102512 dust report 031314 final - city of chicago · executive summary es‐3 figure es‐2...
TRANSCRIPT
City of ChicagoFugitive Dust Study
March 2014
REPORT
ii
Table of Contents
ExecutiveSummary...................................................................................................................................................ES‐1
Section1 IntroductionandPurpose....................................................................................................................1‐1
Section2 ConceptualBulkMaterialStorageFacility......................................................................................2‐1
Section3 EmissionCalculations............................................................................................................................3‐1 3.1DropOperations........................................................................................................................................................3‐1 3.2TravelontheSurfaceofthePile.........................................................................................................................3‐2 3.3PavedRoads................................................................................................................................................................3‐2 3.4BulldozingandGrading..........................................................................................................................................3‐3 3.5WindErosionfromStockpiles.............................................................................................................................3‐4 3.6FugitiveDustEmissionEstimates.....................................................................................................................3‐5
Section4 DispersionModeling..............................................................................................................................4‐1 4.1AERMODReferences/Version.............................................................................................................................4‐1 4.2ModelingSetup...........................................................................................................................................................4‐1
4.2.1Terrain...............................................................................................................................................................4‐1 4.2.2ReceptorGrid..................................................................................................................................................4‐1 4.2.3MeteorologicalDataandLanduse.........................................................................................................4‐1 4.2.4PollutantsandAveragingTimes............................................................................................................4‐5
4.3EmissionSources......................................................................................................................................................4‐5 4.3.1SourceTypes...................................................................................................................................................4‐5 4.3.2ModelingApproach......................................................................................................................................4‐6
4.4PM10(24‐hr)andPM2.5(Annual,24‐hr)ModelingResults.....................................................................4‐7 4.4.1PetcokeMaterialHandlingModelingResults...................................................................................4‐7 4.4.2CoalMaterialHandlingModelingResults..........................................................................................4‐9 4.4.3WindErosionModelingforthePetcokeandCoalStoragePiles............................................4‐10
4.5InterpretationofModelPredictions...............................................................................................................4‐18 4.6ComparisontoBackgroundAirQualityinChicago..................................................................................4‐18
Section5 Conclusions...............................................................................................................................................5‐1
AppendixA PetroleumCokeData..............................................................................................................A‐1
AppendixB SlagData.....................................................................................................................................B‐1
AppendixC ModelingResultsFigures.......................................................................................................C‐1
Table of Contents
iii
List of Figures
FigureES‐1 EstimatesofTotalDustEmissions.......................................................................................................ES‐2 FigureES‐2 EstimatesofPM10Emissions...................................................................................................................ES‐3 FigureES‐3 EstimatesofPM2.5Emissions..................................................................................................................ES‐3 Figure2‐1 ConceptualBulkMaterialStorageFacilityConfigurationofArea,Volume,andLine
VolumeSources................................................................................................................................................2‐2 Figure4‐1 PolarandFencelineReceptorGrid..........................................................................................................4‐3 Figure4‐2 WindroseforChicagoMidwayAirport2008SurfaceObservations........................................4‐4 Figure4‐3 Highest24‐HourAveragePM10ConcentrationPredictionsforPetroleumCoke(All
Sources)............................................................................................................................................................4‐11 Figure4‐4 Highest24‐HourAveragePM2.5ConcentrationPredictionsforPetroleumCoke(All
Sources)............................................................................................................................................................4‐12 Figure4‐5 HighestAnnualAveragePM2.5ConcentrationPredictionsforPetroleumCoke(All
Sources)............................................................................................................................................................4‐13 Figure4‐6 Highest24‐HourAveragePM10ConcentrationPredictionsforCoal(AllSources)........4‐14 Figure4‐7 Highest24‐HourAveragePM2.5ConcentrationPredictionsforCoal(AllSources)........4‐15 Figure4‐8 HighestAnnualAveragePM2.5ConcentrationPredictionsforCoal(AllSources)...........4‐16 Figure4‐9 1‐HourAveragingPeriodPM10EmissionsWindErosionofaPetcokeStoragePile....4‐17 Figure4‐10 1‐HourAveragingPeriodPM10EmissionRateWindErosionofaCoalStoragePile...4‐17 Figure4‐11 AnnualAveragePM2.5ConcentrationsatMonitoringLocationsinChicago......................4‐19 Figure4‐12 24‐HourAveragePM2.5ConcentrationsatMonitoringLocationsinChicago...................4‐19 Figure4‐13 24‐HourAveragePM10ConcentrationsatMonitoringLocationsinChicago....................4‐20 Figure4‐3a 24‐HrAveragePetcokePM10EmissionsModeling;AllEquipmentEmissions..................C‐1Figure4‐3b 24‐HrAveragePetcokePM10EmissionsModeling;Bull‐dozer/GraderEmissions.........C‐2Figure4‐3c 24‐HrAveragePetcokePM10EmissionsModeling;DropEmissions....................................C‐3Figure4‐3d 24‐HrAveragePetcokePM10EmissionsModeling;PavedRoadEmissions......................C‐4Figure4‐3e 24‐HrAveragePetcokePM10EmissionsModeling;EmissionsfromTravelonPile
Surface..................................................................................................................................................................C‐5Figure4‐3f 24‐HrAveragePetcokePM10EmissionsModeling;WindErosionEmissionsfrom
Stockpile.............................................................................................................................................................C‐6Figure4‐4a 24‐HrAveragePetcokePM2.5EmissionsModeling;AllEquipmentEmissions................C‐7Figure4‐4b 24‐HrAveragePetcokePM2.5EmissionsModeling;Bull‐dozer/GraderEmissions.......C‐8Figure4‐4c 24‐HrAveragePetcokePM2.5EmissionsModeling;DropEmissions...................................C‐9Figure4‐4d 24‐HrAveragePetcokePM2.5EmissionsModeling;PavedRoadEmissions..................C‐10Figure4‐4e 24‐HrAveragePetcokePM2.5EmissionsModeling;EmissionsfromTravelonPile
Surface...............................................................................................................................................................C‐11Figure4‐4f 24‐HrAveragePetcokePM2.5EmissionsModeling;WindErosionEmissionsfrom
Stockpile..........................................................................................................................................................C‐12Figure4‐5a AnnualAveragePetcokePM2.5EmissionsModeling;AllEquipmentEmissions..........C‐13Figure4‐5b AnnualAveragePetcokePM2.5EmissionsModeling;Bull‐dozer/GraderEmissions.C‐14Figure4‐5c AnnualAveragePetcokePM2.5EmissionsModeling;DropEmissions..............................C‐15Figure4‐5d AnnualAveragePetcokePM2.5EmissionsModeling;PavedRoadEmissions................C‐16Figure4‐5e AnnualAveragePetcokePM2.5EmissionsModeling;EmissionsfromTravelonPile
Surface.............................................................................................................................................................C‐17Figure4‐5f AnnualAveragePetcokePM2.5EmissionsModeling;WindErosionEmissionsfrom
Stockpile..........................................................................................................................................................C‐18Figure4‐6a 24‐HrAverageCoalPM10EmissionsModeling;AllEquipmentEmissions.....................C‐19
Table of Contents
iv
Figure4‐6b 24‐HrAverageCoalPM10EmissionsModeling;Bull‐dozer/GraderEmissions.............C‐20Figure4‐6c 24‐HrAverageCoalPM10EmissionsModeling;DropEmissions.........................................C‐21Figure4‐6d 24‐HrAverageCoalPM10EmissionsModeling;PavedRoadEmissions...........................C‐22Figure4‐6e 24‐HrAverageCoalPM10EmissionsModeling;EmissionsfromTravelonPile
Surface...............................................................................................................................................................C‐23Figure4‐6f 24‐HrAverageCoalPM10EmissionsModeling;WindErosionEmissionsfrom
Stockpile..........................................................................................................................................................C‐24Figure4‐7a 24‐HrAverageCoalPM2.5EmissionsModeling;AllEquipmentEmissions.....................C‐25Figure4‐7b 24‐HrAverageCoalPM2.5EmissionsModeling;Bull‐dozer/GraderEmissions............C‐26Figure4‐7c 24‐HrAverageCoalPM2.5EmissionsModeling;DropEmissions........................................C‐27Figure4‐7d 24‐HrAverageCoalPM2.5EmissionsModeling;PavedRoadEmissions..........................C‐28Figure4‐7e 24‐HrAverageCoalPM2.5EmissionsModeling;EmissionsfromTravelonPile
Surface..............................................................................................................................................................C‐29Figure4‐7f 24‐HrAverageCoalPM2.5EmissionsModeling;WindErosionEmissionsfrom
Stockpile..........................................................................................................................................................C‐30Figure4‐8a AnnualAverageCoalPM2.5EmissionsModeling;AllEquipmentEmissions..................C‐31Figure4‐8b AnnualAverageCoalPM2.5EmissionsModeling;Bull‐dozer/GraderEmissions.........C‐32Figure4‐8c AnnualAverageCoalPM2.5EmissionsModeling;DropEmissions......................................C‐33Figure4‐8d AnnualAverageCoalPM2.5EmissionsModeling;PavedRoadEmissions........................C‐34Figure4‐8e AnnualAverageCoalPM2.5EmissionsModeling;EmissionsfromTravelonPile Surface..............................................................................................................................................................C‐35Figure4‐8f AnnualAverageCoalPM2.5EmissionsModeling;WindErosionEmissionsfrom
Stockpile..........................................................................................................................................................C‐36Figure4‐9 1‐HourAveragingPeriodPM10Emissions;WindErosionofaPetcokeStoragePile..C‐37Figure4‐10 1‐HourAveragingPeriodPM10EmissionRate;WindErosionofaCoalStoragePile.C‐38
List of Tables
Table2‐1 CharacteristicsofBulkMaterials.............................................................................................................2‐3 Table3‐1 TSPEmissionSummary...............................................................................................................................3‐7 Table3‐2 PM10EmissionSummary.............................................................................................................................3‐8 Table3‐3 PM2.5EmissionSummary............................................................................................................................3‐9 Table4‐1 ModelingSourceSummary........................................................................................................................4‐8 Table4‐2 AERMODModelingResultsSummaryforPetcokeMaterialHandling...................................4‐9 Table4‐3 AERMODModelingResultsSummaryforCoalMaterialHandling.........................................4‐10
ES‐1
Executive Summary
TheCityofChicago(City)hasproposedregulationsfortheHandlingandStorageofBulkMaterialPilestocontrolpotentialemissionsofdustfromfacilitiesthatprocessandstorebulkmaterials.Thisstudyevaluatesthepotentialmechanismsofdustgenerationassociatedwithbulkmaterialpiles,andisdesignedtoinformtheCityconcerningtheimportanceofactivitiesthat,ifunmitigated,couldproduceexcessivedustandadverselyaffectambientairquality.Thestudyfindsthatbulkmaterialpilescaningeneralbesignificantsourcesofdustandcontributetolocalizedexceedancesofambientairqualitystandards.Ofthematerialsevaluated(petcoke,coal,Mesabaore,andslag),potentialemissionsofpetcokewerefoundtobehighest.Factorsimportanttofugitivedustgenerationincludebulkmaterialpropertiessuchassiltcontent,materialhandlingprocedures,andmeteorologicalconditionssuchasdryweatherandhighwinds.
