of operation per day for the Tier 4F fleet (assume 24 hours/day for each haul truck) 552 600 600 672 792 816 912 912 912 816 792 792 792 432 432 336 336 312 120 120 hours/day Maximum hours of operation per day for the Tier 4F fleet (assume 24

hours/day for each haul truck)Maximum hours of operation per hour for the Tier 4F fleet (assume 60 minutes/hour per haul truck) 23 25 25 28 33 34 38 38 38 34 33 33 33 18 18 14 14 13 5 5 hours/hour Maximum hours of operation per hour for the Tier 4F fleet (assume

60 minutes/hour per haul truck)Load factor (from equipment list emailed by David on 04/16/14) 0.32 0.32 0.32 0.32 0.32 0.32 0.32 0.32 0.32 0.32 0.32 0.32 0.32 0.32 0.32 1.32 2.32 3.32 4.32 5.32 -- Load factor (from equipment list emailed by David on 04/16/14)

Gasoline or Diesel (same as the Old MPO) Diesel Diesel Diesel Diesel Diesel Diesel Diesel Diesel Diesel Diesel Diesel Diesel Diesel Diesel Diesel Diesel Diesel Diesel Diesel Diesel -- Gasoline or Diesel (same as the Old MPO)On-road or Nonroad engine (same as the Old MPO) Nonroad Nonroad Nonroad Nonroad Nonroad Nonroad Nonroad Nonroad Nonroad Nonroad Nonroad Nonroad Nonroad Nonroad Nonroad Nonroad Nonroad Nonroad Nonroad Nonroad -- On-road or Nonroad engine (same as the Old MPO)Tier Rating (from equipment list emailed by David on 04/16/14) Tier 4I/Tier 4F Tier 4I/Tier 4F Tier 4I/Tier 4F Tier 4I/Tier 4F Tier 4I/Tier 4F Tier 4I/Tier 4F Tier 4I/Tier 4F Tier 4I/Tier 4F Tier 4I/Tier 4F Tier 4I/Tier 4F Tier 4I/Tier 4F Tier 4I/Tier 4F Tier 4I/Tier 4F Tier 4I/Tier 4F Tier 4I/Tier 4F Tier 4I/Tier 4F Tier 4I/Tier 4F Tier 4I/Tier 4F Tier 4I/Tier 4F Tier 4I/Tier 4F -- Tier Rating (from equipment list emailed by David on 04/16/14)

One way distance traveled in the pit when hauling ore directly to the Primary Crusher Dump Hopper (Weighted average distance, ore hauled from several locations in pit)

0 5,625 7,559 8,917 10,251 10,123 12,270 10,993 12,276 12,587 10,298 7,348 11,085 8,820 17,481 12,860 15,244 17,892 0 0 feetOne way distance traveled in the pit when hauling ore directly to the Primary Crusher Dump Hopper (Weighted average distance, ore hauled from several locations in pit)

Vehicle miles traveled per year in the pit when hauling ore directly to the Primary Crusher Dump Hopper (based on mining rates and distance traveled)

0 200,871 361,769 426,747 490,602 484,493 587,229 526,113 587,516 602,382 492,865 313,949 530,525 422,102 836,632 615,451 729,544 419,862 0 0 8,628,653 VMT/yearVehicle miles traveled per year in the pit when hauling ore directly to the Primary Crusher Dump Hopper (based on mining rates and distance traveled)

Maximum vehicle miles traveled per day in the pit when hauling ore directly to the Primary Crusher Dump Hopper (based on mining rates and distance traveled)

0 550 991 1,169 1,344 1,327 1,609 1,441 1,610 1,650 1,350 860 1,453 1,156 2,292 1,686 1,999 1,150 0 0 VMT/dayMaximum vehicle miles traveled per day in the pit when hauling ore directly to the Primary Crusher Dump Hopper (based on mining rates and distance traveled)

Maximum vehicle miles traveled per hour in the pit when hauling ore directly to the Primary Crusher Dump Hopper (based on mining rates and distance traveled)

0 25 45 53 61 60 73 65 73 75 61 39 66 52 104 76 90 52 0 0 VMT/hourMaximum vehicle miles traveled per hour in the pit when hauling ore directly to the Primary Crusher Dump Hopper (based on mining rates and distance traveled)

One way distance traveled out of the pit when hauling ore directly to the Primary Crusher Dump Hopper (Weighted average distance.

0 973 973 973 973 973 973 973 973 973 973 973 973 973 973 973 973 973 0 0 feet One way distance traveled out of the pit when hauling ore directly to the Primary Crusher Dump Hopper (Weighted average distance.

Vehicle miles traveled per year out of the pit when hauling ore directly to the Primary Crusher Dump Hopper (based on mining rates and distance traveled)

0 34,746 46,566 46,566 46,566 46,566 46,566 46,566 46,566 46,566 46,566 41,575 46,566 46,566 46,566 46,566 46,566 22,833 0 0 751,081 VMT/yearVehicle miles traveled per year out of the pit when hauling ore directly to the Primary Crusher Dump Hopper (based on mining rates and distance traveled)

Maximum vehicle miles traveled per day out of the pit when hauling ore directly to the Primary Crusher Dump Hopper (based on mining rates and distance traveled)

0 95 128 128 128 128 128 128 128 128 128 114 128 128 128 128 128 63 0 0 VMT/dayMaximum vehicle miles traveled per day out of the pit when hauling ore directly to the Primary Crusher Dump Hopper (based on mining rates and distance traveled)

Mobile Equipment for Mining

Haul Trucks - General Information

N/A

Mining and Transferring of Waste Rock to be Placed in Storage Areas

Ore (Mill & LG) sent to the ROM Stockpile (to be concentrated)

Mining and Transferring of Ore to be Concentrated (sulfide ore)

Ore (Mill & LG) reclaimed from the ROM Stockpile (to be concentrated)

PNB000827

Rosemont Project


Hudbay, RP16Aug






Truck Shifts Stockpile to Crusher RP16Aug 0 398 0 0 0 0 0 0 0 0 0 389 0 0 0 0 0 1,398 2,748 457

Maximum vehicle miles traveled per hour out of the pit when hauling ore directly to the Primary Crusher Dump Hopper (based on mining rates and distance traveled)

0 4 6 6 6 6 6 6 6 6 6 5 6 6 6 6 6 3 0 0 VMT/hourMaximum vehicle miles traveled per hour out of the pit when hauling ore directly to the Primary Crusher Dump Hopper (based on mining rates and distance traveled)

One way distance traveled in the pit when hauling ore to the ROM Stockpile - Low Grade ore (Weighted average distance, LG ore hauled from several locations in pit)

6,726 5,625 7,559 8,917 10,251 10,123 12,270 10,993 12,276 0 0 0 0 0 0 0 0 0 0 0 feetOne way distance traveled in the pit when hauling ore to the ROM Stockpile - Low Grade ore (Weighted average distance, LG ore hauled from several locations in pit)

Vehicle miles traveled per year in the pit when hauling ore to the ROM Low Grade Ore Stockpile (based on mining rates and distance traveled)

110,018 34,947 137,204 171,328 42,123 85,679 116,083 29,071 73,477 0 0 0 0 0 0 0 0 0 0 0 799,930 VMT/yearVehicle miles traveled per year in the pit when hauling ore to the ROM Low Grade Ore Stockpile (based on mining rates and distance traveled)

Maximum vehicle miles traveled per day in the pit when hauling ore to the ROM Low Grade Ore Stockpile (based on mining rates and distance traveled)

301 96 376 469 115 235 318 80 201 0 0 0 0 0 0 0 0 0 0 0 VMT/dayMaximum vehicle miles traveled per day in the pit when hauling ore to the ROM Low Grade Ore Stockpile (based on mining rates and distance traveled)

Maximum vehicle miles traveled per hour in the pit when hauling ore to the ROM Low Grade Ore Stockpile (based on mining rates and distance traveled)

13 4 16 20 5 10 13 3 8 0 0 0 0 0 0 0 0 0 0 0 VMT/hourMaximum vehicle miles traveled per hour in the pit when hauling ore to the ROM Low Grade Ore Stockpile (based on mining rates and distance traveled)

One way distance traveled out of the pit when hauling ore to the ROM Stockpile - Low Grade ore (Weighted average distance, LG ore hauled to different lifts in stockpile)

1,123 4,442 3,668 5,497 6,409 7,785 6,120 6,076 6,173 0 0 0 0 0 0 0 0 0 0 0 feetOne way distance traveled out of the pit when hauling ore to the ROM Stockpile - Low Grade ore (Weighted average distance, LG ore hauled to different lifts in stockpile)

Vehicle miles traveled per year out of the pit when hauling ore to the ROM Low Grade Ore Stockpile (based on mining rates and distance traveled)

18,360 27,598 66,584 105,620 26,336 65,888 57,898 16,068 36,946 0 0 0 0 0 0 0 0 0 0 0 421,299 VMT/yearVehicle miles traveled per year out of the pit when hauling ore to the ROM Low Grade Ore Stockpile (based on mining rates and distance traveled)

Maximum vehicle miles traveled per day out of the pit when hauling ore to the ROM Low Grade Ore Stockpile (based on mining rates and distance traveled)

50 76 182 289 72 181 159 44 101 0 0 0 0 0 0 0 0 0 0 0 VMT/dayMaximum vehicle miles traveled per day out of the pit when hauling ore to the ROM Low Grade Ore Stockpile (based on mining rates and distance traveled)

Maximum vehicle miles traveled per hour out of the pit when hauling ore to the ROM Low Grade Ore Stockpile (based on mining rates and distance traveled)

2 3 8 12 3 8 7 2 4 0 0 0 0 0 0 0 0 0 0 0 VMT/hourMaximum vehicle miles traveled per hour out of the pit when hauling ore to the ROM Low Grade Ore Stockpile (based on mining rates and distance traveled)

One way distance traveled in the pit when hauling ore from the ROM High or Low Grade Ore Stockpiles to the Primary Crusher Dump Hopper (Average distance, HG & LG ore hauled from different lifts in stockpile)

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 feet

One way distance traveled in the pit when hauling ore from the ROM High or Low Grade Ore Stockpiles to the Primary Crusher Dump Hopper (Average distance, HG & LG ore hauled from different lifts in stockpile)

Vehicle miles traveled per year in the pit when hauling ore from the ROM Stockpile to the Primary Crusher Dump Hopper (based on mining rates and distance traveled)

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 VMT/yearVehicle miles traveled per year in the pit when hauling ore from the ROM Stockpile to the Primary Crusher Dump Hopper (based on mining rates and distance traveled)

Maximum vehicle miles traveled per day in the pit when hauling ore from the ROM Stockpile to the Primary Crusher Dump Hopper (based on mining rates and distance traveled)

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 VMT/dayMaximum vehicle miles traveled per day in the pit when hauling ore from the ROM Stockpile to the Primary Crusher Dump Hopper (based on mining rates and distance traveled)

Maximum vehicle miles traveled per hour in the pit when hauling ore from the ROM Stockpile to the Primary Crusher Dump Hopper (based on mining rates and distance traveled)

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 VMT/hourMaximum vehicle miles traveled per hour in the pit when hauling ore from the ROM Stockpile to the Primary Crusher Dump Hopper (based on mining rates and distance traveled)

One way distance traveled out of the pit when hauling ore from the ROM High or Low Grade Ore Stockpile to the Primary Crusher Dump Hopper (Weighted average distance, HG ore hauled from different lifts in stockpile)

0 1,673 0 0 0 0 0 0 0 0 0 7,068 0 0 0 0 0 7,068 5,141 4,104 feet

One way distance traveled out of the pit when hauling ore from the ROM High or Low Grade Ore Stockpile to the Primary Crusher Dump Hopper (Weighted average distance, HG ore hauled from different lifts in stockpile)

Vehicle miles traveled per year out of the pit when hauling ore from the ROM High Grade Ore Stockpile to the Primary Crusher Dump Hopper (based on mining rates and distance traveled)

0 8,780 0 0 0 0 0 0 0 0 0 36,260 0 0 0 0 0 172,408 246,032 32,698 496,179 VMT/yearVehicle miles traveled per year out of the pit when hauling ore from the ROM High Grade Ore Stockpile to the Primary Crusher Dump Hopper (based on mining rates and distance traveled)

Maximum vehicle miles traveled per day out of the pit when hauling ore from the ROM High Grade Ore Stockpile to the Primary Crusher Dump Hopper (based on mining rates and distance traveled)

0 24 0 0 0 0 0 0 0 0 0 99 0 0 0 0 0 472 674 90 VMT/day

Maximum vehicle miles traveled per day out of the pit when hauling ore from the ROM High Grade Ore Stockpile to the Primary Crusher Dump Hopper (based on mining rates and distance traveled)

Maximum vehicle miles traveled per hour out of the pit when hauling ore from the ROM High Grade Ore Stockpile to the Primary Crusher Dump Hopper (based on mining rates and distance traveled)

0 1 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 20 28 4 VMT/hour

Maximum vehicle miles traveled per hour out of the pit when hauling ore from the ROM High Grade Ore Stockpile to the Primary Crusher Dump Hopper (based on mining rates and distance traveled)

One way distance traveled in the pit when hauling waste rock for tailings buttresses (Weighted average distance, rock hauled from different location in pit)

6,726 5,625 7,559 8,917 10,251 10,123 12,270 10,993 12,276 12,587 10,298 7,348 11,085 8,820 17,481 12,860 15,244 17,892 0 0 feetOne way distance traveled in the pit when hauling waste rock for tailings buttresses (Weighted average distance, rock hauled from different location in pit)

One way distance traveled out of the pit when hauling waste rock for tailings buttresses (Weighted average distance, rock hauled from different locations in pit)

9,894 9,246 8,896 8,276 13,933 0 11,662 0 10,857 10,824 10,979 11,530 12,587 14,595 0 0 0 0 0 0 feetOne way distance traveled out of the pit when hauling waste rock for tailings buttresses (Weighted average distance, rock hauled from different locations in pit)

Percent of waste rock that is for tailings buttresses 17% 54% 33% 45% 22% 0% 75% 0% 75% 52% 73% 99% 84% 38% 0% 0% 0% 0% 0% 0% % Percent of waste rock that is for tailings buttresses

One way distance traveled in the pit when hauling waste rock to storage areas (Weighted average distance, rock hauled from different locations in pit)

6,726 5,625 7,559 8,917 10,251 10,123 12,270 10,993 12,276 12,587 10,298 7,348 11,085 8,820 17,481 12,860 15,244 17,892 0 0 feetOne way distance traveled in the pit when hauling waste rock to storage areas (Weighted average distance, rock hauled from different locations in pit)

One way distance traveled out of the pit when hauling waste rock to storage areas (Weighted average distance, rock hauled to different locations from pit)

7,030 9,358 13,568 10,629 11,068 10,331 10,528 10,380 11,466 13,280 13,499 12,706 13,483 14,690 13,846 14,225 14,573 14,919 0 0 feetOne way distance traveled out of the pit when hauling waste rock to storage areas (Weighted average distance, rock hauled to different locations from pit)

Percent of waste rock that is sent to storage areas 83% 46% 67% 55% 78% 100% 25% 100% 25% 48% 27% 1% 16% 62% 100% 100% 100% 100% 100% 100% % Percent of waste rock that is sent to storage areas

Vehicle miles traveled per year in the pit when hauling all types of waste rock (based on mining rates, distances traveled, percentages of the different types of waste rock)

918,944 816,402 954,712 1,116,708 1,438,643 1,376,649 1,656,328 1,558,879 1,699,803 1,818,148 1,487,597 1,061,349 994,375 325,305 214,404 67,483 128,200 147,828 0 0 17,781,756 VMT/yearVehicle miles traveled per year in the pit when hauling all types of waste rock (based on mining rates, distances traveled, percentages of the different types of waste rock)

Haul Trucks - Hauling Waste Rock

Haul Trucks - Hauling Ore

PNB000828

Rosemont Project


Hudbay, RP16Aug






Truck Shifts Stockpile to Crusher RP16Aug 0 398 0 0 0 0 0 0 0 0 0 389 0 0 0 0 0 1,398 2,748 457Maximum vehicle miles traveled per day in the pit when hauling all types of waste rock (based on mining rates, distances traveled, percentages of the different types of waste rock)

2,518 2,237 2,616 3,059 3,941 3,772 4,538 4,271 4,657 4,981 4,076 2,908 2,724 891 587 185 351 405 0 0 VMT/dayMaximum vehicle miles traveled per day in the pit when hauling all types of waste rock (based on mining rates, distances traveled, percentages of the different types of waste rock)

Maximum vehicle miles traveled per hour in the pit when hauling all types of waste rock (based on mining rates, distances traveled, percentages of the different types of waste rock)

105 93 109 127 164 157 189 178 194 208 170 121 114 37 24 8 15 17 0 0 VMT/hourMaximum vehicle miles traveled per hour in the pit when hauling all types of waste rock (based on mining rates, distances traveled, percentages of the different types of waste rock)

Vehicle miles traveled per year out of the pit when hauling all types of waste rock (based on mining rates, distances traveled, percentages of the different types of waste rock)

1,025,498 1,349,383 1,521,575 1,198,455 1,642,256 1,404,898 1,536,181 1,471,966 1,524,246 1,732,515 1,685,370 1,667,347 1,141,987 540,504 169,814 74,647 122,555 123,267 0 0 19,932,462 VMT/yearVehicle miles traveled per year out of the pit when hauling all types of waste rock (based on mining rates, distances traveled, percentages of the different types of waste rock)

Maximum vehicle miles traveled per day out of the pit when hauling all types of waste rock (based on mining rates, distances traveled, percentages of the different types of waste rock)

2,810 3,697 4,169 3,283 4,499 3,849 4,209 4,033 4,176 4,747 4,617 4,568 3,129 1,481 465 205 336 338 0 0 VMT/dayMaximum vehicle miles traveled per day out of the pit when hauling all types of waste rock (based on mining rates, distances traveled, percentages of the different types of waste rock)

Maximum vehicle miles traveled per hour out of the pit when hauling all types of waste rock (based on mining rates, distances traveled, percentages of the different types of waste rock)

117 154 174 137 187 160 175 168 174 198 192 190 130 62 19 9 14 14 0 0 VMT/hourMaximum vehicle miles traveled per hour out of the pit when hauling all types of waste rock (based on mining rates, distances traveled, percentages of the different types of waste rock)

PNB000829

IN Mobile

Annual Daily Hourly Annual Daily Hourly

Horsepower 2,650 Caterpillar Spec Sheet

Empty Weight (tons) 175 Caterpillar Spec Sheet

Loaded Weight (tons) 440 May 2016 Mine Plan

Payload (tons) 265 May 2016 Mine Plan

Crawler Dozers, PL87 Class 0 Horsepower 366 Cat WebsiteInformation Not

Needed0 0 0.0

Crawler Dozers, D10T Class 6 Horsepower 580 Cat WebsiteInformation Not

Needed38,400 105 5.3

Crawler Dozer, D8 Class 0 Horsepower 310 Cat WebsiteInformation Not

Needed0 0 0.0

Rubber Tired Dozers, 834 Class 3 Horsepower 531 Cat WebsiteInformation Not

Needed19,200 53 2.6

Motor Graders, 16M Class 4 Horsepower 297 Cat Website -- 117,760 323 16.13 25,600 70 3.5

Horsepower 1,348 Cat Website

Empty Weight (tons) 125 Cat Website

Loaded Weight (tons) 248 Add 30,000 gal water

List of Mobile Equipment

Main Mine Equipment

Information Not Needed


Mobile Equipment Name Fleet Size Equipment Detail

Water Trucks, 30,000 gallons 6 312,400 1,027 42.79

34


Haulage Trucks, 260 tons(Tier 4)

34 241,230

140

Value SourceVMT/year

(per vehicle)

VMT - Y9

7.00

Hours Used - Y9

--

816

42,600


Rosemont Copper ProjectPermit Renewal/Modification May 2017

PNB000830

Rosemont Copper Project | Amended Model Report Trinity Consultants G-1

APPENDIX G: OZONE AND SECONDARY PM2.5 GUIDANCE

PNB000831

Introduction

ADEQ Guidance to ACFY on Ozone Impact Analysis January 7, 2016

Based on preliminary information provided by Arizona Clean Fuels Yuma (ACFY), it is likely the proposed

refinery project will trigger PSD review for ozone. The Project area is currently designated as

unclassifiable/attainment with respect to the 2008 ozone NAAQS, and the Project NOx and voe emission

increases will be approximately 250-300 tpy each. Therefore, there will be a PSD requirement to

demonstrate that the Project emissions do not "cause or contribute" to a vio lation of the ozone NAAQS.

EPA recently revised the ozone NAAQS from 75 parts per billion ("ppb") to 70 ppb on an 8-hr averaging

interval; this more stringent standard will take effect December 28, 2015. 80 Fed. Reg. 65292. In the final

ozone NAAQS rule, EPA also amended the PSD rules to allow sources to be grandfathered with respect to

the new NAAQS (i.e., to require only that the source owner/operator demonstrate compliance with the

2008 ozone NAAQS) if either the permit application was deemed complete before the new ozone NAAQS

rule was signed in October 2015, or if a draft permit was issued before the new ozone NAAQS became

effective in December 2015. 80 Fed. Reg. 65292 at p. 65433. Neither of these grandfathering provisions

will apply to the ACFY Project as a permit application has not yet been received, therefore this Project will

have to demonstrate that the Project emissions do not cause or contribute to a violation of the 2015

ozone NAAQS.

ACFY has collected PSD pre-construction ozone data at the Project site for a one year period that indicates

the 2015 NAAQS concentration is being exceeded in the area. In addition, three recent years of ozone

data from ADEQ operated ozone monitors in the area also indicate exceedances of the 2015 NAAQS.

Therefore, the Project area may be designated non-attainment with respect to the 2015 ozone NAAQS in

the future. However, given the time frame for the designation process, it is very likely that the PSD

permitting requirements for ozone will still be in effect during the review and approval of the ACFY Project

permit application. Therefore, ACFY will have to demonstrate that the Project's emissions do not cause

or contribute to a violation of the 2015 ozone NAAQS.

Cause or Contribute Criteria and Significant Impact Levels

Historically, under the de minimis doctrine, EPA and the courts have allowed the use of several types of

"screening tools" in the permitting process. These tools include the Significant Emissions Rates (SERs) and

the Significant Impact Levels (SILs). The SERs, defined in tons per year (tpy) for each regulated pollutant,

are incorporated in the codified PSD and NNSR rules and are used to determine whether the emissions

increase from any proposed source or modification can be excluded from review entirely. Similarly, the

SILs, which are incorporated in the codified rules for certain pollutants and are expressed in terms of

ambient concentration, are used as a quantitative representation of the ambiguous phrase, "cause or

contribute to." A source that will cause an increase in concentration in an area that is violating a NAAQS

is deemed not to "cause or contribute" to the violation if its contribution is less than the SIL. (See: A.A.C.

R18-2-406(A)(5)(b); 40 CFR § 51.165(b)(2); Section Ill.A of appendix S to 40 CFR part 51.)

Under the PSD program air quality impact analysis process, SILs are used first to determine whether a

Project's ambient impact of a particular pollutant is significant enough to warrant a complete source

PNB000832

impact analysis. If a complete analysis is required, and if a violation of a NAAQS is predicted in that

analysis, the SILs are then used to determine whether the source's impact is considered to "cause or

contribute" to that violation. See, for example, 80 Fed. Reg. 65292 at p. 65441.

EPA's October 1, 2015, implementation memo for the new 2015 ozone NAAQS notes the importance of

the SI Ls with respect to implementing the ozone NAAQS under the PSD program:

There are a number of existing program tools that can be used to help facilitate the permitting

process, and the EPA continues to work with stakeholders on others that will improve the

permitting process while assuring attainment and protection of the ozone standards. These

include the use of emission offset programs and significant impact levels (S/Ls) for ozone for PSD

permitting. The existing "PSD offsets" tool continues to be available for permit applicants and

reviewing authorities to address ozone impacts from a proposed source or modification, including

in an area that is not designated nonattainment but where ambient monitoring data shows ozone

concentrations that exceed tjJe revised NAAQS. We believe that S/Ls and related "screening tools"

are useful in determining the extent to which an ambient impact analysis must be completed to

make the required demonstration for the applicable pollutant. We intend to provide additional

guidance on these screening tools in the near future. {Internal footnote omitted.]

Development of an Interim Ozone SIL

The codified Arizona major NSR rules do not specify a SIL or any other comparable de minimis threshold

for the ozone air quality impact analysis. Similarly, no such provisions have been established in the federal

major NSR rules nor have there been any EPA policy statements of general applicability. EPA is in the

process of developing an ozone SIL. 80 Fed. Reg. 65292 at p. 65441. EPA also has announced its intent to

introduce a new de minimis tool, specifically for ozone and PM2.s precursors, called Model Emissions Rates

for Precursors (MERPs). 80 Fed. Reg. 45340 at p. 45347. These federal provisions, whether established

through rulemaking or policy, are not expected to be finalized at the time of permitting the ACFY project.

Where no SIL has been established by rule or by generally applicable policy, PSD permitting authorities

may need to develop interim SILs. These interim SIL values must be reasonable and supported by an

administrative record. See, for example, final order of the EPA Environmental Appeals Board (EAB) in PSD

Appeal Nos. 98-27 and 98-28, Sept. 9, 1999, upholding the decision of the Indiana Department of

Environmental Management (IDEM) to apply an ozone SIL of 3 ppb ("The mere fact that EPA has not set

a significant impact level for ozone does not, without more, demonstrate clear error or an abuse of

discretion on the part of IDEM in using significant impact levels for ozone in the context of this case.").