ProceduresdevelopedbytheU.S.EnvironmentalProtectionAgency(EPA)wereimplementedtoestimatepotentialdustemissionsfrommaterialhandlingandstorageactivities,including:
materialdroppingoperations(fromtruckdumping,front‐endloaderuse,conveyors,etc.);
bulldozingandgrading;
vehicletravelonpavedroadsandtheunpavedsurfaceofthestoragepile;and
surfacewinderosionfromstockpiles.
Dustemissionsfrommanyoftheseactivitiesdependuponbulkmaterialcharacteristicssuchasgrainsize(primarilysiltcontent),moisturecontent,andbulkdensity.PertherequestoftheCity,dustemissionswereevaluatedfromfourbulkmaterials:
petroleumcoke(petcoke);
coal;
Mesabaore(enrichedincopperandnickel);and
slag.
Spreadsheetcalculationsweredevelopedtoestimatepotentialemissionsofeachbulkmaterialfromeachsource.AconceptualbulkmaterialprocessingandstoragefacilitywasconstructedusingparametersfromtheCity’sdraftregulationsandknowledgeofactivitiestypicalofbulkmaterialhandling.EPA’sAP42emissionfactormethodswereimplementedusingmaterial‐specificparametersasappropriate.Mitigationeffortswerenotconsideredinordertoestimateconservativeworst‐casedustemissions.
ResultsofthedustemissioncalculationsarepresentedinFigureES‐1(totaldust),FigureES‐2(PM10,orparticulatematterwithaerodynamicdiameterlessthan10µm),andFigureES‐3(PM2.5,orparticulatematterwithaerodynamicdiameterlessthan2.5µm).Comparingbetweenfigures,totaldustemissionsaremuchhigherthanthoseofPM10andPM2.5,reflectiveofthenatureoffugitivedustsourcestoreleaselargerparticlesizes.Thehighestemissionestimatesareforbulldozingoperations,whichdependstronglyonthematerialsiltcontent.Emissionestimatesfromthetravelofhaultrucks
Executive Summary
ES‐2
onthepavedaccessroadandfromgradingthestockpilematerialarethesameforallbulkmaterialsasthecalculationmethodsforthesetwoactivitiesdonotdependonmaterialproperties.Overall,emissionestimatesarehighestforthepetroleumcokematerial.Estimatesofwinderosionemissionsfromthestockpile,thoughlowerthanothersourcesonanannualbasis,maybeofelevatedimportanceonanepisodicbasisastheemissionsareassumedtooccuroveraverylimitednumberofhoursperyear.
ThefugitivedustemissionestimatesweresubsequentlyusedasinputtotheAERMODdispersionmodeltopredicttheincrementalconcentrationsofparticulatematterinambientairthatcouldresultfromtheactivitiesatabulkprocessingandstoragefacility.Akeyaspectofthecalculationsinvolvedthelinkageofhourlyemissionestimatestothemeteorologicaldatausedinthedispersionmodelingstudy.ThepredictedincrementalconcentrationsofPM10andPM2.5exceedthelevelsofNationalAmbientAirQualityStandards(NAAQSs)foranumberoftheemissionsourcesconsidered.SincebackgroundlevelsofPM10andPM2.5alreadyaccountforsubstantialfractionsoftheNAAQSs,substantialmitigationeffortsmayberequiredonthepartofoperatorsofbulkmaterialprocessingandstoragefacilitiestoensurethatfugitivedustemissionsdonotleadtolocalizedexceedancesofambientairqualitystandards.
Figure ES‐1 Estimates of Total Dust Emissions
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PetroleumCoke
Coal Mesaba Ore Slag
An
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Wind Erosion of the Stockpile
Grading Material
Bulldozing Material
Paved Roads
Travel on the Stockpile
Drop Operations
Executive Summary
ES‐3
Figure ES‐2 Estimates of PM10 Emissions
Figure ES‐3 Estimates of PM2.5 Emissions
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PetroleumCoke
Coal Mesaba Ore Slag
An
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Wind Erosion of the Stockpile
Grading Material
Bulldozing Material
Paved Roads
Travel on the Stockpile
Drop Operations
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PetroleumCoke
Coal Mesaba Ore Slag
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Wind Erosion of the Stockpile
Grading Material
Bulldozing Material
Paved Roads
Travel on the Stockpile
Drop Operations
1‐1
Section 1
Introduction and Purpose
Thepresenceandmovementofbulksolidmaterialscanleadtoinadvertent,fugitiveemissionsofdusttotheair.TheCityofChicagohasproposedregulationsfortheHandlingandStorageofBulkMaterialPilestocontrolpotentialemissionsfromfacilitiesthatprocessandstorebulkmaterials.
Thisfugitiveduststudyevaluatesthepotentialmechanismsofdustgenerationassociatedwithbulkmaterialpiles.ThestudyisdesignedtoinformtheCityconcerningtheimportanceofactivitiesthatifunmitigatedmightproducedustandaffectambientairquality.ProceduresdevelopedbytheU.S.EnvironmentalProtectionAgencyareimplementedtoestimatepotentialdustemissionsfrommaterialhandlingactivities,includingdroppingoperations(fromtruckdumping,front‐endloaderuse,conveyors,etc.),bulldozing,vehicletravelonpavedroadsandthesurfaceofthepile,andsurfacewinderosionfromstockpiles.Asdustemissionsofmanyoftheseactivitiesdependuponbulkmaterialcharacteristicssuchasgrainsizeandmoisturecontent,severaldifferentbulksolidmaterialsareevaluated.Predictedemissionsareusedinconjunctionwithairdispersionmodelingtoestimatepotentiallevelsofdustinambientairthatresultfromoperationofabulksolidmaterialstorageandprocessingfacility.
2‐1
Section 2
Conceptual Bulk Material Storage Facility
Thefugitiveduststudyfocusesonagenericbutrepresentativebulkmaterialprocessingfacility.Theconceptualfacilityisnotdesignedtorepresentaspecificbulksolidmaterialsprocessingfacility,butratherismodeledafterspecificationsintheCity’sdraftregulationsandincludesavarietyofprocessescapableofgeneratingdust,someorallofwhichmayberelevanttospecificfacilities.
Forsimplicity,astoragepilecoveringacirculararealfootprintisassumed.Thetopofthepileisassumedtobeconicalfrustuminshape,withsideslopesleadingtoaflattop.Thevolumeofmaterialstorageisassumedtobe100,000cubicyards(yd3),and2,000tonsperday(tpd)ofmaterialisassumedtobeprocessedforfivedayseachweek.