See, also, final order of the EPA Administrator denying Petition Nos. Vl-2010-05, Vl-2011-06, and Vl-2012-

07, Jan. 30, 2014, with respect to claims that the Louisiana Department of Environmental Quality acted

inappropriately in using SILs to excuse predicted violations of the Class I S02 increment ("EPA has long

interpreted and continues to interpret this ambiguity in the statute to permit the use of SILs to determine

if the impact from a source contributes to an existing violation.")

PNB000833

EPA established an interim 1-hr N02 SIL in their June 29, 2010 memorandum Guidance Concerning the

Implementation of the 1-hour N02 NAAQS for the Prevention of Significant Deterioration Program, and

later an interim 1-hr S02 SIL in their August 23, 2010, memorandum General Guidance for Implementing

the 1-hour S02 National Ambient Air Quality Standard in Prevention of Significant Deterioration Permits,

Including an Interim 1-hour S02 Significant Impact Level. In these memoranda EPA described the basis

and historical precedence for establishing these short-term SI Ls at values equal to 4% of the corresponding

NAAQS. Using this same logic, it is reasonable and consistent with previous EPA actions for ADEQ to

establish an interim ozone SIL at 4% of the 2015 NAAQS, equal to 2.8 ppb for an 8-hour average. This is

the same value (4% of 2008 NAAQS) that IDEM established as an interim ozone SIL which EAB upheld.

Recent EPA modeling guidance for PM2.s has suggested that the PM2.s SILs should only be used as a

screening technique for determining when a Project requires a cumulative impact analysis when the

difference between the NAAQS and the existing air quality is greater than the SIL concentration (herein

referred to as the delta test). See EPA's Guidance for PM2.s Permit Modeling, EPA-454/B-14-001, May

2014. Whiie this would of course result in extra conservatism, it must be noted that this is inconsistent

with how EPA and ADEQ have applied the SILs in the past. No explanation has been offered by EPA for

this seemingly arbitrary shift in policy. Moreover, and of particular note with respect to an ozone PSD

analysis, EPA has not suggested application of the "delta" test for any pollutant other than PM2.s.

Additionally, the PM2.s modeling guidance does not suggest that the SILs cannot be directly used to

determine if a source "causes or contributes" to a violation of the NAAQS during a cumulative analysis. In

summary, the SI Ls have been historically been used to determine when a source "causes or contributes"

to a violation of the NAAQS, both in attainment areas and in non-attainment areas, without the "delta"

test as suggested by the new EPA PM2.s guidance.

EPA Guidance on Single Source Ozone Impact Analysis

On January 4, 2012, the EPA granted a petition submitted on behalf of the Sierra Club that requested the

EPA initiate rulemaking to establish air quality models for ozone and PM2.s for use by all major sources

applying for a PSD permit. In granting that petition, EPA explained that the "complex chemistry of ozone

and secondary formation of PM2.s are well documented and have historically presented significant

challenges to the designation of particular models for assessing the impacts of individual stationary

sources on the formation of these air pollutants" and further explained that "[b]ecause of these

considerations, the EPA's judgment in the past has been that it was not technically sound to designate

with particularity specific models that must be used to assess the impacts of a single source on ozone

concentrations".

EPA's current approach to assess ozone impacts of an individual source is performed on a case-by-case

basis in consultation with the appropriate EPA Regional Office and/or permit reviewing authority. Section

5.2.1.c of the current 40 CFR Part 51 Appendix W (the Guideline on Air Quality Models) states that the

"[c]hoice of methods used to assess the [ozone] impact of an individual source depends on the nature of

the source and its emissions." There is currently not a preferred or recommended analytical technique or

modeling system to perform ozone compliance demonstration assessments for individual sources. Some

assessments have been completely qualitative in nature; while others have utilized photochemical grid

PNB000834

models as part of the assessment. Through the consultation process, a modeling protocol should be

developed by the permit applicant and approved by the appropriate permitting authority to ensure that

the analysis conducted will conform to the recommendations, requirements, and principles of Section

10.2.1 of the current Guideline.

In the July 29, 2015 proposed revision to the Guideline, the EPA has stated that advances in photochemical

modeling indicate it is now reasonable to propose more specific guidance that identifies particular models

or analytical techniques that may be used under specific circumstances. The degree of complexity varies

depending on the nature of the source, its emissions, and the background environment. EPA has proposed

a two-step demonstration approach for addressing single-source impacts on ozone and secondary PM2.s.

The first step involves use of t echnically credible relationships between precursor emissions and a source's

impacts that may be published in the peer-reviewed literature; developed from modeling that was

previously conducted for an area by a source, a governmental agency, or some other entity and that is

deemed sufficient; or generated by a peer-reviewed reduced form model. The second step involves

application of photochemical grid models. The appropriate method for a given Project should be selected

in consultation with the reviewing authority and be consistent with EPA guidance. To implement these

proposed changes to the Guideline related to addressing ozone and secondary PM2.s impacts, the EPA

intends to pursue a separate rulemaking to establish new values for PM2.s Significant Impact Levels (SI Ls)

and to introduce a new demonstration tool for ozone and PM2.s precursors referred to as Model Emissions

Rates for Precursors (MERP). EPA intends that the MERPs will represent a level of precursor emissions

that is not expected to contribute significantly to concentrations of ozone or secondarily formed PM2.s.

Based on the present understanding of the atmospheric science of ozone and secondary PM2.s formation,

the MERP values will likely be higher than the SERs.

EPA's current PM2.s modeling guidance provides for a three tier approach to address secondary PM2.s with

(1) a qualitative assessment; (2) a hybrid qualitative/quantitative assessment utilizing existing technical

work; and (3) a full quantitative modeling exercise. The EPA expects that MERPs will replace the first tier

as the qualitative assessment.

EPA is currently performing and reviewing single-source photochemical modeling studies and other PM2.s

and ozone research to develop MERPs for PM2.s and ozone precursors (ozone precursors include the PSD

regulated pollutants NOx and VOC). Some of these studies are summarized below, along with findings

related to the ambient ozone impacts for sources with NOx and voe emissions on the order of 300 tpy

(similar to the current estimates for the ACFY Project).

Comparison of Single Source Air Quality Assessment Techniques for Ozone, PM2.s, other Criteria

Pollutants and AQRVs. EPA Contract No: EP-D-07-102, Work Assignment No 4-06 & 5-08.

Environ International Corporation, September 2012.

Two CAMx analyses of Electric Generating Units (EGUs) and Oil and Gas Developments were

performed. For the first modeling analysis, EGUs with greater than approximately 5000 tpy

combined of NOx and S02 resulted in 8-hr ozone impacts of 6 to 13 ppb, while EGUs with

approximately 150 tpy of NOx emissions resulted in 8-hr ozone impacts of approximately 1 ppb.

PNB000835

In the second eAMx analysis, EGUs with greater than 1750 tpy of NOx resulted in 8-hr ozone

impacts ranging from 5 ppb to 17 ppb, while EGU sources with NOx emissions of 660 tpy and

smaller resulted in 8-hr ozone impacts less than 1.1 ppb. For Oil and Gas Scenario OG3 with 290

tpy NOx and 90 tpy voe emissions, the 8-hr ozone impact was 1.5 ppb.

lnteragency Workgroup on Air Quality Modeling Phase 3 Summary Report: Near-Field Single

Source Secondary Impacts. EPA-454/P-15-002, July 2015

This report includes examples of single source impacts in two urban areas, Atlanta and Detroit. A

photochemical grid model was applied with baseline emissions and subsequent additiona l

simulations where a new hypothetical source was included with a fixed precursor emission rate.

The simulations with the additional hypothetical source were compared with the baseline

simulation where the hypothetical source is not included (e.g. brute-force difference) and single

source impacts are estimated for 03 and secondary PM2.s. Impacts tend to be highest within 15

km the source and decrease as distance from the source increases. The maximum single-source

8-hr ozone impact is less than 0.5 ppb for all cases with NOx and voe emissions over the range of

100 to 300 tpy (each).

This report also includes a review of existing research and observational studies published

between 2005 and 2015 relating to single source precursor emissions and downwind ozone

impacts. The studies indicate that 8-hr ozone impacts are on the order of 1 ppb for NOx emission

sources of up to 500 tpy. The peak 8-hr ozone impact reported in literature was approximately

33 ppb for a very large NOx source ("'14,000 tpy) in the Louisiana/eastern Texas area.

A Screening Method for Ozone Impacts of New Sources based on High Order Sensitivity Analysis

of CAMx Simulations for Sydney, ENVIRON Corporation, EPA's 10th Conference on Air Quality

Modeling, March 13-15, 2012

This study developed a method for estimating single-source ozone impacts in the Sydney Australia

area. Severa l hypothetical new sources were modeled using eAMx and both a sensitivity test

method (HDDM) and a brute force approach to develop the relationship between ozone impacts

as a function of NOx and voe emissions. A 5000 tpy source was modeled assuming only NOx, only

voe, and a mixture of the two pollutants. The reported maximum ozone 1-hr impact was less

than 1.6 ppb at any grid cell.

In summary, these studies indicate that sources with NOx and voe emissions on the order of 300 tpy

(similar to the AeFY Project) would likely result in ozone impacts below an interim ozone SIL established

at 2.8 ppb.

Requirements for AeFY Ozone Impact Analysis

Based on the current EPA Guidelines, the AeFY ozone impact analysis methodology should be determined

on a case-by-case basis in consultation with the appropriate EPA Regional Office and/or permit reviewing

authority. Given the nature of the source and level of emissions, it is likely that the appropriate level of

PNB000836

analysis would be qualitative in nature. ACFY could summarize the ozone impacts reported for similarly

sized sources in the literature, and demonstrate that the impacts are not likely to cause or contribute to

a violation of the 2015 NAAQS (because the existing air quality is already above the 2015 NAAQS

concentration, this means that ACFY ozone impacts would need to be below an interim SIL concentration).

Using EPA's current proposed guidance, the ACFY ozone impact analysis methodology could utilize a tier

2 "hybrid qualitative/quantitative assessment" approach. The assessment should address the topics

discussed in Section 111.2.1 of EPA's PM2.s Modeling Guidance. This hybrid assessment involves the use of

technically credible relationships between precursor emissions and a source's impacts that have been

published in peer-reviewed literature or by governmental agencies. For example, based on the brief

analysis of ozone modeling studies discussed previously, it could be concluded that sources with NOx and

voe emissions similar to ACFY would likely result in ozone impacts below an interim 8-hr ozone SIL of 2.8

ppb.

As EPA has noted in their PM2.s modeling guidance, it is anticipated that only a few situations will require

explicit Tier 3 photochemical grid modeling. Given the relatively modest Project NOx and VOC emissions

for the ACFY Project, it is not likely that this Project is one of the few situations for which Tier 3

photochemical grid modeling is warranted.