Figure2‐1depictstheconfigurationoftheconceptualbulkmaterialstoragefacility.Apavedaccessroadisassumedtoapproachthefacilityfromtheeastandruntangentialtotheoutsideofthepile.Haultrucksareassumedtotraversetheaccessroadanddepositloadsoffreshmaterialatthenorthernedgeofthepile.Abulldozerandgraderareassumedtomovethebulkmaterialandshapethepile.Afront‐endloaderandanarticulatedtruckareassumedtomovematerialonthesurfaceofthestoragepileandfacilitatetheloadingofaconveyorthatplacesthebulkmaterialonrailcarsorbargesforshipmentoutofthefacility.Theassumedequipmentandoperationsaregenericinconstruction,butaredesignedtorepresentthespectrumofactivitiestypicallyfoundatbulkmaterialstoragefacilities.
Thesizeofthestoragepileisdeterminedbytheassumedvolumeandshapeofthepile.Basedonanassumedratioof0.4ofthediameterofthetop(flat)portionofthepilecomparedtoitsbaseandanassumedpileheightof30feet,thebaseddiameterofthepileiscalculatedtobe469feet.Theresultingexposedsurfacearea(basedontheassumedconicalfrustumshape)is176,325ft2.
Fourdifferentbulkmaterialsareexaminedtoconsiderarangeofcharacteristicsthatinfluencedustemissions.ThebulkmaterialswereselectedinconjunctionwithdiscussionswiththeCityofChicago,andareselectedtoberepresentativeofmaterialslikelyhandledatlocalstorageandprocessingfacilities.Propertiesofthefourmaterials,asgatheredfromsampleanalysesandinformationintheliterature,aresummarizedinTable2‐1.
2‐2
LegendforSources
SLINE1 Lineof18volumesourcesforpavedroademissions(haultrucks)
SLINE2 Lineof6volumesourcesforemissionsfromtravelonthepilesurface(articulatedtruckandfront‐endloader)for24‐hourmodeling
UAREA1 Areasourceforemissionsfromtravelonthepilesurface(articulatedtruckandfront‐endloader)forannualmodeling
PAREA1
FAREA1
Areasourcesforbulldozingandgradingfor24‐hourandannualmodeling,respectively
CAREA1 Areasourceforwinderosionfromstockpiles
VOL1toVOL5
Dropsourcesfromconveyor(1‐3),haultruckdumping(4),andarticulatedtruckloading(5)
Figure 2‐1 Conceptual Bulk Material Storage Facility Configuration of Area, Volume, and Line Volume Sources
Section 2 Conceptual Bulk Material Storage Facility
2‐3
Table 2‐1 Characteristics of Bulk Materials
Property Material
Petcoke Coal Mesaba Ore Slag
Silt (%) 21.2 (a) 4.6 (c) 3 (e) 0.55 (f)
Moisture (%) 6.7 (a) 4.8 (c) 1 (e) 8.69 (f)
Bulk Density (lb/ft3) 50 (b) 50 (d) 135 (e) 60 (g)
Data sources: (a) Average of measurements from two petcoke samples (Appendix A) (b) http://www.petroleumhpv.org/docs/pet_coke/2000‐08‐30Pet%20Coke%20Robust%20Summary.pdf (c) AP42 Table 13.2.4‐1 values for coal in iron and steel industry (d) Typical bituminous value, http://www.tapcoinc.com/content/product_data/Tapco_Catalog_09_p88‐94.pdf (e) http://s3.amazonaws.com/zanran_storage/www.isamill.com/ContentPages/2534118165.pdf#page=8 (f) Average of measurements from three slag samples obtained by CDPH from a local bulk material handling company (Appendix B) (g) http://www.aqua‐calc.com/page/density‐table/substance/slag‐coma‐and‐blank‐furn‐point‐‐blank‐granulated
3‐1
Section 3
Emission Calculations
FugitivedustemissionsareestimatedaccordingtomethodsrecommendedbytheU.S.EnvironmentalProtectionAgency(EPA)initsCompilationofAirPollutantEmissionFactors(AP42)document.AP42hasevolvedtoanon‐linereferencedocumentthatcontainsnumerouschaptersdevotedtoestimatingfugitivedustemissions(http://www.epa.gov/ttn/chief/ap42/index.html).
ThespecificAP42sectionsthatareusedtoestimatepotentialfugitivedustemissionsfrombulkmaterialstoragefacilitiesaredescribedinsubsequentsections.Someoftheemissionfactorsdependonwindvelocities,andarehencetiedtometeorologicaldata(describedinSection4.2.3).Dustemissionsarecalculatedonanhourlybasistocomplementsubsequentairdispersionmodeling.Withtheexceptionofwinderosionfromstockpiles,emissionsareestimatedduringassumedhoursoffacilityoperationfrom7:00AMthrough5:00PM(tenhoursperday)forfivedayseachweek.
3.1 Drop Operations Dustcanbegeneratedeachtimeamaterialistransferredfromonelocationtoanothervia“dropping”operations.AP42Section13.2.4providesthefollowingequationtoestimatetheseemissions:
0.0032 5
.
2
.
wherethetermsare:
E Dustemissionperunitofmaterialhandled(lb/ton); k Particlesizemultiplier(1fortotaldust,0.35forPM10,and0.053forPM2.5); U Meanwindspeed(mph);and M Moisturecontentofthebulkmaterial(%).
Fivedropoperationsareassumedtooccuracrosstheconceptualbulkmaterialstorageandprocessingfacility:
Duringtheunloadingofincominghaultrucks;
Duringtheloadingofanarticulatedtruckbythefront‐endloader;and
Atthreepointsonaconveyorsystem(conveyorloading,anintermediatetransferpoint,andtheloadingofoutgoingrailcarsorbarges).
Aprocessingrateof2,000tonsperdayisassumedforeachdropoperationundertheassumptionofquasi‐steady‐stateoperation(equalmaterialinflowsandoutflows).Theprocessingrateisassumedtobedistributedevenlyoverfacilityoperatinghours.
Section 3 Emission Calculations
3‐2
3.2 Travel on the Surface of the Pile
Dustcanbegeneratedwhenoff‐roadvehiclestraveldirectlyacrossthesurfaceofthebulkmaterialstoragepile.AP42Section13.2.2providesthefollowingequationtoestimatetheseemissions:
12 3
wherethetermsare:
E Dustemissionpervehiclemiletraveled(lb/VMT); s Siltcontentofthebulkmaterial(%);
k Particlesizemultiplierforindustrialroads(4.9lb/VMTfortotaldust,1.5lb/VMTforPM10,and0.15lb/VMTforPM2.5);
a Particlesizedependentconstant(0.7fortotaldust,0.9forPM10,and0.9forPM2.5); b Empiricalconstantequalto0.45;and W Averageweightofthevehiclestravelingonthesurface(tons).Siltcontentisspecifictothebulkmaterial(seeTable2‐1).Twovehiclesareassumedtotravelonthestorageandprocessingpile:
afront‐endloaderwithatareweightof14.5tonsandbucketcapacityof6.5cubicfeet;and
anarticulatedtruckwithatareweightof30tonsandcarryingcapacityof40tons.
Eachvehicleisassumedtoloadorcarry2,000ton/dayofbulkmaterial.Thearticulatedtruckisassumedtomaketripsacrossthepile,traversingatotalof8.9milesperday.Thefront‐endloaderisassumedtotravelhalfofthisdistance(4.45milesperday).Theaveragevehicleweightof38.9‐40.1tonsisestimatedbyweightingtheaverageloadedandunloadedweightsofthevehiclesbytheassumedtraveldistances(thevaluedependstoasmallextentonthebulkdensityofthematerial).
3.3 Paved Roads Dustcanalsobegeneratedbyon‐roadvehiclesthatresuspendsiltedmaterialfrompavedroadways.AP42Section13.2.1providesthefollowingequationtoestimatetheseemissions:
. .
wherethetermsare:
E Dustemissionpervehiclemiletraveled(lb/VMT);k Particlesizemultiplier(0.011lb/VMTfortotaldust,0.0022lb/VMTforPM10,and
0.00054lb/VMTforPM2.5); sL Roadsurfacesiltloading(g/m2);and W Averageweightofthevehiclestravelingtheroad(tons).
Thesiltloadinginthiscaseisnotspecificallygermanetothebulkmaterial,butratherreflectsthedegreeoffinedustcoveringtheroadduetoallsources.Amid‐rangesLvalueof70g/m2isselectedfromvaluesdocumentedinAP42Table13.2.1‐3,asdevelopedfrommeasurementsinthesandandgravelprocessingindustry.Anaveragevehicleweightof40tonsisassignedtoWastheaverageloadedandunloadedweightofahaultruckwithatareweightof30tonscarrying20tonsofbulk
Section 3 Emission Calculations
3‐3
materialtothestorageandprocessingfacility.Theone‐waydistanceoftravelassumedbyahaultruckis100feetfromthegatetothehaulroadplus369feetalongtheoutsideofthematerialpile(onequarterofthepilecircumference).Allowingfordoublethedistancetogoinandoutofthefacilityandthe100trucksnecessarytodeliverbulkmaterial,haultrucksareassumedtotravelatotalof17.8vehiclemileseachdayoffacilityoperation.
3.4 Bulldozing and Grading Bulldozersarelikelytobeusedtomovematerialsshortdistances,suchasfromthedumpareasofhaultruckstowardthestoragepileorworkinglimitedareasofthepile.Gradersarelikelytobeusedtomaintainthegeneralshapeoftheentirepile.Abulldozerandgraderareassumedtoeachoperate50%ofthetimeattheconceptualbulkmaterialfacility.AP42Section11.9(Table11.9‐1)providesthefollowingequationsforestimatingdustemissionsduringthecourseoftheiroperations.Forthebulldozer,theemissionfactorsare:
Totaldust.
.
PM.
.
PM . .
.
.
wherethetermsare:
EB Dustemissionpertime(lb/hr); Empiricalconstantof78.4lb/hr(petroleumcokeandcoal)or5.7lb/hr(Mesabaore
andslag); Empiricalconstantof18.6lb/hr(petroleumcokeandcoal)or1.0lb/hr(Mesabaore
andslag); s Siltcontentofthebulkmaterial(%); M Moisturecontentofthebulkmaterial(%); k10 PM10particlesizemultiplierequalto0.75;and
k2.5 PM2.5particlesizemultiplierequalto0.022(petroleumcokeandcoal)or0.105(Mesabaoreandslag).
Emissionsfromgradingoperationsareestimatedas:
wherethetermsare:
EG Dustemissionpertime(lb/VMT); Empiricalconstantof0.051lb/VMTforPM10and0.040lb/VMTfortotaldustand
PM2.5; Empiricalconstantof2forPM10and2.5fortotaldustandPM2.5; k Particlesizemultiplierequalto1(totaldust),0.6(PM10),or0.031(PM2.5); S Averagespeedofthegrader(mph).
TheaverageAP42defaultmedianvalueof7.1mphisassumedfortheaveragevehiclespeedS.Atthisspeed,thegraderwilltravel3.55milesonthestoragepileeachhourifutilizedhalfthetime.
Section 3 Emission Calculations
3‐4
3.5 Wind Erosion from Stockpiles Windsofsufficientstrengthcancausedusttoblowoffofstoragepiles,especiallyifthematerialisfineanddry.AP42Section13.2.5providesthefollowingequationforestimatingdustemissionsduetowinderosionfromstockpiles:
58 ∗ ∗ 25 ∗ ∗
wherethetermsare:
P Dustemissionperunitarea(g/m2);
k Particlesizemultiplier(1fortotaldust,0.5forPM10,and0.075forPM2.5); u* Frictionvelocity(m/s);and ut* Thresholdfrictionvelocity(m/s).
Theequationforfrictionvelocityappliesonlywhentheatmosphericfrictionvelocityexceedsthethresholdfrictionvelocity.Additionally,winderosioneventstypicallyoccurunderdryconditionsoverapilethathasrecentlyexperiencedsurfacedisturbance.Oncefinematerialshaveblownoffthesurface,thelayermustbereplenishedbeforethenextwinderosioneventcanoccur.
Twocalculationsareperformedtoestimatethepotentialmagnitudeofemissionsduetowinderosionfromstockpiles.First,aworst‐caseassumptionismadethatonewinderosioneventcouldoccureachday(providedthefrictionvelocityexceedsthethresholdforatleastonehourduringtheday).Suchasituationmightoccurduringperiodsofextendeddrynesswhilethestoragepileremainsactiveandthesurfaceisroutinelyreplenished.Second,theassumptionismadethattherecouldbeonaverageonewinderosioneventeachmonth.Thedailyandmonthlywinderosionmodelsarethusdesignedtotestthesensitivityofthewinderosionalgorithms.
HourlyestimatesofthefrictionvelocityareavailablefromtheAERMETpreprocessingprogram,whichestimatesu*valuesinthecourseofpreparingmeteorologicaldataforusebytheAERMODdispersionmodel.Thethresholdfrictionvelocityut*dependsontheparticlesizecharacteristicsofthebulkmaterial.AP42Table13.2.5‐1providesdatafromafieldprocedureforestimatingut*.Acurve‐fitofthedata(R2=0.9995)yieldstheequationforut*(incm/s):
∗ 64.43 .
whereOisthemidpointopeningsize(inmm)ofthesievesthatindicatethestatisticalmodeofanempirically‐derivedgrainsizedistribution(followingthemethoddescribedinAP42Section13.2.5).Estimatesofut*forthefourbulkmaterialsexaminedare:
47cm/sforpetroleumcoke,basedonanaverageestimatederivedfromgrainsizeanalysesoftwosamples(AppendixA);
54cm/sto112cm/sforcoal,basedonspecificvaluesreportedinAP42section13.2.5;
187cm/sforMesabaore,basedondatafromareportedgrainsizeanalysisparticlesizedistribution(http://s3.amazonaws.com/zanran_storage/www.isamill.com/ContentPages/2534118165.pdf#page=8);and
61cm/sforslag,basedontheresultsofagrainsizeanalysis(AppendixB).
Section 3 Emission Calculations
3‐5
Overeachdailyperiod,theequationtopredictevent‐basedwinderosionisappliedtothehourofthedaywiththehighesthourlyfrictionvelocity.Inaddition,frictionvelocityestimatesfromthemeteorologicaldataarereducedbyafactorof0.9toaccountforreducedwindspeedsthatwouldbeexpectedtooccuroverastoragepileasitactsasapartialobstructiontosurfacewinds(asdescribedinAP42Section13.2.4).
3.6 Fugitive Dust Emission Estimates Theequationsforfugitivedustemissionsfromthevarioussourceswereimplementedinaspreadsheetinconjunctionwithhourlymeteorologicaldataforthe2008calendaryear.Emissionestimateswerederivedfortotalsuspendedparticulate(TSP,ortotaldust)anditssubcomponentsPM10andPM2.5.Summariesoftheannualemissiontotals,intons/year,areprovidedinTable3‐1(TSP),Table3‐2(PM10),andTable3‐3(PM2.5).
Thecompiledemissionestimatesreflectthenatureofthedependenciesoftheunderlyingfactorsthataffectemissions.Emissionestimatesforthepavedroadandgradingsourcesarethesameforallfourmaterialsastherearenodependenciesonbulkmaterialpropertiesintheconstitutivemodelequations.Petroleumcoke,duetoitshighsiltcontent,generatesthehighestemissionestimatesforoff‐roadvehiclestravelingonthepilesurface,bulldozing,andwinderosionfromstockpiles.Mesabaoreproducesthehighestemissionestimatesfordroppingoperations(materialhandling)becauseofitslowmoisturecontent.1Stockpilewinderosionestimatesaregreatestforpetroleumcoke,andlowest(zero)forMesabaore(forwhichthethresholdfrictionvelocityisneverexceededinthehourlymeteorologicaldata).Stockpilewinderosionestimatesforthemonthlyeventmodelareasubstantialfractionofthoseofthedailyeventmodel,reflectiveofthenatureoftheunderlyingnon‐linearmodelequationthatpredictsveryhighemissionsunderelevatedwindconditions.
Totalfugitivedustemissionsarehighestforthepetroleumcokematerial,butcanbesubstantial(oftheorderof100tons/yearormore)forallmaterials.Thegenericassumptionsregardingfacilitysize,materialhandlingpractices,andequipmentconfigurationandutilizationcanbeexpectedtobedifferentinpracticeatactualfacilities,andfacility‐specificassessmentsmaybeusefulingeneratingmoreaccurateestimatesofemissions.
Thefugitiveduststudydoesnotexplicitlyconsiderdustcontrolmeasuresinordertohighlightprocessescapableofproducingdustemissions.Mostfugitivedustemissionsareamenabletocontrol.Forexample,pavedroademissionscanbereducedthroughstreetsweepingandtargetedapplicationofwater.Manyestimatesarealsomadewithconservativeassumptionsdesignedtooverestimatelikelyemissions(suchasthepremisethatdryconditionswillpersistforlongperiodsoftime).
Therearealsouncertaintiesinherenttotheestimationoffugitivedustemissions.Thefugitivedustemissionestimatesmustthereforebeinterpretedwithcaution.SomesenseofthereliabilityofthemethodsisprovidedintheAP42sectionsfromwhichthepredictiveequationsaretaken,andreadersareencouragedtoreviewtheU.S.EPA’sdescriptions.
1ThemoisturecontentoftheMesabaore(astakenfromtheliterature)isnotablylowerthanthatfortheothermaterialsconsidered.Asmoisturecontentisexpressedasaweightpercentageandtheorehasahigherbulkdensity,thevolumefractionofwaterishigherthanrepresented(relativetoothermaterials).AstheAP42equationformaterialdroppingemissionsdoesnotaccountfordifferencesinbulkdensity,dropemissionestimatesfortheMesabaorematerialmaybeoverstatedrelativetotheothermaterials.
Section 3 Emission Calculations
3‐6
TheU.S.EPAAP42emissionfactorsarederivedfromempiricaldatatoidentifyandcapturethevariablesthatmostinfluencefugitivedustemissions.Manyoftheemissionfactorsdependonbulkmaterialproperties.Sincethesamehandlingassumptionsareusedtoevaluateeachmaterial,comparisonsbetweenmaterialsindicatetrendsandtendenciesbasedonthecharacteristicsofthematerialsthatcanbeinfluencedbyfacility‐specificcontrolandmitigationmeasures.