PNB000837

Rosemont Copper Project | Amended Model Report Trinity Consultants H-1

APPENDIX H: MODEL SOURCE PARAMETERS

PNB000838

Open Pit Sources

Source ID Source Description

Easting (X)(m)

Northing (Y)(m)

Base Elevation

(m)

Release Height

(m) X length (ft)Y length

(ft)

Pit Volume

(ft3)Angle

(degree)

PM10

(lb/hr-ft2)

PM2.5

(lb/hr-ft2)

CO

(lb/hr-ft2)

NOx

(lb/hr-ft2)

SO2

(lb/hr-ft2)

PIT Open Pit 522639.8 3521372.0 1112.52 0 2460.63 3444.88 3.81E+09 0 4.67E-05 7.44E-06 1.52E-05 1.44E-05 2.66E-08PIT2 Waste Rock Area 523530.6 3519025.3 1661.16 0 5516.08 2443.57 6.74E+08 -19.3 2.49E-06 4.79E-07 1.73E-06 1.36E-06 3.81E-09


Easting (X)(m)

Northing (Y)(m)

Base Elevation

(m)

Release Height

(m) X length (ft)Y length

(ft)

Pit Volume

(ft3)Angle

(degree)

PM10

(lb/hr-ft2)

PM2.5

(lb/hr-ft2)

CO

(lb/hr-ft2)

NOx

(lb/hr-ft2)

SO2

(lb/hr-ft2)

PIT Open Pit 522639.8 3521372.0 1112.52 0 2460.63 3444.88 3.81E+09 0 --- 2.62E-06 --- 1.14E-05 1.95E-08PIT2 Waste Rock Area 523530.6 3519025.3 1661.16 0 5516.08 2443.57 6.74E+08 -19.3 --- 4.27E-07 --- 9.76E-07 1.85E-09

Year 9 - Modeling Hourly Emissions, Open Pit Sources

Year 9 - Modeling Annual Emissions, Open Pit Sources

Rosemont Copper ProjectPermit Renewal/Modification July 2017

PNB000839

Point Sources


Easting (X)(m)

Northing (Y)(m)

Base Elevation

(m)

Stack Height

(ft)

Temperature

(oF)Exit Velocity

(fps)

Stack Diameter

(ft)

PM10

(lb/hr)

PM2.5

(lb/hr)CO

(lb/hr)

NOx

(lb/hr)

SO2

(lb/hr)

AE001 Primary Crusher Dust Collector 524055.1 3521975.9 1520.34 40 -459.67 54.08 2.17 0.19 0.04 --- --- ---AE002 Stockpile Dust Collector 524054.7 3522378.4 1541.68 50 -459.67 50.03 4.83 0.94 0.14 --- --- ---AE003 Reclaim Tunnel Line 1 Dust Collector 524068.5 3522379.2 1538.63 40 -459.67 51.99 3.67 0.40 0.07 --- --- ---AE004 Reclaim Tunnel Line 2 Dust Collector 524041.5 3522378.7 1538.63 40 -459.67 51.99 3.67 0.40 0.07 --- --- ---AE005 Copper Conc Dust Collector 524063.9 3522653.5 1543.20 45 -459.67 50.03 4.83 0.94 0.14 --- --- ---AE009 Quicklime Dust Collector 523983.6 3522559.9 1543.51 46 -459.67 221.35 0.33 0.02 0.00 --- --- ---AE010 Moly Float Scrubber 523987.2 3522628.2 1543.51 45 -459.67 31.83 1.00 0.22 0.22 --- --- ---AE011 Moly Bag Loader Dust Collector 523982.1 3522648.4 1535.77 17.5 -459.67 7.80 1.17 0.01 0.00 --- --- ---AE012 Moly Conc Storage Bin Dust Collector 523990.0 3522648.1 1537.72 23 -459.67 7.80 1.17 0.01 0.00 --- --- ---AE013 Moly Dryer Scrubber 523994.3 3522651.4 1546.25 53 -459.67 23.87 0.67 0.04 0.02 --- --- ---AE014 Flocculant Hopper Dust Filter 524275.2 3522568.3 1524.61 30 -459.67 23.87 0.67 0.03 0.01 --- --- ---AE015 Lime Scrubber 523990.2 3522556.9 1533.60 14 -459.67 95.49 0.33 0.07 0.07 --- --- ---AE016 Collector Storage and Dist Tank 524017.5 3522569.6 1538.94 30 -459.67 21.22 1.00 0.04 0.04 --- --- ---AE017 Collector Area Vent Fan 524001.4 3522569.6 1538.94 30 -459.67 10.61 1.00 0.02 0.02 --- --- ---AE019 Laboratory Dust Collector 1 524320.0 3522649.9 1539.24 20 110 76.13 1.67 0.23 0.09 --- --- ---AE020 Laboratory Dust Collector 2 524325.1 3522649.9 1539.24 20 110 76.13 1.67 0.23 0.09 --- --- ---AE021 Laboratory Dust Collector 3 524330.6 3522650.1 1539.24 20 110 76.13 1.67 0.23 0.09 --- --- ---FB01 Emergency Generator #1 523973.9 3522503.3 1532.53 14 890 218.07 1.33 0.59 0.59 10.38 18.98 0.02FB02 Emergency Generator #2 523973.6 3522489.8 1532.53 14 890 218.07 1.33 0.59 0.59 10.38 18.98 0.02FB03 Emergency Generator #3 523973.6 3522481.9 1532.53 14 890 218.07 1.33 0.59 0.59 10.38 18.98 0.02FB04 Primary Crusher Fire Water Pump 523984.1 3522497.3 1532.53 9 980 338.00 0.30 0.13 0.13 2.30 2.63 0.004


Easting (X)(m)

Northing (Y)(m)

Base Elevation

(m)

Stack Height

(ft)

Temperature

(oF)Exit Velocity

(fps)

Stack Diameter

(ft)

PM10

(lb/hr)

PM2.5

(lb/hr)CO

(lb/hr)

NOx

(lb/hr)

SO2

(lb/hr)

AE001 Primary Crusher Dust Collector 524055.1 3521975.9 1520.34 40 -459.67 54.08 2.17 --- 0.04 --- --- ---AE002 Stockpile Dust Collector 524054.7 3522378.4 1541.68 50 -459.67 50.03 4.83 --- 0.14 --- --- ---AE003 Reclaim Tunnel Line 1 Dust Collector 524068.5 3522379.2 1538.63 40 -459.67 51.99 3.67 --- 0.07 --- --- ---AE004 Reclaim Tunnel Line 2 Dust Collector 524041.5 3522378.7 1538.63 40 -459.67 51.99 3.67 --- 0.07 --- --- ---AE005 Copper Conc Dust Collector 524063.9 3522653.5 1543.20 45 -459.67 50.03 4.83 --- 0.14 --- --- ---AE009 Quicklime Dust Collector 523983.6 3522559.9 1543.51 46 -459.67 221.35 0.33 --- 0.00 --- --- ---AE010 Moly Float Scrubber 523987.2 3522628.2 1543.51 45 -459.67 31.83 1.00 --- 0.22 --- --- ---AE011 Moly Bag Loader Dust Collector 523982.1 3522648.4 1535.77 17.5 -459.67 7.80 1.17 --- 0.00 --- --- ---AE012 Moly Conc Storage Bin Dust Collector 523990.0 3522648.1 1537.72 23 -459.67 7.80 1.17 --- 0.00 --- --- ---AE013 Moly Dryer Scrubber 523994.3 3522651.4 1546.25 53 -459.67 23.87 0.67 --- 0.02 --- --- ---AE014 Flocculant Hopper Dust Filter 524275.2 3522568.3 1524.61 30 -459.67 23.87 0.67 --- 0.00 --- --- ---AE015 Lime Scrubber 523990.2 3522556.9 1533.60 14 -459.67 95.49 0.33 --- 0.07 --- --- ---AE016 Collector Storage and Dist Tank 524017.5 3522569.6 1538.94 30 -459.67 21.22 1.00 --- 0.04 --- --- ---AE017 Collector Area Vent Fan 524001.4 3522569.6 1538.94 30 -459.67 10.61 1.00 --- 0.02 --- --- ---AE019 Laboratory Dust Collector 1 524320.0 3522649.9 1539.24 20 110 76.13 1.67 --- 0.09 --- --- ---AE020 Laboratory Dust Collector 2 524325.1 3522649.9 1539.24 20 110 76.13 1.67 --- 0.09 --- --- ---AE021 Laboratory Dust Collector 3 524330.6 3522650.1 1539.24 20 110 76.13 1.67 --- 0.09 --- --- ---FB01 Emergency Generator #1 523973.9 3522503.3 1532.53 14 890 218.07 1.33 --- 0.03 --- 1.08 0.001FB02 Emergency Generator #2 523973.6 3522489.8 1532.53 14 890 218.07 1.33 --- 0.03 --- 1.08 0.001FB03 Emergency Generator #3 523973.6 3522481.9 1532.53 14 890 218.07 1.33 --- 0.03 --- 1.08 0.001FB04 Primary Crusher Fire Water Pump 523984.1 3522497.3 1532.53 9 980 338.00 0.30 --- 0.01 --- 0.15 0.0002

Year 9 - Modeling Hourly Emissions, Point Sources

Year 9 - Modeling Annual Emissions, Point Sources


PNB000840

Volume Sources


Easting (X)(m)

Northing (Y)(m)

Base Elevation

(m)

Release Height

(m)

Initial Lateral

Dimension (m)

Initial Vertical

Dimension (m)

PM10

(lb/hr)

PM2.5

(lb/hr)CO

(lb/hr)

NOx

(lb/hr)

SO2

(lb/hr)

BLST1 Blasting Emissions 522950.8 3522110.1 1371.60 10 14.19 9.30 182.36 10.52 2791.67 708.33 83.33BLST2 Blasting Emissions 523118.4 3522114.9 1371.60 10 14.19 9.30 182.36 10.52 2791.67 708.33 83.33BLST3 Blasting Emissions 522943.3 3521919.8 1371.60 10 14.19 9.30 182.36 10.52 2791.67 708.33 83.33BLST5 Blasting Emissions 522943.3 3521706.8 1371.60 10 14.19 9.30 182.36 10.52 2791.67 708.33 83.33BLST4 Blasting Emissions 523116.3 3521920.4 1371.60 10 14.19 9.30 182.36 10.52 2791.67 708.33 83.33BLST6 Blasting Emissions 523116.3 3521712.7 1371.60 10 14.19 9.30 182.36 10.52 2791.67 708.33 83.33PC01 ROM Stockpile Wind Erosion 523934.4 3521928.6 1548.27 6 74.00 5.60 1.74 0.26 --- --- ---

PC02 Unloading to Primary Crusher Dump Hopper 524048.9 3521939.3 1541.62 0 2.79 0.47 0.68 0.10 --- --- ---TDS19B Tailings Wind Erosion 525277.6 3521892.0 1572.77 6 233.00 5.58 0.03 0.00 --- --- ---TDS19A Tailings Wind Erosion 525469.9 3520860.1 1551.43 6 233.00 5.58 13.40 2.01 --- --- ---TDS19C Tailings Wind Erosion 524564.6 3521080.7 1551.43 6 140.00 5.58 1.13 0.17 --- --- ---

MS07Transfer of Sodium Metaphosphate to the

Sodium Metaphosphate Storage Bin 524213.2 3522567.7 1524.00 3 0.47 0.70 0.0030 0.0005 --- --- ---

MS09 Flocculant Feed Bin to Flocculant Screw Feeder 524265.9 3522569.9 1524.00 3 0.47 0.70 0.0009 0.0001 --- --- ---

MS10Flocculant Screw Feeder to Flocculant Heated

Receiving Hopper 524261.8 3522569.2 1524.00 3 0.47 0.70 0.0009 0.0001 --- --- ---

MS11Flocculant Heated Receiving Hopper to

Flocculant Venturi 524258.1 3522569.6 1524.00 3 0.47 0.70 0.001 0.0001 --- --- ---

MS12 Flocculant Venturi to Flocculant Mixing Tank 524254.4 3522568.8 1524.00 3 0.47 0.70 0.001 0.0001 --- --- ---CHR_1 Combination Ore/Waste Rock 523341.7 3522423.3 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_2 Combination Ore/Waste Rock 523357.4 3522403.8 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_3 Combination Ore/Waste Rock 523373.1 3522384.3 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_4 Combination Ore/Waste Rock 523388.8 3522364.9 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_5 Combination Ore/Waste Rock 523404.5 3522345.4 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_6 Combination Ore/Waste Rock 523420.2 3522325.9 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_7 Combination Ore/Waste Rock 523435.9 3522306.5 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_8 Combination Ore/Waste Rock 523451.6 3522287.0 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_9 Combination Ore/Waste Rock 523467.2 3522267.5 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_10 Combination Ore/Waste Rock 523482.9 3522248.1 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_11 Combination Ore/Waste Rock 523498.6 3522228.6 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_12 Combination Ore/Waste Rock 523514.3 3522209.1 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_13 Combination Ore/Waste Rock 523530.0 3522189.7 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_14 Combination Ore/Waste Rock 523545.7 3522170.2 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_15 Combination Ore/Waste Rock 523561.4 3522150.7 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_16 Combination Ore/Waste Rock 523577.0 3522131.3 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_17 Combination Ore/Waste Rock 523592.7 3522111.8 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_18 Combination Ore/Waste Rock 523606.0 3522090.9 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_19 Combination Ore/Waste Rock 523615.4 3522067.8 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_20 Combination Ore/Waste Rock 523624.8 3522044.6 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_21 Combination Ore/Waste Rock 523634.1 3522021.4 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_22 Combination Ore/Waste Rock 523643.5 3521998.2 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_23 Combination Ore/Waste Rock 523652.9 3521975.0 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_24 Combination Ore/Waste Rock 523662.2 3521951.9 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_25 Combination Ore/Waste Rock 523671.6 3521928.7 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_26 Combination Ore/Waste Rock 523681.0 3521905.5 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_27 Combination Ore/Waste Rock 523690.3 3521882.3 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_28 Combination Ore/Waste Rock 523699.7 3521859.1 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_29 Combination Ore/Waste Rock 523709.0 3521836.0 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_30 Combination Ore/Waste Rock 523718.4 3521812.8 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_31 Combination Ore/Waste Rock 523731.3 3521793.3 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_32 Combination Ore/Waste Rock 523754.8 3521784.5 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_33 Combination Ore/Waste Rock 523778.2 3521775.7 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_34 Combination Ore/Waste Rock 523801.6 3521766.9 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_35 Combination Ore/Waste Rock 523825.0 3521758.1 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_36 Combination Ore/Waste Rock 523848.4 3521749.3 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_37 Combination Ore/Waste Rock 523872.4 3521751.3 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_38 Combination Ore/Waste Rock 523896.6 3521757.3 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_39 Combination Ore/Waste Rock 523920.9 3521763.4 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_40 Combination Ore/Waste Rock 523945.2 3521769.5 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_41 Combination Ore/Waste Rock 523969.4 3521775.5 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_42 Combination Ore/Waste Rock 523993.7 3521781.6 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_43 Combination Ore/Waste Rock 524017.9 3521787.7 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_44 Combination Ore/Waste Rock 524042.2 3521793.7 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_45 Combination Ore/Waste Rock 524063.9 3521802.8 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_46 Combination Ore/Waste Rock 524074.4 3521825.5 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_47 Combination Ore/Waste Rock 524084.9 3521848.2 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_48 Combination Ore/Waste Rock 524095.3 3521870.9 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_49 Combination Ore/Waste Rock 524089.7 3521878.5 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_50 Combination Ore/Waste Rock 524066.4 3521869.3 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_51 Combination Ore/Waste Rock 524043.1 3521860.2 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_52 Combination Ore/Waste Rock 524019.8 3521851.1 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_53 Combination Ore/Waste Rock 523996.6 3521842.0 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_54 Combination Ore/Waste Rock 523973.3 3521832.9 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_55 Combination Ore/Waste Rock 523949.9 3521824.2 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_56 Combination Ore/Waste Rock 523925.4 3521818.9 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_57 Combination Ore/Waste Rock 523901.0 3521813.7 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_58 Combination Ore/Waste Rock 523876.5 3521808.5 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_59 Combination Ore/Waste Rock 523852.1 3521803.3 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001