Section 3 Emission Calculations
3‐7
Table 3‐1 TSP Emission Summary
Petcoke Coal Mesaba Ore Slag
Silt (%) 21.2 4.6 3 0.55
Moisture (%) 6.7 4.8 1 8.69
Threshold Friction Velocity (u
*t, m/s)
0.47 0.54 to 1.12 1.88 0.62
Bulk Density (lb/ft3) 50 50 135 60
Total Suspended Particulate (TSP) Emissions (tons/year)
Drop operations 2.2 3.6 32.0 1.6
Travel on Pile Surface 20.2 6.9 5.2 1.6
Paved Roads 52.5 52.5 52.5 52.5
Bulldozing Material 168.8 41.6 13.9 0.1
Grading Material 24.9 24.9 24.9 24.9
Wind erosion from stockpiles (daily)
57.9 0.8 to 41.5 0 27.6
Wind erosion from stockpiles (monthly)
11.2 0.8 to 9.7 0 8.0
Total (daily wind erosion) 326 130 to 171 129 108
Total (once per month wind erosion)
280 130 to 139 129 89
Percentage hours greater than friction velocity threshold
37% 0.6% to 26% 0% 18%
Section 3 Emission Calculations
3‐8
Table 3‐2 PM10 Emission Summary
Petcoke Coal Mesaba Ore Slag
Silt (%) 21.2 4.6 3 0.55
Moisture (%) 6.7 4.8 1 8.7
Threshold Friction Velocity (u
*t, m/s)
0.47 0.54 to 1.12 1.88 0.62
Bulk Density (lb/ft3) 50 50 135 60
PM10 Emissions (tons/year)
Drop operations 0.8 1.2 11.20 0.5
Travel on Pile Surface 6.9 1.7 1.2 0.3
Paved Roads 10.5 10.5 10.5 10.5
Bulldozing Material 62.1 10.0 2.5 0.01
Grading Material 7.2 7.2 7.2 7.2
Wind erosion from stockpiles (daily)
29.0 0.4 to 20.8 0 13.8
Wind erosion from stockpiles (monthly)
5.6 0.4 to 4.8 0 4.0
Total (daily wind erosion) 116 31 to 51 33 32
Total (once per month wind erosion)
93 31 to 35 33 22
Percentage hours greater than friction velocity threshold
37% 0.6% to 26% 0% 18%
Section 3 Emission Calculations
3‐9
Table 3‐3 PM2.5 Emission Summary
Petcoke Coal Mesaba Ore Slag
Silt (%) 21.2 4.6 3 0.55
Moisture (%) 6.7 4.8 1 8.69
Threshold Friction Velocity (u
*t, m/s)
0.47 0.54 to 1.12 1.88 0.62
Bulk Density (lb/ft3) 50 50 135 60
PM2.5 Emissions (tons/year)
Drop operations 0.1 0.2 1.7 0.08
Travel on Pile Surface 0.7 0.2 0.1 0.03
Paved Roads 2.6 2.6 2.6 2.6
Bulldozing Material 3.7 0.9 1.5 0.01
Grading Material 0.8 0.8 0.8 0.8
Wind erosion from stockpiles (daily)
4.3 0.1 to 3.1 0 2.1
Wind erosion from stockpiles (monthly)
0.8 0.1 to 0.7 0 0.6
Total (daily wind erosion) 12 5 to 8 7 6
Total (once per month wind erosion)
9 5 to 5 7 4
Percentage hours greater than friction velocity threshold
37% 0.6% to 26% 0% 18%
4‐1
Section 4
Dispersion Modeling
4.1 AERMOD References/Version DispersionmodelingwasconductedusingthelatestversionoftheU.S.EPA‐approvedAERMODdispersionmodelingsystem(AERMODVersion13350)andtheLakesEnvironmentalAERMODViewgraphicuserinterfaceversion8.5.0.AERMODisacomputer‐basedmathematicaldispersionmodelthatcanpredictambientconcentrationsofpollutantsthatresultfromreleasestotheatmosphere.AERMODalgorithmsassumethat:
Asource’splumeissteady‐state,
TheverticalandhorizontalconcentrationdistributionsfitaGaussiandistributioninthestableboundarylayer(SBL),and
Fortheconvectiveboundarylayer(CBL),thehorizontalconcentrationdistributionisGaussianandverticaldistributionfitsabi‐Gaussianprobabilitydensityfunction.
AERMODuseshour‐by‐hourmeteorologicaldatatopredictthepatternsofambientconcentrationsofpollutantsovertime.Matchedwithhour‐by‐hourestimatesoffugitivedustemissions,AERMODiscapableofpredictingbothshort‐termandlong‐termestimatesoftheimpactsofbulkmaterialprocessingandstoragefacilitiesonambientairquality.
4.2 Modeling Setup 4.2.1 Terrain Digitalelevationmodeldatawasnotrequiredbecausetheterrainsurroundingthesourcewasassumedtobeflat.
4.2.2 Receptor Grid Anon‐uniformpolarreceptorgridcenteredonthesourceconsistsof36radials(oneevery10degrees)thatintersectsixreceptorringsatdistancesof115,140,170,220,280and350metersfromthesource.Thegridconsistsof216receptorseachassumedtobeatground‐level(0.0metershigh).
Fencelinereceptorswerealsoincludedinthemodelandlocatedevery10metersalongthevirtualpropertyboundaryforatotalof36receptors.ThereceptorgridisshowninFigure4.1.
4.2.3 Meteorological Data and Land Use AsdescribedinSection3.4,hourlysurfacemeteorologicaldataforMidwayAirport(StationID72534,baseelevation607feetand10meteranemometerheight),Chicago,IL,andupperairdatafromLincoln,IL(StationID4833)for2008wereobtainedfromathirdpartyvendor.ThedataaspurchasedhaveundergonethequalityassuranceprocessrequiredbyEPAtoidentifyandfillinmissingdata.ThesurfaceandupperairmeteorologicaldatawerepreparedforuseinAERMODusingtheAERMETmeteorologicaldatapreprocessorandLakesEnvironmentalAERMETViewGraphicUser
Section 4 Dispersion Modeling
4‐2
InterfaceVersion8.50.Processingofthesurfacefileindicatedmorethan99percentdataavailabilityoutof8,711recordsused.
Surfaceparameters(albedo,Bowenratioandsurfaceroughness)weredeterminedusingtheAERSURFACEpreprocessorandsurfacedatafromtheNationalLandCoverDatabaseforthestateofIllinoisbasedontheNorthAmericanDatum83.AERSURFACEevaluated30degreesectorsoverafullcircletogenerate12setsofthethreeparameters(oneforeachsector).
ThemeteorologicaldataoutputfromAERMETissummarizedinthewindroseshowninFigure4.2.Windsmostcommonlyoriginatefromthesouth‐southwestandwesterlydirectionsingeneral,thoughwindsoriginatefromalldirectionsforatleastsomepercentageoftime.Theaveragewindspeedoverthe8,711availablemeasurements2forcalendaryear2008was9.7mph(treatingcalmconditionsas0).Hourlyaveragewindsexceeded15mph13%ofthetimeand20mph4%ofthetime.
2 Wind speeds were missing from 73 hours during the 2008 calendar year. These hours are assigned a code of 999 by AERMET and are ignored by AERMOD in dispersion modeling, as are 500 additional hours that are reported as calm conditions (with 0 wind speed). For the purpose of estimating annual emission totals, hours with missing wind speeds were assigned the average values of wind speeds of the previous and subsequent hours, and calm conditions were assigned a wind speed of 0.25 m/s (half of the lowest measureable wind speed).
Section 4 Dispersion Modeling
4‐3
Figure 4‐1 Polar and Fenceline Receptor Grid
Section 4 Dispersion Modeling
4‐4
Figure 4‐2 Windrose for Chicago Midway Airport 2008 Surface Observations
Section 4 Dispersion Modeling
4‐5
4.2.4 Pollutants and Averaging Times Modelingwasconductedforemissionsofparticulatematterlessthan10micrometersaerodynamicdiameter(PM10)andparticulatematterlessthan2.5micronaerodynamicdiameter(PM2.5)frompetcokeandcoalmaterialhandlingoperations.ThesourcesthatcomprisethematerialhandlingoperationarediscussedinSection4.3.ModelingofPM10wasconductedfora24‐houraveragingtimeforbothpetcokeandcoalmaterialhandlingoperationsinrecognitionofPM10’sNationalAmbientAirQualityStandard(NAAQS).Similarly,modelingofPM2.5wasconductedforannualand24‐houraveragingperiodsforpetcokeandcoalhandlingoperationsinrecognitionofPM2.5’sNAAQSs.Inaddition,1‐houraveragePM10modelingwasconductedtoexaminespecificimpactsofthewinderosionfromstockpilessourceforbothpetcokeandcoal.
Particulatematterdepositionusingparticlesizedatawasnotconsideredforanymodelingruns,resultinginnoremovalofmassfromtheplume,andhencelikelymoreconservativepredictionsofimpactstoambientair.