Year 9 - Modeling Hourly Emissions, Volume Sources


PNB000841

Volume Sources


Easting (X)(m)

Northing (Y)(m)

Base Elevation

(m)

Release Height

(m)

Initial Lateral

Dimension (m)

Initial Vertical

Dimension (m)

PM10

(lb/hr)

PM2.5

(lb/hr)CO

(lb/hr)

NOx

(lb/hr)

SO2

(lb/hr)


CHR_60 Combination Ore/Waste Rock 523827.6 3521798.1 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_61 Combination Ore/Waste Rock 523803.2 3521792.9 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_62 Combination Ore/Waste Rock 523790.5 3521811.7 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_63 Combination Ore/Waste Rock 523779.6 3521834.2 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_64 Combination Ore/Waste Rock 523768.7 3521856.7 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_65 Combination Ore/Waste Rock 523757.8 3521879.2 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_66 Combination Ore/Waste Rock 523746.9 3521901.7 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_67 Combination Ore/Waste Rock 523736.0 3521924.2 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_68 Combination Ore/Waste Rock 523725.1 3521946.7 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_69 Combination Ore/Waste Rock 523714.2 3521969.2 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_70 Combination Ore/Waste Rock 523703.3 3521991.7 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_71 Combination Ore/Waste Rock 523692.4 3522014.2 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_72 Combination Ore/Waste Rock 523681.5 3522036.7 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_73 Combination Ore/Waste Rock 523670.6 3522059.2 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_74 Combination Ore/Waste Rock 523659.7 3522081.7 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_75 Combination Ore/Waste Rock 523648.0 3522103.7 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_76 Combination Ore/Waste Rock 523633.0 3522123.7 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_77 Combination Ore/Waste Rock 523618.0 3522143.7 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_78 Combination Ore/Waste Rock 523603.0 3522163.7 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_79 Combination Ore/Waste Rock 523588.0 3522183.7 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_80 Combination Ore/Waste Rock 523573.0 3522203.7 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_81 Combination Ore/Waste Rock 523558.0 3522223.7 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_82 Combination Ore/Waste Rock 523543.0 3522243.7 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_83 Combination Ore/Waste Rock 523528.0 3522263.7 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_84 Combination Ore/Waste Rock 523513.0 3522283.7 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_85 Combination Ore/Waste Rock 523498.0 3522303.7 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_86 Combination Ore/Waste Rock 523483.0 3522323.7 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_87 Combination Ore/Waste Rock 523468.0 3522343.7 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_88 Combination Ore/Waste Rock 523453.0 3522363.7 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_89 Combination Ore/Waste Rock 523438.0 3522383.7 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_90 Combination Ore/Waste Rock 523423.0 3522403.7 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_91 Combination Ore/Waste Rock 523408.0 3522423.7 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_92 Combination Ore/Waste Rock 523393.0 3522443.7 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001CHR_93 Combination Ore/Waste Rock 523377.8 3522463.5 1402.08 6.5 11.63 6.05 0.09 0.01 0.04 0.04 0.0001WHR1_1 Waste Rock Haul_1 525100.3 3519801.1 1630.68 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_2 Waste Rock Haul_1 525124.4 3519807.8 1630.68 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_3 Waste Rock Haul_1 525148.7 3519813.6 1630.68 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_4 Waste Rock Haul_1 525173.0 3519819.3 1630.68 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_5 Waste Rock Haul_1 525197.3 3519825.1 1630.68 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_6 Waste Rock Haul_1 525221.7 3519830.9 1630.68 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_7 Waste Rock Haul_1 525246.0 3519836.6 1630.68 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_8 Waste Rock Haul_1 525270.3 3519842.4 1630.68 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_9 Waste Rock Haul_1 525294.6 3519848.2 1630.68 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_10 Waste Rock Haul_1 525319.0 3519853.9 1630.68 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_11 Waste Rock Haul_1 525343.3 3519859.7 1630.68 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_12 Waste Rock Haul_1 525367.6 3519865.5 1630.68 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_13 Waste Rock Haul_1 525385.8 3519872.9 1630.68 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_14 Waste Rock Haul_1 525367.8 3519890.3 1630.68 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_15 Waste Rock Haul_1 525349.9 3519907.7 1630.68 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_16 Waste Rock Haul_1 525331.9 3519925.1 1630.68 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_17 Waste Rock Haul_1 525313.9 3519942.4 1630.68 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_18 Waste Rock Haul_1 525295.9 3519959.8 1630.68 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_19 Waste Rock Haul_1 525278.0 3519977.2 1630.68 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_20 Waste Rock Haul_1 525260.0 3519994.6 1630.68 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_21 Waste Rock Haul_1 525242.0 3520012.0 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_22 Waste Rock Haul_1 525224.1 3520029.3 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_23 Waste Rock Haul_1 525206.1 3520046.7 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_24 Waste Rock Haul_1 525188.1 3520064.1 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_25 Waste Rock Haul_1 525170.1 3520081.5 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_26 Waste Rock Haul_1 525152.2 3520098.9 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_27 Waste Rock Haul_1 525134.2 3520116.2 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_28 Waste Rock Haul_1 525116.2 3520133.6 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_29 Waste Rock Haul_1 525098.3 3520151.0 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_30 Waste Rock Haul_1 525080.3 3520168.4 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_31 Waste Rock Haul_1 525062.3 3520185.8 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_32 Waste Rock Haul_1 525044.4 3520203.1 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_33 Waste Rock Haul_1 525026.4 3520220.5 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_34 Waste Rock Haul_1 525008.4 3520237.9 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_35 Waste Rock Haul_1 524990.4 3520255.3 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_36 Waste Rock Haul_1 524972.5 3520272.7 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_37 Waste Rock Haul_1 524953.4 3520288.7 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_38 Waste Rock Haul_1 524932.7 3520302.7 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_39 Waste Rock Haul_1 524912.1 3520316.8 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_40 Waste Rock Haul_1 524891.4 3520330.9 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_41 Waste Rock Haul_1 524870.8 3520345.0 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_42 Waste Rock Haul_1 524850.1 3520359.1 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_43 Waste Rock Haul_1 524829.5 3520373.2 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_44 Waste Rock Haul_1 524808.8 3520387.3 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_45 Waste Rock Haul_1 524788.2 3520401.4 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_46 Waste Rock Haul_1 524767.5 3520415.5 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003


PNB000842

Volume Sources


Easting (X)(m)

Northing (Y)(m)

Base Elevation

(m)

Release Height

(m)

Initial Lateral

Dimension (m)

Initial Vertical

Dimension (m)

PM10

(lb/hr)

PM2.5

(lb/hr)CO

(lb/hr)

NOx

(lb/hr)

SO2

(lb/hr)


WHR1_47 Waste Rock Haul_1 524746.9 3520429.6 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_48 Waste Rock Haul_1 524726.2 3520443.7 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_49 Waste Rock Haul_1 524705.6 3520457.8 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_50 Waste Rock Haul_1 524684.9 3520471.8 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_51 Waste Rock Haul_1 524664.3 3520485.9 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_52 Waste Rock Haul_1 524643.6 3520500.0 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_53 Waste Rock Haul_1 524623.0 3520514.1 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_54 Waste Rock Haul_1 524602.3 3520528.2 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_55 Waste Rock Haul_1 524581.7 3520542.3 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_56 Waste Rock Haul_1 524561.0 3520556.4 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_57 Waste Rock Haul_1 524540.4 3520570.5 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_58 Waste Rock Haul_1 524519.7 3520584.6 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_59 Waste Rock Haul_1 524499.1 3520598.7 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_60 Waste Rock Haul_1 524478.4 3520612.8 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_61 Waste Rock Haul_1 524457.8 3520626.8 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_62 Waste Rock Haul_1 524437.1 3520640.9 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_63 Waste Rock Haul_1 524416.5 3520655.0 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_64 Waste Rock Haul_1 524395.8 3520669.1 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_65 Waste Rock Haul_1 524375.2 3520683.2 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_66 Waste Rock Haul_1 524354.5 3520697.3 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_67 Waste Rock Haul_1 524333.9 3520711.4 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_68 Waste Rock Haul_1 524313.2 3520725.5 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_69 Waste Rock Haul_1 524292.6 3520739.6 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_70 Waste Rock Haul_1 524271.9 3520753.7 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_71 Waste Rock Haul_1 524251.3 3520767.8 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_72 Waste Rock Haul_1 524230.6 3520781.9 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_73 Waste Rock Haul_1 524210.0 3520795.9 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_74 Waste Rock Haul_1 524189.3 3520810.0 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_75 Waste Rock Haul_1 524168.7 3520824.1 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_76 Waste Rock Haul_1 524148.0 3520838.2 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_77 Waste Rock Haul_1 524127.4 3520852.3 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_78 Waste Rock Haul_1 524106.7 3520866.4 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_79 Waste Rock Haul_1 524086.1 3520880.5 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_80 Waste Rock Haul_1 524065.4 3520894.6 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_81 Waste Rock Haul_1 524044.8 3520908.7 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_82 Waste Rock Haul_1 524024.1 3520922.8 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_83 Waste Rock Haul_1 524003.5 3520936.9 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_84 Waste Rock Haul_1 523982.8 3520951.0 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_85 Waste Rock Haul_1 523962.2 3520965.0 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_86 Waste Rock Haul_1 523941.5 3520979.1 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_87 Waste Rock Haul_1 523920.9 3520993.2 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_88 Waste Rock Haul_1 523900.2 3521007.3 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_89 Waste Rock Haul_1 523879.6 3521021.4 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_90 Waste Rock Haul_1 523858.9 3521035.5 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_91 Waste Rock Haul_1 523838.3 3521049.6 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_92 Waste Rock Haul_1 523817.6 3521063.7 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_93 Waste Rock Haul_1 523797.0 3521077.8 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_94 Waste Rock Haul_1 523776.3 3521091.9 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_95 Waste Rock Haul_1 523759.8 3521110.2 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_96 Waste Rock Haul_1 523745.0 3521130.4 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_97 Waste Rock Haul_1 523730.2 3521150.5 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_98 Waste Rock Haul_1 523715.4 3521170.7 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_99 Waste Rock Haul_1 523714.4 3521191.9 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_100 Waste Rock Haul_1 523725.7 3521214.2 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_101 Waste Rock Haul_1 523737.1 3521236.5 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_102 Waste Rock Haul_1 523748.5 3521258.8 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_103 Waste Rock Haul_1 523759.8 3521281.0 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_104 Waste Rock Haul_1 523771.2 3521303.3 1581.91 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_105 Waste Rock Haul_1 523782.5 3521325.6 1543.81 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_106 Waste Rock Haul_1 523793.9 3521347.8 1543.81 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_107 Waste Rock Haul_1 523805.3 3521370.1 1543.81 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_108 Waste Rock Haul_1 523816.6 3521392.4 1543.81 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_109 Waste Rock Haul_1 523828.0 3521414.6 1543.81 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_110 Waste Rock Haul_1 523839.3 3521436.9 1543.81 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_111 Waste Rock Haul_1 523846.5 3521459.2 1543.81 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_112 Waste Rock Haul_1 523834.9 3521481.3 1543.81 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_113 Waste Rock Haul_1 523823.4 3521503.5 1543.81 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_114 Waste Rock Haul_1 523811.8 3521525.7 1543.81 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_115 Waste Rock Haul_1 523800.2 3521547.8 1543.81 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_116 Waste Rock Haul_1 523788.7 3521570.0 1543.81 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_117 Waste Rock Haul_1 523777.1 3521592.2 1543.81 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_118 Waste Rock Haul_1 523765.6 3521614.3 1543.81 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_119 Waste Rock Haul_1 523754.0 3521636.5 1543.81 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_120 Waste Rock Haul_1 523744.3 3521659.2 1543.81 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_121 Waste Rock Haul_1 523742.0 3521684.1 1543.81 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_122 Waste Rock Haul_1 523739.7 3521709.0 1543.81 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_123 Waste Rock Haul_1 523737.3 3521733.9 1543.81 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_124 Waste Rock Haul_1 523750.5 3521739.3 1543.81 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_125 Waste Rock Haul_1 523774.2 3521731.3 1543.81 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR1_126 Waste Rock Haul_1 523787.5 3521715.5 1543.81 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003