4.3 Emission Sources 4.3.1 Source Types AERMODhasthecapabilityofmodelingvarioustypesoffugitivedustsourcesthatincludeareasources,volumesources,andlinesourcesaslinevolumesources.3Areasourcesareappropriatetomodelgroundlevelreleaseswithnoplumerisesuchasstoragepiles.Volumesourcesapplytoconveyorsandothersourceswhereaplumewouldbegeneratedfromadrop‐likeoperation.Linesourcesincluderoadways.AERMODcanbeusedtomodellinesourcesasaseriesofadjacentvolumesources.
Areasourceswereusedformodelinganyvariationsinareatothestoragepilesurfacesuchasforbulldozeroperationsinaspecificarea.Areasourceemissionratesaresimplytheequipmentemissionrateinmasspertimedividedbythetotalsourcearea.Forshort‐termmodelingapplicationswhereabulldozerwouldbeworkinginaspecificareaofthestoragepile,itsemissionratewouldbedistributedoverthatlocalizedarea,usuallyafractionofthetotalarea.Forlong‐termmodelingapplicationsoverayearormorewhereabulldozerwouldbeworkingovertheentirefaceofthestoragepile,theemissionratewouldappropriatelybedistributedbythetotalstoragepileworkingfacearea.Thereleaseheightsforareasourceswereassumedtobezero(ground‐level).
Forthisevaluation,roadways,bothpavedandunpaved(trafficoverthebulkmaterialsurface),weremodeledasadjacentvolumesourcesinaccordancewithEPAguidance.4Thetopofthesource’splumeheightisgivenas1.7timesthevehicleheightandthesource’splumereleaseheightiscalculatedas½ofthetopoftheplumeheight.Therecommendedplumewidthiscalculatedasthevehiclewidthplussixmetersforasinglelaneroad,whichistheapproachusedforthismodelingevaluation.Theinitialverticalplumesizeiscalculatedastheplumeheightdividedbyafactorof2.15,andtheinitialhorizontalplumeheightiscalculatedastheplumewidthdividedby2.15.
3 AERMOD as issued by EPA does not contain algorithms for line sources. The Lakes Environmental interface to AERMOD allows specification of line sources that are translated into series of adjacent volume sources. 4 Volume II of the U.S. EPA User’s Guide for the Industrial Source Complex (ISC3) Dispersion Models (U.S. EPA, 1992).
Section 4 Dispersion Modeling
4‐6
4.3.2 Modeling Approach Themodelingapproachconsideredagenericbulkmaterialprocessingfacilitythatincludesvariousmaterialhandlingoperationsandstorage.Figure2.1showstheconceptualbulkmaterialstoragefacilitywiththeprimefeaturebeingalargestoragepileshapedasaconicalfrustum.Thematerialhandlingoperationswouldincludetypicalheavyequipmentactivitysuchas:
Resupplyofmaterialtothestoragepileviaon‐roadhaultruckactivity;
Preparationandmaintenanceofthestoragepilewithabulldozerandgrader;
Materialtransportwithintheconfinesofthesiteandoverthesurfaceofthestoragepileusingafront‐endloaderandarticulateddumptruck;
Conveyanceofmaterialforloadingoperationswithamulti‐segmentconveyorsystem.
Allofthisequipmentmightnotbeusedateveryfacility,butthegoalofthisstudyistoconsiderallpossiblemeansbywhichfugitivedustemissionsmightarise.Withtheexceptionofthestoragepileitself,theemissionsourcesareprimarilydefinedbytheuseofheavyequipmentandtrucksatspecificareaswithinconfinesof‐andaround‐thesiteboundary.Thesourcesandprimaryareasofoperationusedasinputstothemodelareasfollows:
Winderosionofthewholestoragepilecouldoccurannuallyasthesurfaceisintermittentlydisturbed.Thestoragepilewasmodeledasanareasourcesubjecttowinderosion;thereforetheemissionratesinputtothemodelwerederivedfromwinderosionequationsdescribedinSection3.5.
Abulldozerandgraderwouldlikelyoperateinanominalrectangularareatoconstantlyreshapethestoragepileasmaterialisaddedandremoved.Emissionsfromtheseactivitieswouldmainlybethedustfromthebulldozertracksandthegraderblade.Thissourcewasmodeledasrectangularareasourcelocatedontheeastsideofthefacilityforshort‐term(daily)operations,butemissionsweredistributedoverthefullstoragepileareaforlong‐termprojections.TheemissionratesinputtothemodelwerederivedfromequationsdescribedinSection3.4.
Haultrucksbringingnewmaterialtothefacilityfordepositandprocessingareassumedtotravelonthepavedperimeterroadanddumpmaterialonthenorthsideofthestoragepile.Thesourcesfromthisactivitywouldbedustemissionsmobilizedfromthepavementbytrucktiresandthedumpingemissionswherethematerialisunloadedatthenorthsideofthepile.Thepavedroadwayisassumedtooriginatefromaneastentranceandextendalongtheedgeofthestoragepiletothenorthwherematerialunloadingwouldoccur.Emissionswouldincludetheroundtripintoandoutofthesite.Thetrucktripemissionsweremodeledasalinevolumesource,whichisaseriesofnearlyequalvolumesourcesfromthebeginningoftheroutetotheend.TheemissionratesfortrucktraveloverpavedroadthatwereinputtothemodelwerederivedfromequationsdescribedinSection3.3.Theunloadingofthenewmaterialatthenorthsideofstoragepilewasmodeledasasinglevolumesource.TheemissionratesfortruckunloadingwerederivedfromdropoperationequationsdescribedinSection3.1.
Anarticulateddumptruckandfront‐endloaderoperatingonthefaceofthestoragepilewouldtravelalongamakeshiftunpavedroadonthesurfaceofthestoragepilebetweenthelocation
Section 4 Dispersion Modeling
4‐7
wherethehaultrucksunloadandthecenterofthepile.Thefrontendloaderwouldfillthearticulateddumptruckatthenorthsideofthesiteandtheywouldtraveltogethertothecenterofthesitewherethedumptruckwouldunloaditsmaterialandthefront‐endloaderwouldloadmaterialontotheconveyorinlethopper.TheloadingofthearticulateddumptruckwasmodeledasasinglevolumesourceusingemissionratesderivedfromthedropequationsdescribedinSection3.1.Travel‐relatedemissionsoftheloaderanddumptruckontheunpavedroad(bulkmaterialsurface)betweenthecenterofthepileandthenorthsideofthepileweremodeledusingemissionratesderivedfromunpavedroadequationsdescribedinSection3.2.Thepavedroadwastreatedasaseriesofnominallyequalvolumesources.ThearticulateddumptruckunloadingneartheconveyorwasmodeledasasinglevolumesourceusingemissionratesderivedfromthedropequationsdescribedinSection3.1.
Theconveyorwouldbecoveredexceptatthreepositionsinthesystem,theinlet,anintermediatesegmentchangeinconveyanceandtheoutletoftheconveyorsystem.Thetwopointswherefugitiveemissionswouldoccurwouldbeattheintermediatesegmentchangeandtheoutlet.Theoutletiswherebargeandtraincarloadingwouldoccur.TheconveyorsystemoutletandintermediatelocationsweremodeledassinglevolumesourcesusingemissionratesderivedfromthedropequationsdescribedinSection3.1.
Table4‐1summarizeseachoftheseactivitiesandhowtheyaredefinedformodelingpurposes.
4.4 PM10 (24‐hr) and PM2.5 (Annual, 24‐hr) Modeling Results Petcokeandcoalmaterialhandlingoperationsweremodeledforthemaximum24‐houraveragePM10concentrationsandthemaximumannual‐averageand24‐houraveragePM2.5concentrations.AERMODwassetuptoallowtheevaluationofindividualandgroupsoffugitiveemissionsources.Themodelingresultsarepresentedinthefollowingsections.
4.4.1 Petcoke Material Handling Modeling Results ThepetcokematerialhandlingmodelingresultsandcorrespondingfiguresthatgraphicallysummarizethemodelingresultsaredescribedinTable4‐2.EachmodelingscenarioisrepresentedbyacorrespondingfigurethatisdescribedinthetableandincludedinAppendixC.Figuresdepictingthepredictedimpactsofallsources(summedtogether)arealsoincludedinthissection.
AsShowninTable4‐2,predictedconcentrationsof24‐houraveragedPM10and24‐houraveragePM2.5greatlyexceedNationalAmbientAirQualityStandards(NAAQSs).Amongthesourcegroups,bulldozer/graderoperationsarepredictedtoresultinthemaximumincrementalconcentration(4,899µg/m3forPM10and317µg/m3forPM2.5,bothatthesamereceptor).Substantialimpactsarealsopredictedforthepavedandunpavedroadsources.Fortheannualaveragingperiod,thetotalpredictedconcentrationofPM2.5onlymodestlyexceededtheleveloftheNAAQS.Intermsofindividualsources,pavedroademissionsdominatethetotalpredictedannual‐averagePM2.5concentrationandthesource‐specificmaximumPM2.5concentrationof14µg/m3wouldoccuralongtheperimeterroad.ThisconcentrationexceedstheNAAQSof12µg/m3and(asexpectedforaground‐levelsource)thepredictedimpactsrapidlydropoffwithinafewmetersfurtherawayfromtheperimeterroad.