PNB000843

Volume Sources


Easting (X)(m)

Northing (Y)(m)

Base Elevation

(m)

Release Height

(m)

Initial Lateral

Dimension (m)

Initial Vertical

Dimension (m)

PM10

(lb/hr)

PM2.5

(lb/hr)CO

(lb/hr)

NOx

(lb/hr)

SO2

(lb/hr)




PNB000844

Volume Sources


Easting (X)(m)

Northing (Y)(m)

Base Elevation

(m)

Release Height

(m)

Initial Lateral

Dimension (m)

Initial Vertical

Dimension (m)

PM10

(lb/hr)

PM2.5

(lb/hr)CO

(lb/hr)

NOx

(lb/hr)

SO2

(lb/hr)




PNB000845

Volume Sources


Easting (X)(m)

Northing (Y)(m)

Base Elevation

(m)

Release Height

(m)

Initial Lateral

Dimension (m)

Initial Vertical

Dimension (m)

PM10

(lb/hr)

PM2.5

(lb/hr)CO

(lb/hr)

NOx

(lb/hr)

SO2

(lb/hr)




PNB000846

Volume Sources


Easting (X)(m)

Northing (Y)(m)

Base Elevation

(m)

Release Height

(m)

Initial Lateral

Dimension (m)

Initial Vertical

Dimension (m)

PM10

(lb/hr)

PM2.5

(lb/hr)CO

(lb/hr)

NOx

(lb/hr)

SO2

(lb/hr)




PNB000847

Volume Sources


Easting (X)(m)

Northing (Y)(m)

Base Elevation

(m)

Release Height

(m)

Initial Lateral

Dimension (m)

Initial Vertical

Dimension (m)

PM10

(lb/hr)

PM2.5

(lb/hr)CO

(lb/hr)

NOx

(lb/hr)

SO2

(lb/hr)


WHR2_194 Waste Rock Haul_2 525185.8 3522521.7 1569.72 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_195 Waste Rock Haul_2 525160.8 3522522.1 1569.72 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_196 Waste Rock Haul_2 525135.8 3522522.5 1569.72 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_197 Waste Rock Haul_2 525110.8 3522522.8 1569.72 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_198 Waste Rock Haul_2 525085.8 3522523.2 1569.72 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_199 Waste Rock Haul_2 525060.8 3522523.6 1569.72 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_200 Waste Rock Haul_2 525035.8 3522524.0 1569.72 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_201 Waste Rock Haul_2 525010.8 3522524.3 1569.72 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_202 Waste Rock Haul_2 524985.8 3522524.7 1569.72 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_203 Waste Rock Haul_2 524960.8 3522525.1 1569.72 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_204 Waste Rock Haul_2 524935.8 3522525.4 1569.72 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_205 Waste Rock Haul_2 524910.8 3522525.8 1569.72 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_206 Waste Rock Haul_2 524885.8 3522526.2 1569.72 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_207 Waste Rock Haul_2 524862.3 3522523.8 1569.72 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_208 Waste Rock Haul_2 524849.7 3522502.2 1569.72 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_209 Waste Rock Haul_2 524837.1 3522480.7 1569.72 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_210 Waste Rock Haul_2 524824.5 3522459.1 1554.48 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_211 Waste Rock Haul_2 524811.9 3522437.5 1554.48 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_212 Waste Rock Haul_2 524799.2 3522415.9 1554.48 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_213 Waste Rock Haul_2 524786.6 3522394.3 1554.48 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_214 Waste Rock Haul_2 524774.0 3522372.7 1554.48 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_215 Waste Rock Haul_2 524761.4 3522351.2 1554.48 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_216 Waste Rock Haul_2 524748.8 3522329.6 1554.48 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_217 Waste Rock Haul_2 524736.2 3522308.0 1554.48 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_218 Waste Rock Haul_2 524723.5 3522286.4 1554.48 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_219 Waste Rock Haul_2 524710.9 3522264.8 1554.48 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_220 Waste Rock Haul_2 524698.3 3522243.2 1554.48 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_221 Waste Rock Haul_2 524685.7 3522221.7 1554.48 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_222 Waste Rock Haul_2 524673.1 3522200.1 1554.48 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_223 Waste Rock Haul_2 524653.3 3522185.7 1554.48 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_224 Waste Rock Haul_2 524631.6 3522173.3 1554.48 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_225 Waste Rock Haul_2 524609.9 3522160.9 1554.48 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_226 Waste Rock Haul_2 524588.2 3522148.5 1554.48 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_227 Waste Rock Haul_2 524566.5 3522136.1 1554.48 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_228 Waste Rock Haul_2 524544.8 3522123.6 1554.48 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_229 Waste Rock Haul_2 524523.1 3522111.2 1554.48 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_230 Waste Rock Haul_2 524501.4 3522098.8 1554.48 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_231 Waste Rock Haul_2 524479.7 3522086.4 1554.48 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_232 Waste Rock Haul_2 524458.0 3522074.0 1554.48 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_233 Waste Rock Haul_2 524436.3 3522061.6 1554.48 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_234 Waste Rock Haul_2 524414.6 3522049.2 1554.48 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_235 Waste Rock Haul_2 524392.9 3522036.7 1554.48 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_236 Waste Rock Haul_2 524371.2 3522024.3 1554.48 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_237 Waste Rock Haul_2 524349.5 3522011.9 1554.48 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_238 Waste Rock Haul_2 524327.8 3521999.5 1554.48 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_239 Waste Rock Haul_2 524306.1 3521987.1 1554.48 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_240 Waste Rock Haul_2 524284.4 3521974.7 1554.48 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_241 Waste Rock Haul_2 524262.7 3521962.2 1554.48 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_242 Waste Rock Haul_2 524241.0 3521949.8 1554.48 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_243 Waste Rock Haul_2 524219.3 3521937.4 1554.48 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_244 Waste Rock Haul_2 524197.6 3521925.0 1554.48 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_245 Waste Rock Haul_2 524175.9 3521912.6 1554.48 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_246 Waste Rock Haul_2 524154.2 3521900.2 1554.48 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003WHR2_247 Waste Rock Haul_2 524132.5 3521887.8 1554.48 6.5 11.63 6.05 0.26 0.03 0.20 0.18 0.0003


PNB000848

Volume Sources


Easting (X)(m)

Northing (Y)(m)

Base Elevation

(m)

Release Height

(m)

Initial Lateral

Dimension (m)

Initial Vertical

Dimension (m)

PM10

(lb/hr)

PM2.5

(lb/hr)CO

(lb/hr)

NOx

(lb/hr)

SO2

(lb/hr)

BLST1 Blasting Emissions 522950.8 3522110.1 1371.60 10 14.19 9.30 --- 0.15 --- 4.54 0.53BLST2 Blasting Emissions 523118.4 3522114.9 1371.60 10 14.19 9.30 --- 0.15 --- 4.54 0.53BLST3 Blasting Emissions 522943.3 3521919.8 1371.60 10 14.19 9.30 --- 0.15 --- 4.54 0.53BLST5 Blasting Emissions 522943.3 3521706.8 1371.60 10 14.19 9.30 --- 0.15 --- 4.54 0.53BLST4 Blasting Emissions 523116.3 3521920.4 1371.60 10 14.19 9.30 --- 0.15 --- 4.54 0.53BLST6 Blasting Emissions 523116.3 3521712.7 1371.60 10 14.19 9.30 --- 0.15 --- 4.54 0.53PC01 ROM Stockpile Wind Erosion 523934.4 3521928.6 1548.27 6 74.00 5.60 --- 0.26 --- --- ---

PC02Unloading to Primary Crusher Dump

Hopper 524048.9 3521939.3 1541.62 0 2.79 0.47 --- 0.10 --- --- ---TDS19B Tailings Wind Erosion 525277.6 3521892.0 1572.77 6 233.00 5.58 --- 0.00 --- --- ---TDS19A Tailings Wind Erosion 525469.9 3520860.1 1551.43 6 233.00 5.58 --- 2.01 --- --- ---TDS19C Tailings Wind Erosion 524564.6 3521080.7 1551.43 6 140.00 5.58 --- 0.17 --- --- ---

MS07Transfer of Sodium Metaphosphate to the

Sodium Metaphosphate Storage Bin 524213.2 3522567.7 1524.00 3 0.47 0.70 --- 0.0005 --- --- ---

MS09Flocculant Feed Bin to Flocculant Screw

Feeder 524265.9 3522569.9 1524.00 3 0.47 0.70 --- 0.0001 --- --- ---

MS10Flocculant Screw Feeder to Flocculant

Heated Receiving Hopper 524261.8 3522569.2 1524.00 3 0.47 0.70 --- 0.0001 --- --- ---

MS11Flocculant Heated Receiving Hopper to

Flocculant Venturi 524258.1 3522569.6 1524.00 3 0.47 0.70 --- 0.0001 --- --- ---

MS12Flocculant Venturi to Flocculant Mixing

Tank 524254.4 3522568.8 1524.00 3 0.47 0.70 --- 0.0001 --- --- ---CHR_1 Combination Ore/Waste Rock 523341.7 3522423.3 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_2 Combination Ore/Waste Rock 523357.4 3522403.8 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_3 Combination Ore/Waste Rock 523373.1 3522384.3 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_4 Combination Ore/Waste Rock 523388.8 3522364.9 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_5 Combination Ore/Waste Rock 523404.5 3522345.4 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_6 Combination Ore/Waste Rock 523420.2 3522325.9 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_7 Combination Ore/Waste Rock 523435.9 3522306.5 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_8 Combination Ore/Waste Rock 523451.6 3522287.0 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_9 Combination Ore/Waste Rock 523467.2 3522267.5 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001

CHR_10 Combination Ore/Waste Rock 523482.9 3522248.1 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_11 Combination Ore/Waste Rock 523498.6 3522228.6 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_12 Combination Ore/Waste Rock 523514.3 3522209.1 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_13 Combination Ore/Waste Rock 523530.0 3522189.7 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_14 Combination Ore/Waste Rock 523545.7 3522170.2 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_15 Combination Ore/Waste Rock 523561.4 3522150.7 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_16 Combination Ore/Waste Rock 523577.0 3522131.3 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_17 Combination Ore/Waste Rock 523592.7 3522111.8 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_18 Combination Ore/Waste Rock 523606.0 3522090.9 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_19 Combination Ore/Waste Rock 523615.4 3522067.8 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_20 Combination Ore/Waste Rock 523624.8 3522044.6 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_21 Combination Ore/Waste Rock 523634.1 3522021.4 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_22 Combination Ore/Waste Rock 523643.5 3521998.2 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_23 Combination Ore/Waste Rock 523652.9 3521975.0 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_24 Combination Ore/Waste Rock 523662.2 3521951.9 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_25 Combination Ore/Waste Rock 523671.6 3521928.7 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_26 Combination Ore/Waste Rock 523681.0 3521905.5 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_27 Combination Ore/Waste Rock 523690.3 3521882.3 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_28 Combination Ore/Waste Rock 523699.7 3521859.1 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_29 Combination Ore/Waste Rock 523709.0 3521836.0 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_30 Combination Ore/Waste Rock 523718.4 3521812.8 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_31 Combination Ore/Waste Rock 523731.3 3521793.3 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_32 Combination Ore/Waste Rock 523754.8 3521784.5 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_33 Combination Ore/Waste Rock 523778.2 3521775.7 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_34 Combination Ore/Waste Rock 523801.6 3521766.9 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_35 Combination Ore/Waste Rock 523825.0 3521758.1 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_36 Combination Ore/Waste Rock 523848.4 3521749.3 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_37 Combination Ore/Waste Rock 523872.4 3521751.3 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_38 Combination Ore/Waste Rock 523896.6 3521757.3 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_39 Combination Ore/Waste Rock 523920.9 3521763.4 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_40 Combination Ore/Waste Rock 523945.2 3521769.5 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_41 Combination Ore/Waste Rock 523969.4 3521775.5 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_42 Combination Ore/Waste Rock 523993.7 3521781.6 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_43 Combination Ore/Waste Rock 524017.9 3521787.7 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_44 Combination Ore/Waste Rock 524042.2 3521793.7 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_45 Combination Ore/Waste Rock 524063.9 3521802.8 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_46 Combination Ore/Waste Rock 524074.4 3521825.5 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_47 Combination Ore/Waste Rock 524084.9 3521848.2 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_48 Combination Ore/Waste Rock 524095.3 3521870.9 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_49 Combination Ore/Waste Rock 524089.7 3521878.5 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_50 Combination Ore/Waste Rock 524066.4 3521869.3 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_51 Combination Ore/Waste Rock 524043.1 3521860.2 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_52 Combination Ore/Waste Rock 524019.8 3521851.1 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_53 Combination Ore/Waste Rock 523996.6 3521842.0 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_54 Combination Ore/Waste Rock 523973.3 3521832.9 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001

Year 9 - Modeling Annual Emissions, Volume Sources


PNB000849

Volume Sources


Easting (X)(m)

Northing (Y)(m)

Base Elevation

(m)

Release Height

(m)

Initial Lateral

Dimension (m)

Initial Vertical

Dimension (m)

PM10

(lb/hr)

PM2.5

(lb/hr)CO

(lb/hr)

NOx

(lb/hr)

SO2

(lb/hr)


CHR_55 Combination Ore/Waste Rock 523949.9 3521824.2 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_56 Combination Ore/Waste Rock 523925.4 3521818.9 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_57 Combination Ore/Waste Rock 523901.0 3521813.7 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_58 Combination Ore/Waste Rock 523876.5 3521808.5 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_59 Combination Ore/Waste Rock 523852.1 3521803.3 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_60 Combination Ore/Waste Rock 523827.6 3521798.1 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_61 Combination Ore/Waste Rock 523803.2 3521792.9 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_62 Combination Ore/Waste Rock 523790.5 3521811.7 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_63 Combination Ore/Waste Rock 523779.6 3521834.2 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_64 Combination Ore/Waste Rock 523768.7 3521856.7 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_65 Combination Ore/Waste Rock 523757.8 3521879.2 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_66 Combination Ore/Waste Rock 523746.9 3521901.7 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_67 Combination Ore/Waste Rock 523736.0 3521924.2 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_68 Combination Ore/Waste Rock 523725.1 3521946.7 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_69 Combination Ore/Waste Rock 523714.2 3521969.2 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_70 Combination Ore/Waste Rock 523703.3 3521991.7 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_71 Combination Ore/Waste Rock 523692.4 3522014.2 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_72 Combination Ore/Waste Rock 523681.5 3522036.7 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_73 Combination Ore/Waste Rock 523670.6 3522059.2 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_74 Combination Ore/Waste Rock 523659.7 3522081.7 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_75 Combination Ore/Waste Rock 523648.0 3522103.7 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_76 Combination Ore/Waste Rock 523633.0 3522123.7 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_77 Combination Ore/Waste Rock 523618.0 3522143.7 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_78 Combination Ore/Waste Rock 523603.0 3522163.7 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_79 Combination Ore/Waste Rock 523588.0 3522183.7 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_80 Combination Ore/Waste Rock 523573.0 3522203.7 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_81 Combination Ore/Waste Rock 523558.0 3522223.7 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_82 Combination Ore/Waste Rock 523543.0 3522243.7 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_83 Combination Ore/Waste Rock 523528.0 3522263.7 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_84 Combination Ore/Waste Rock 523513.0 3522283.7 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_85 Combination Ore/Waste Rock 523498.0 3522303.7 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_86 Combination Ore/Waste Rock 523483.0 3522323.7 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_87 Combination Ore/Waste Rock 523468.0 3522343.7 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_88 Combination Ore/Waste Rock 523453.0 3522363.7 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_89 Combination Ore/Waste Rock 523438.0 3522383.7 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_90 Combination Ore/Waste Rock 523423.0 3522403.7 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_91 Combination Ore/Waste Rock 523408.0 3522423.7 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_92 Combination Ore/Waste Rock 523393.0 3522443.7 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001CHR_93 Combination Ore/Waste Rock 523377.8 3522463.5 1402.08 6.5 11.63 6.05 --- 0.03 --- 0.03 0.0001WHR1_1 Waste Rock Haul_1 525100.3 3519801.1 1630.68 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_2 Waste Rock Haul_1 525124.4 3519807.8 1630.68 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_3 Waste Rock Haul_1 525148.7 3519813.6 1630.68 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_4 Waste Rock Haul_1 525173.0 3519819.3 1630.68 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_5 Waste Rock Haul_1 525197.3 3519825.1 1630.68 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_6 Waste Rock Haul_1 525221.7 3519830.9 1630.68 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_7 Waste Rock Haul_1 525246.0 3519836.6 1630.68 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_8 Waste Rock Haul_1 525270.3 3519842.4 1630.68 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_9 Waste Rock Haul_1 525294.6 3519848.2 1630.68 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003

WHR1_10 Waste Rock Haul_1 525319.0 3519853.9 1630.68 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_11 Waste Rock Haul_1 525343.3 3519859.7 1630.68 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_12 Waste Rock Haul_1 525367.6 3519865.5 1630.68 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_13 Waste Rock Haul_1 525385.8 3519872.9 1630.68 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_14 Waste Rock Haul_1 525367.8 3519890.3 1630.68 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_15 Waste Rock Haul_1 525349.9 3519907.7 1630.68 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_16 Waste Rock Haul_1 525331.9 3519925.1 1630.68 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_17 Waste Rock Haul_1 525313.9 3519942.4 1630.68 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_18 Waste Rock Haul_1 525295.9 3519959.8 1630.68 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_19 Waste Rock Haul_1 525278.0 3519977.2 1630.68 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_20 Waste Rock Haul_1 525260.0 3519994.6 1630.68 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_21 Waste Rock Haul_1 525242.0 3520012.0 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_22 Waste Rock Haul_1 525224.1 3520029.3 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_23 Waste Rock Haul_1 525206.1 3520046.7 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_24 Waste Rock Haul_1 525188.1 3520064.1 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_25 Waste Rock Haul_1 525170.1 3520081.5 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_26 Waste Rock Haul_1 525152.2 3520098.9 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_27 Waste Rock Haul_1 525134.2 3520116.2 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_28 Waste Rock Haul_1 525116.2 3520133.6 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_29 Waste Rock Haul_1 525098.3 3520151.0 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_30 Waste Rock Haul_1 525080.3 3520168.4 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_31 Waste Rock Haul_1 525062.3 3520185.8 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_32 Waste Rock Haul_1 525044.4 3520203.1 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_33 Waste Rock Haul_1 525026.4 3520220.5 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_34 Waste Rock Haul_1 525008.4 3520237.9 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_35 Waste Rock Haul_1 524990.4 3520255.3 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_36 Waste Rock Haul_1 524972.5 3520272.7 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_37 Waste Rock Haul_1 524953.4 3520288.7 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003


PNB000850

Volume Sources


Easting (X)(m)

Northing (Y)(m)

Base Elevation

(m)

Release Height

(m)

Initial Lateral

Dimension (m)

Initial Vertical

Dimension (m)

PM10

(lb/hr)

PM2.5

(lb/hr)CO

(lb/hr)

NOx

(lb/hr)

SO2

(lb/hr)


WHR1_38 Waste Rock Haul_1 524932.7 3520302.7 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_39 Waste Rock Haul_1 524912.1 3520316.8 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_40 Waste Rock Haul_1 524891.4 3520330.9 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_41 Waste Rock Haul_1 524870.8 3520345.0 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_42 Waste Rock Haul_1 524850.1 3520359.1 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_43 Waste Rock Haul_1 524829.5 3520373.2 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_44 Waste Rock Haul_1 524808.8 3520387.3 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_45 Waste Rock Haul_1 524788.2 3520401.4 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_46 Waste Rock Haul_1 524767.5 3520415.5 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_47 Waste Rock Haul_1 524746.9 3520429.6 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_48 Waste Rock Haul_1 524726.2 3520443.7 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_49 Waste Rock Haul_1 524705.6 3520457.8 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_50 Waste Rock Haul_1 524684.9 3520471.8 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_51 Waste Rock Haul_1 524664.3 3520485.9 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_52 Waste Rock Haul_1 524643.6 3520500.0 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_53 Waste Rock Haul_1 524623.0 3520514.1 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_54 Waste Rock Haul_1 524602.3 3520528.2 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_55 Waste Rock Haul_1 524581.7 3520542.3 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_56 Waste Rock Haul_1 524561.0 3520556.4 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_57 Waste Rock Haul_1 524540.4 3520570.5 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_58 Waste Rock Haul_1 524519.7 3520584.6 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_59 Waste Rock Haul_1 524499.1 3520598.7 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_60 Waste Rock Haul_1 524478.4 3520612.8 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_61 Waste Rock Haul_1 524457.8 3520626.8 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_62 Waste Rock Haul_1 524437.1 3520640.9 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_63 Waste Rock Haul_1 524416.5 3520655.0 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_64 Waste Rock Haul_1 524395.8 3520669.1 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_65 Waste Rock Haul_1 524375.2 3520683.2 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_66 Waste Rock Haul_1 524354.5 3520697.3 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_67 Waste Rock Haul_1 524333.9 3520711.4 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_68 Waste Rock Haul_1 524313.2 3520725.5 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_69 Waste Rock Haul_1 524292.6 3520739.6 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_70 Waste Rock Haul_1 524271.9 3520753.7 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_71 Waste Rock Haul_1 524251.3 3520767.8 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_72 Waste Rock Haul_1 524230.6 3520781.9 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_73 Waste Rock Haul_1 524210.0 3520795.9 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_74 Waste Rock Haul_1 524189.3 3520810.0 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_75 Waste Rock Haul_1 524168.7 3520824.1 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_76 Waste Rock Haul_1 524148.0 3520838.2 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_77 Waste Rock Haul_1 524127.4 3520852.3 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_78 Waste Rock Haul_1 524106.7 3520866.4 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_79 Waste Rock Haul_1 524086.1 3520880.5 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_80 Waste Rock Haul_1 524065.4 3520894.6 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_81 Waste Rock Haul_1 524044.8 3520908.7 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_82 Waste Rock Haul_1 524024.1 3520922.8 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_83 Waste Rock Haul_1 524003.5 3520936.9 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_84 Waste Rock Haul_1 523982.8 3520951.0 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_85 Waste Rock Haul_1 523962.2 3520965.0 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_86 Waste Rock Haul_1 523941.5 3520979.1 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_87 Waste Rock Haul_1 523920.9 3520993.2 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_88 Waste Rock Haul_1 523900.2 3521007.3 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_89 Waste Rock Haul_1 523879.6 3521021.4 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_90 Waste Rock Haul_1 523858.9 3521035.5 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_91 Waste Rock Haul_1 523838.3 3521049.6 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_92 Waste Rock Haul_1 523817.6 3521063.7 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_93 Waste Rock Haul_1 523797.0 3521077.8 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_94 Waste Rock Haul_1 523776.3 3521091.9 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_95 Waste Rock Haul_1 523759.8 3521110.2 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_96 Waste Rock Haul_1 523745.0 3521130.4 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_97 Waste Rock Haul_1 523730.2 3521150.5 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_98 Waste Rock Haul_1 523715.4 3521170.7 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_99 Waste Rock Haul_1 523714.4 3521191.9 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_100 Waste Rock Haul_1 523725.7 3521214.2 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_101 Waste Rock Haul_1 523737.1 3521236.5 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_102 Waste Rock Haul_1 523748.5 3521258.8 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_103 Waste Rock Haul_1 523759.8 3521281.0 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_104 Waste Rock Haul_1 523771.2 3521303.3 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_105 Waste Rock Haul_1 523782.5 3521325.6 1543.81 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_106 Waste Rock Haul_1 523793.9 3521347.8 1543.81 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_107 Waste Rock Haul_1 523805.3 3521370.1 1543.81 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_108 Waste Rock Haul_1 523816.6 3521392.4 1543.81 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_109 Waste Rock Haul_1 523828.0 3521414.6 1543.81 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_110 Waste Rock Haul_1 523839.3 3521436.9 1543.81 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_111 Waste Rock Haul_1 523846.5 3521459.2 1543.81 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_112 Waste Rock Haul_1 523834.9 3521481.3 1543.81 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_113 Waste Rock Haul_1 523823.4 3521503.5 1543.81 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003


PNB000851

Volume Sources


Easting (X)(m)

Northing (Y)(m)

Base Elevation

(m)

Release Height

(m)

Initial Lateral

Dimension (m)

Initial Vertical

Dimension (m)

PM10

(lb/hr)