4‐8
Table 4‐1 Modeling Source Summary
Source Description/
Type ID
Applicable Modeling Averaging Period
Height
[m]
Diameter
[m]
SigmaY
[m]
SigmaZ
[m]
Length_X
[m] Configuration
Line Volume Height
[m]
PlumeWidth
[m]
Line Volume
Type
Wind Erosion from stockpiles/ AREA_CIRC
CAREA1 All averaging periods 0 71.5
2
Bull‐dozer/Grader operations over the entire storage pile surface/ AREA_CIRC
FAREA1 Annual Averaging period 2 71.5
2
Bull‐dozer/Grader/ AREA_POLY
PAREA1 Short term Averaging periods (24‐hour)
2
2
Paved Road Haul Trucks/ LINE_VOLUME
SLINE1 (HT000001 ‐HT000018)
All averaging periods
Adjacent 5.7 8.44 Surface Based
Unpaved Road Articulated Dump Truck & Front End Loader/ LINE_VOLUME
SLINE2 (L0000069 ‐ L0000075)
Short term Averaging periods (24‐hour)
Adjacent 5.18 9.05 Surface Based
Unpaved Road Articulated Dump Truck & Front End Loader/ AREA_CIRC
UAREA1
For the long‐term averaging period, the emissions were spread‐out over the entire area of the storage pile.
2 71.5
2
Conveyor Drop 1/ VOLUME
VOL1 All averaging periods 5
1.163 1.163 5.0009
Conveyor Drop 2/ VOLUME
VOL2 All averaging periods 5
1.163 1.163 5.0009
Conveyor Drop 3/ VOLUME
VOL3 All averaging periods 5
1.163 1.163 5.0009
On‐Road Haul Truck Dump/ VOLUME
VOL4 All averaging periods 2.438
0.567 0.567 2.4381
Articulated Dump Truck Loading/ VOLUME
VOL5 All averaging periods 3.048
0.425 0.567 1.8275
Note: A base elevation of zero was used for all sources; emission rates were not included because an hourly emission rate source file that has more than one emission rate per source was used for each run. Lake Environmental AERMOD View uses single abbreviated source IDs to represent multiple volume sources (SLINE1 and SLINE2). Because the temperature of the sources are nearly ambient, fugitive dust emission plumes are modeled as not being buoyant.
Section 4 Dispersion Modeling
4‐9
Table 4‐2 AERMOD Modeling Results Summary for Petcoke Material Handling
Material Pollutant Averaging
Period Source Group Figure
Maximum Predicted
Concentration (µg/m3)
Coordinates (meters)
X Y
Petcoke
PM10
24‐hour
(NAAQS = 150 µg/m3)
All 4.3, 4.3a
5297 70.71 84.26
Dozer 4.3b 4899 70.71 84.26
Drops 4.3c 69.6 ‐70.71 ‐84.26
Paved Roads 4.3d 450.3 110 0
Travel on Pile Surface
4.3e 276.7 37.62 103.37
Wind Erosionfrom Stockpiles
4.3f 9.6 103.4 37.6
PM2.5 24‐hour (NAAQS = 35 µg/m3)
All 4.4, 4.4a
390.5 70.71 84.26
Dozer 4.4b 317.5 70.71 84.26
Drops 4.4c 10.5 ‐70.71 ‐84.26
Paved Roads 4.4d 110.5 110 0
Travel on Pile Surface
4.4e 27.7 37.62 103.37
Wind Erosionfrom Stockpiles
4.4f 1.4 103.4 37.6
PM2.5
Annual
(NAAQS = 12 µg/m3)
All 4.5, 4.5a
21.4 108.3 19.1
Dozer 4.5b 6.1 84.26 70.71
Drops 4.5c 0.8 ‐70.71 ‐84.26
Paved Roads 4.5d 14.1 108.3 19.1
Travel on Pile Surface
4.5e 0.9 84.26 70.71
Wind Erosionfrom Stockpiles
4.5f 0.1 37.62 103.37
4.4.2 Coal Material Handling Modeling Results ThecoalmaterialhandlingmodelingresultsandcorrespondingfiguresthatgraphicallysummarizethemodelingresultsaredescribedinTable4‐3.EachmodelingscenarioisrepresentedbyacorrespondingfigurethatisdescribedinthetableandincludedinAppendixC.Figuresdepictingthepredictedimpactsofallsources(summedtogether)arealsoincludedinthissection.
Asshowninthetableandsimilartothemodelingresultsforpetcoke,AERMODpredictedforcoalmaterialhandlingoperationsthatforthe24‐houraveragingperiod,amongallthesourcegroups,bulldozer/graderoperationswouldresultinthemaximumconcentrationofbothPM10andPM2.5(atthesamereceptorineachcase).Predictedmaximumconcentrationsarelowerthanthoseforpetcoke(byasmuchasafactorof4,dependingonthespecificemissionsource),butstillsubstantiallylargerthanNAAQS.AERMODalsopredictedthatfortheannualaveragingperiod,pavedroademissionswoulddominatethetotalpredictedconcentration.
Section 4 Dispersion Modeling
4‐10
Table 4‐3 AERMOD Modeling Results Summary for Coal Material Handling
Material Pollutant Averaging
Period Source Group Figure
Maximum Predicted
Concentration (µg/m3)
Coordinates (meters)
X Y
Coal
PM10
24‐hour
(NAAQS = 150 µg/m3)
All 4.6, 4.6a
1509 70.71 84.26
Dozer 4.6b 1215 70.71 84.26
Drops 4.6c 111 ‐70.71 ‐84.26
Paved Roads 4.6d 450.3 110 0
Travel on Pile Surface
4.6e 70 37.62 103.37
Wind Erosionfrom Stockpiles
4.6f 8.4 103.37 37.62
PM2.5
24‐hour
(NAAQS = 35 µg/m3)
All 4.7, 4.7a
186 70.71 84.26
Dozer 4.7b 119.5 70.71 84.26
Drops 4.7c 16.8 ‐70.71 ‐84.26
Paved Roads 4.7d 110.5 110 0
Travel on Pile Surface
4.7e 7 37.62 103.37
Wind Erosionfrom Stockpiles
4.7f 1.26 103.37 37.62
PM2.5
Annual
(NAAQS = 12 µg/m3)
All 4.8, 4.8a
17.2 108.3 19.1
Dozer 4.8b 2.3 84.26 70.71
Drops 4.8c 1.3 ‐70.71 ‐84.26
Paved Roads 4.8d 14.1 108.3 19.1
Travel on Pile Surface
4.8e 0.2 84.26 70.71
Wind Erosionfrom Stockpiles
4.8f 0.08 37.62 103.37
4.4.3 Wind Erosion Modeling for the Petcoke and Coal Storage Piles ThespecificeffectsofwindoneachofapetcokeandcoalstoragepileweremodeledbyisolatingtheAERMODmodelingrunstoonlythePM10emissionratederivedfromthewinderosionfromstockpilesequations.Themodelingwasperformedfora1‐houraveragingperiod,correspondingtotheemissionalgorithmsthatassumethatmaterialblowsoffthepileduringthehourofthedaywiththehighestwindspeed.TheresultsaregraphicallyrepresentedinFigures4.9and4.10forpetcokeandcoaldust,respectivelyandareincludedinAppendixC.Thehighest1‐hourconcentrationsareoftheorderof200µg/m3,which,whenaveragedovera24‐hourperiod,wouldnotlikelyleadtoexceedanceofthePM10NAAQS.However,giventhehighwindsthataccompanythepredictedwinderosionevents,theamountofmaterialreleasedduringtheseeventscouldbesubstantialrelativetootheremissionsources.