PM2.5

(lb/hr)CO

(lb/hr)

NOx

(lb/hr)

SO2

(lb/hr)




PNB000852

Volume Sources


Easting (X)(m)

Northing (Y)(m)

Base Elevation

(m)

Release Height

(m)

Initial Lateral

Dimension (m)

Initial Vertical

Dimension (m)

PM10

(lb/hr)

PM2.5

(lb/hr)CO

(lb/hr)

NOx

(lb/hr)

SO2

(lb/hr)


WHR1_190 Waste Rock Haul_1 524582.4 3520597.7 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_191 Waste Rock Haul_1 524602.9 3520583.3 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_192 Waste Rock Haul_1 524623.3 3520568.9 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_193 Waste Rock Haul_1 524643.7 3520554.4 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_194 Waste Rock Haul_1 524664.2 3520540.0 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_195 Waste Rock Haul_1 524684.6 3520525.6 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_196 Waste Rock Haul_1 524705.0 3520511.2 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_197 Waste Rock Haul_1 524725.5 3520496.8 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_198 Waste Rock Haul_1 524745.9 3520482.4 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_199 Waste Rock Haul_1 524766.3 3520468.0 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_200 Waste Rock Haul_1 524786.8 3520453.6 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_201 Waste Rock Haul_1 524807.2 3520439.2 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_202 Waste Rock Haul_1 524827.6 3520424.8 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_203 Waste Rock Haul_1 524848.1 3520410.4 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_204 Waste Rock Haul_1 524868.5 3520396.0 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_205 Waste Rock Haul_1 524889.0 3520381.6 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_206 Waste Rock Haul_1 524909.4 3520367.2 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_207 Waste Rock Haul_1 524929.8 3520352.8 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_208 Waste Rock Haul_1 524950.3 3520338.4 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_209 Waste Rock Haul_1 524968.7 3520321.6 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_210 Waste Rock Haul_1 524986.7 3520304.2 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_211 Waste Rock Haul_1 525004.7 3520286.9 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_212 Waste Rock Haul_1 525022.7 3520269.6 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_213 Waste Rock Haul_1 525040.7 3520252.2 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_214 Waste Rock Haul_1 525058.7 3520234.9 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_215 Waste Rock Haul_1 525076.7 3520217.6 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_216 Waste Rock Haul_1 525094.8 3520200.2 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_217 Waste Rock Haul_1 525112.8 3520182.9 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_218 Waste Rock Haul_1 525130.8 3520165.5 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_219 Waste Rock Haul_1 525148.8 3520148.2 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_220 Waste Rock Haul_1 525166.8 3520130.9 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_221 Waste Rock Haul_1 525184.8 3520113.5 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_222 Waste Rock Haul_1 525202.8 3520096.2 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_223 Waste Rock Haul_1 525220.8 3520078.8 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_224 Waste Rock Haul_1 525238.8 3520061.5 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_225 Waste Rock Haul_1 525256.9 3520044.2 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_226 Waste Rock Haul_1 525274.9 3520026.8 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_227 Waste Rock Haul_1 525292.9 3520009.5 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_228 Waste Rock Haul_1 525310.9 3519992.2 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_229 Waste Rock Haul_1 525328.9 3519974.8 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_230 Waste Rock Haul_1 525346.9 3519957.5 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_231 Waste Rock Haul_1 525364.9 3519940.1 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_232 Waste Rock Haul_1 525382.9 3519922.8 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_233 Waste Rock Haul_1 525400.9 3519905.5 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_234 Waste Rock Haul_1 525419.0 3519888.1 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_235 Waste Rock Haul_1 525437.0 3519870.8 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_236 Waste Rock Haul_1 525455.0 3519853.5 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_237 Waste Rock Haul_1 525473.0 3519836.1 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_238 Waste Rock Haul_1 525460.9 3519827.2 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_239 Waste Rock Haul_1 525436.5 3519821.6 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_240 Waste Rock Haul_1 525412.1 3519816.0 1581.91 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_241 Waste Rock Haul_1 525387.8 3519810.5 1630.68 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_242 Waste Rock Haul_1 525363.4 3519804.9 1630.68 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_243 Waste Rock Haul_1 525339.0 3519799.4 1630.68 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_244 Waste Rock Haul_1 525314.6 3519793.8 1630.68 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_245 Waste Rock Haul_1 525290.3 3519788.3 1630.68 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_246 Waste Rock Haul_1 525265.9 3519782.7 1630.68 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_247 Waste Rock Haul_1 525241.5 3519777.2 1630.68 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_248 Waste Rock Haul_1 525217.1 3519771.6 1630.68 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_249 Waste Rock Haul_1 525192.7 3519766.1 1630.68 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_250 Waste Rock Haul_1 525168.4 3519760.5 1630.68 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_251 Waste Rock Haul_1 525144.0 3519755.0 1630.68 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_252 Waste Rock Haul_1 525119.6 3519749.4 1630.68 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR1_253 Waste Rock Haul_1 525095.5 3519743.3 1630.68 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR2_1 Waste Rock Haul_2 524141.6 3521807.9 1554.48 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR2_2 Waste Rock Haul_2 524166.6 3521806.6 1554.48 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR2_3 Waste Rock Haul_2 524190.8 3521808.6 1554.48 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR2_4 Waste Rock Haul_2 524213.1 3521819.9 1554.48 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR2_5 Waste Rock Haul_2 524235.4 3521831.3 1554.48 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR2_6 Waste Rock Haul_2 524257.6 3521842.7 1554.48 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR2_7 Waste Rock Haul_2 524279.9 3521854.0 1554.48 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR2_8 Waste Rock Haul_2 524302.2 3521865.4 1554.48 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR2_9 Waste Rock Haul_2 524324.4 3521876.8 1554.48 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003

WHR2_10 Waste Rock Haul_2 524346.7 3521888.1 1554.48 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR2_11 Waste Rock Haul_2 524369.0 3521899.5 1554.48 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR2_12 Waste Rock Haul_2 524391.2 3521910.9 1554.48 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003


PNB000853

Volume Sources


Easting (X)(m)

Northing (Y)(m)

Base Elevation

(m)

Release Height

(m)

Initial Lateral

Dimension (m)

Initial Vertical

Dimension (m)

PM10

(lb/hr)

PM2.5

(lb/hr)CO

(lb/hr)

NOx

(lb/hr)

SO2

(lb/hr)




PNB000854

Volume Sources


Easting (X)(m)

Northing (Y)(m)

Base Elevation

(m)

Release Height

(m)

Initial Lateral

Dimension (m)

Initial Vertical

Dimension (m)

PM10

(lb/hr)

PM2.5

(lb/hr)CO

(lb/hr)

NOx

(lb/hr)

SO2

(lb/hr)




PNB000855

Volume Sources


Easting (X)(m)

Northing (Y)(m)

Base Elevation

(m)

Release Height

(m)

Initial Lateral

Dimension (m)

Initial Vertical

Dimension (m)

PM10

(lb/hr)

PM2.5

(lb/hr)CO

(lb/hr)

NOx

(lb/hr)

SO2

(lb/hr)




PNB000856

Volume Sources


Easting (X)(m)

Northing (Y)(m)

Base Elevation

(m)

Release Height

(m)

Initial Lateral

Dimension (m)

Initial Vertical

Dimension (m)

PM10

(lb/hr)

PM2.5

(lb/hr)CO

(lb/hr)

NOx

(lb/hr)

SO2

(lb/hr)


WHR2_241 Waste Rock Haul_2 524262.7 3521962.2 1554.48 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR2_242 Waste Rock Haul_2 524241.0 3521949.8 1554.48 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR2_243 Waste Rock Haul_2 524219.3 3521937.4 1554.48 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR2_244 Waste Rock Haul_2 524197.6 3521925.0 1554.48 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR2_245 Waste Rock Haul_2 524175.9 3521912.6 1554.48 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR2_246 Waste Rock Haul_2 524154.2 3521900.2 1554.48 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003WHR2_247 Waste Rock Haul_2 524132.5 3521887.8 1554.48 6.5 11.63 6.05 --- 0.11 --- 0.15 0.0003


PNB000857

Road Source Allocation

Pit Pit 2

Waste Rock

Haul Road

Combination

Haul Road

Haulage Trucks, 260 tons(Tier 4) 50% 0% 48% 2%

Crawler Dozers, D10T Class 50% 50% 0% 0%

Rubber Tired Dozers, 834 Class 50% 50% 0% 0%

Motor Graders, 16M Class

50% 50% 0% 0%

Water Trucks, 30,000 gallons

50% 0% 48% 2%

Diesel Blasthole Drill PV311, 12.25 inches 100% 0% 0% 0%

Hydraulic DML Drill100% 0% 0% 0%

Front End Loader 99450% 50% 0% 0%

CAT 6060 50% 50% 0% 0%

Stemming Truck 50% 50% 0% 0%

ANFO/Slurry Truck, 20 tons 100% 0% 0% 0%

Powder Truck, 2 tons 100% 0% 0% 0%

Front End Loaders, 8 yd350% 50% 0% 0%

Hydraulic Excavator, 385 Cat CL (390 DL) 50% 50% 0% 0%

Backhoe/Loader, 2 yd3 (450F) 50% 50% 0% 0%

All-Terrain Crane, 75 tons100% 0% 0% 0%

Transporter with Tractor, 200 tons (789D) 0% 0% 96% 4%

Fuel/Lube Trucks, 6,000 gallons 0% 0% 96% 4%

Truck Mounted Lube Truck 0% 0% 96% 4%

Mechanic Field Service Trucks 0% 0% 96% 4%

Tire Handler 0% 0% 96% 4%

Light Plant, 6 kW 50% 50% 0% 0%Boom Trucks 10 tons, 45 foot boom 50% 50% 0% 0%Boom Trucks 15 tons, 60 foot boom 50% 50% 0% 0%

Front End Loader, 6 yd3 (980K) 50% 50% 0% 0%

Front End Loader, 5 yd3 (930K) 50% 50% 0% 0%

Flat Bed Trucks, 10 tons 0% 0% 96% 4%

Dump Truck, 10 tons 0% 0% 96% 4%

CS683 Soil Compactor / Roller 50% 50% 0% 0%

246C Skid Steer Loader 50% 50% 0% 0%

Off-Road Tire Handling Truck 0% 0% 96% 4%

Street Sweeper 0% 0% 96% 4%

Shovel Motivator 50% 50% 0% 0%

Storm Water Pond Pump 0% 0% 0% 0%

Mine Pit Dewatering Pump 50% 50% 0% 0%

* The waste rock haul road total emissions are distributed over 500 volume sources. The

combination haul road (waste rock and ore) total emissions are distributed over 93 volume

sources.

Fuel Burning Mobile Engine Description

Model Source

Tailpipe Emissions Source Allocation

Rosemont Copper Project

Permit Renewal/Modification July 2017

PNB000858

Road Source Allocation

Pit Pit 2

Waste Rock

Haul Road

Combination

Haul Road

MN01 Drilling 100% 0% 0% 0%

MN03 Loading Concentrate Ore 100% 0% 0% 0%

MN05 Loading Waste Rock 100% 0% 0% 0%

MN06a

Hauling Concentrate Ore to Primary

Crusher Dump Hopper /

Run of Mine Stockpile (Inside the Pit) 100% 0% 0% 0%

MN06b

Hauling Concentrate Ore to Primary

Crusher Dump Hopper /

Run of Mine Stockpile (Outside the Pit) 0% 0% 0% 100%

MN08a

Hauling Waste Rock to Waste Rock Storage

Area (Inside the Pit) 100% 0% 0% 0%

MN08b

Hauling Waste Rock to Waste Rock Storage

Area (Outside the Pit) 0% 0% 96% 4%

MN11

Unloading Waste Rock to Waste Rock

Storage Area 0% 100% 0% 100%

MN12 Bulldozer Use 50% 50% 0% 0%

MN13a Water Truck Use (Inside the Pit) 100% 0% 0% 0%

MN13b Water Truck Use (Outside the Pit) 0% 0% 96% 4%

MN14 Grader Use 50% 50% 0% 0%

MN15a

Support Vehicle Use on Unpaved Roads

(Inside the Pit) 100% 0% 0% 0%

MN15b

Support Vehicle Use on Unpaved Roads

(Outside the Pit) 0% 0% 96% 4%

* The waste rock haul road total emissions are distributed over 500 volume sources. The combination haul road (waste

rock and ore) total emissions are distributed over 93 volume sources.

Model Source

Particulate Source Allocation

Emission Unit ID Emission Unit Description

Rosemont Copper Project

Permit Renewal/Modification July 2017

PNB000859

Rosemont Copper Project | Amended Model Report Trinity Consultants I-1

APPENDIX I: DISPERSION MODEL FILES (ELECTRONIC)

PNB000860

ATTACHMENT 2

Revised Emissions Inventory (Electronic Excel Spreadsheet)

PNB000861

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