Section 4 Dispersion Modeling
4‐11
Figure 4‐3 Highest 24‐Hour Average PM10 Concentration Predictions for Petroleum Coke (All Sources)
Section 4 Dispersion Modeling
4‐12
Figure 4‐4 Highest 24‐Hour Average PM2.5 Concentration Predictions for Petroleum Coke (All Sources)
Section 4 Dispersion Modeling
4‐13
Figure 4‐5 Highest Annual Average PM2.5 Concentration Predictions for Petroleum Coke (All Sources)
Section 4 Dispersion Modeling
4‐14
Figure 4‐6 Highest 24‐Hour Average PM10 Concentration Predictions for Coal (All Sources)
Section 4 Dispersion Modeling
4‐15
Figure 4‐7 Highest 24‐Hour Average PM2.5 Concentration Predictions for Coal (All Sources)
Section 4 Dispersion Modeling
4‐16
Figure 4‐8 Highest Annual Average PM2.5 Concentration Predictions for Coal (All Sources)
Section 4 Dispersion Modeling
4‐17
Figure 4‐9 1‐Hour Averaging Period PM10 Emissions Wind Erosion of a Petcoke Storage Pile
Figure 4‐10 1‐Hour Averaging Period PM10 Emission Rate Wind Erosion of a Coal Storage Pile
Section 4 Dispersion Modeling
4‐18
4.5 Interpretation of Model Predictions PredictionofincrementalPM10andPM2.5concentrationsgreaterthantheNAAQSlevelsdoesnotnecessarilymeanthatairqualitystandardswillinpracticebeexceededas(1)fugitivedustemissionfactorsmayoverpredictactualemissions,(2)facilitiesmaynotemployallofthesourcesconsidered,and/orinthemannerconsidered,and(3)therehasbeennoaccountingofpotentialmitigationeffortsdesignedtocurbdustemissions.However,giventhemagnitudeofincrementalconcentrationspredictedforsomeemissionsources,thepotentialexistsforNAAQSstobeexceeded,especiallyatlocationsclosetobulkmaterialprocessingandstoragefacilities.Predictedconcentrationsaregenerallypredictedtodecreaserapidlywithdistancefromthefacility,characteristicofthedispersionofemissionsfromaground‐levelsource.Basedonmodelingassumptions,theprocessesmostlikelytoaffectairqualityarebulldozing/gradingoperations,pavedroademissions,andunpavedroad(bulkmaterialsurface)emissions.Predictedimpactsfromthepavedroademissionsourcearethesameforpetroleumcokeandcoalbecausetheestimatesareindependentofmaterialproperties,dependingprincipallyontheamountoffinedustpresentontheroadsavailabletobemobilizedbyvehiculartraffic.TheAP42‐basedvalueforroadsiltloadingisbasedonolderdatacollectedfromindustrialfacilitiesandmaygreatlyoverestimatevaluesatfacilitiesthatemploystreetsweepersanddustsuppression(watering).Forthebulldozing/gradingandunpavedroad(bulkmaterialsurface)sources,modelingestimatesforthepetroleumcokematerialaresubstantiallylargerthanthoseforcoal,aresultofthemuchhighersiltcontentofthepetcokematerialthatleadstohigherpredictedemissions.Uncertaintyassociatedwiththeemissionsestimatesmaybesubstantial,asreflectedbylowemissionfactorratingsintheAP42database.
4.6 Comparison to Background Air Quality in Chicago Chicago,likemanyurbanareas,hasmanyemissionsourcesofparticulatematterthatcontributetosignificantbackgroundconcentrationsofPM2.5andPM10.Datafromthe2012IllinoisAirQualityReport(http://www.epa.state.il.us/air/air‐quality‐report/2012/air‐quality‐report‐2012.pdf)indicatebackgroundconcentrationsareclosetothelevelsoftheNationalAmbientAirQualityStandards(NAAQS).MonitoredannualaveragePM2.5concentrationsareoftheorderof12µg/m3,orapproximatelythesameastheallowableNAAQSof12µg/m3(Figure4‐11).Measured24‐houraveragePM2.5concentrationsreachashighas30µg/m3,orabout86%oftheNAAQSof35µg/m3(Figure4‐12).Thehighest24‐houraveragePM10concentrationof106µg/m3measuredin2012represents71%ofthe150µg/m3NAAQS(Figure4‐13).Inallcases(andparticularlyforPM2.5),incrementalparticulatematterconcentrationsduetoemissionsfrombulkmaterialprocessingandstoragefacilitiesmustbesmallinordertoavoidlocalizedexceedancesoftheNAAQS.ThemodelpredictionsofTable4‐2and4‐3,however,indicatethepotentialimpactsofbulkmaterialfacilitiesmaybesubstantial.GiventhelevelsofpotentialimpactsandthelimitedgapbetweenbackgroundlevelsandNAAQS,itmaybedifficultforbulkmaterialfacilitiestoavoidlocalizedexceedancesofairqualitystandardsevenifdiligentmitigationmeasuresareemployed.
Section 4 Dispersion Modeling
4‐19
Figure 4‐11 Annual Average PM2.5 Concentrations at Monitoring Locations in Chicago
Figure 4‐12 24‐Hour Average PM2.5 Concentrations at Monitoring Locations in Chicago
0
10
20
30
40
Washington High School Mayfair Pump Station Springfield Pump Station Com Ed Maintenance
Co
nce
ntr
atio
n (
µg/
m3)
PM2.5 24‐Hour 2010‐12 Design Value ConcentrationsChicago Air Quality Monitoring Stations
National Ambient Air Quality Standard = 35 µg/m3
Section 4 Dispersion Modeling
4‐20
Figure 4‐13 24‐Hour Average PM10 Concentrations at Monitoring Locations in Chicago
0
20
40
60
80
100
120
140
160
Highest 2nd Highest 3rd Highest
Co
nce
ntr
atio
n (
µg/
m3)
Highest 24‐Hour Concentrations of PM10 in 2012Washington High School Monitoring Station
National Ambient Air Quality Standard = 150 µg/m3
5‐1
Section 5
Conclusions
CalculationsindicatethatfugitivedustemissionsfrombulkmaterialstorageandhandlingfacilitiesmaybesubstantialenoughtoleadtolocalizedexceedancesoftheNationalAmbientAirQualityStandardsforPM10andPM2.5.Thestudydoesnotaccountforuseofmitigationmethodstoreducefugitivedustemissions.Varyingcharacteristicsofbulkmaterialsarelikelytoleadtodifferencesinemissionsamongfacilities.Inparticular,modelequationspredictgreateremissionsformaterialswithhighsiltcontents.Thus,ofthematerialsexaminedinthisstudy,thehighestoverallemissionsandairqualityimpactsarepredictedforthepetroleumcokematerial.
Thevariouscategoriesofemissionsourcesarepredictedtohavedifferinglevelsofimpactstoambientair.Thefollowingarepredictedimpactsfromvarioussourceshandlingpetcokeandcoal:
Dropoperationsfromconveyorpointsandbulkmaterialtransfersarepredictedtoleadtomodestincreasesinambientdustconcentrations.Thefencelineincrementsof111µg/m3for24‐houraveragePM10and16.8µg/m3for24‐houraveragePM2.5predictedforcoal(Table4‐3),whencombinedwithbackground,couldcontributetoexceedancesofNationalAmbientAirQualityStandards(NAAQSs).
Travelonthesurfaceofthestoragepilebyoff‐roadconstructionvehicles(anarticulatedtruckandafront‐endloader)arepredictedtoresultinaworst‐caseincremental24‐houraveragePM10fencelineconcentrationofpetcokeof277µg/m3thatbyitselfexceedstheNAAQS.
Haultruckstravelingonthepavedaccessroadarepredictedtocausehighlocalizedimpacts,withtheworst‐caseincremental24‐houraveragefencelineconcentrationsof450µg/m3(PM10)and110µg/m3(PM2.5)eachaboutthreetimestheleveloftheNAAQS.ThemodeledannualaveragePM2.5concentrationof14µg/m3isalsopredictedtoexceedtheNAAQS.Thedustlevelontheindustrialroads,akeyparameterusedinthecalculations,maybeoverestimatedforlocalroadsandcurrentpractices.Locationofthehaulroadadjacenttothefencelinealsocontributestotheelevatedimpacts.
Bulldozingoperationsareresponsibleforthehighestincremental24‐houraveragefencelineconcentrationsof4,899µg/m3(PM10)and317µg/m3(PM2.5)forthepetcokematerial(Table4‐2),eachapproximatelyanorderofmagnitudegreaterthantheNAAQSs,Aworst‐caseincrementof6µg/m3totheannualPM2.5concentration(Table4‐2)isroughlyhalftheleveloftheNAAQS.
Winderosionofthestoragepilesurfaceleadstothelowestpredictedincrementstoambientdustconcentrations(Table4‐2andTable4‐3).Thisinpartresultsfromtheepisodicnatureofwinderosion,whichisassumedtooccuronlyonceperdayduringthehourofthehighest(andmostdispersive)windspeed.Figure4‐9andFigure4‐10,whichdepictpotential1‐houraveragedustconcentrationsduetostoragepilewinderosion,indicatesubstantialshort‐termimpactsarepossible,especiallyincasesinwhichmaterialisblownoffthepileinstantaneously.
Section 5 Conclusions
5‐2
Theestimatesmayreflectconservativeassumptionsregardingvehicleutilizationandfacility‐relatedactivities.Giventhestudy’sinherentuncertaintiesandassumptions,thestudyresultsarebestinterpretedasindicatingapotentialforbulkmaterialprocessingandstoragefacilitiestoadverselyaffectairquality.Useofbestmanagementpracticescanmitigatemostfugitivedustimpacts,butpotentiallocalizedexceedancesofNationalAmbientAirQualityStandardsmaystillresult,andairqualitymonitoringmaybeausefultooltobetterevaluatefacilityimpacts.
A‐1
Appendix A
Petroleum Coke Data
1 of 8
February 25, 2014Date:STAT Analysis Corporation
Project: PPT DOCClient: CDM Smith Inc.
Lab Order: 13120303Work Order Sample Summary
Lab Sample ID Client Sample ID Collection DateTag Number Date Received
13120303-001A PPTDOC-KCBX-South 12/13/2013 10:00:00 AM 12/13/201313120303-002A PPTDOC-KCBX-North 12/13/2013 10:15:00 AM 12/13/2013
2 of 8
Project: PPT DOC
Client Sample ID: PPTDOC-KCBX-South
Collection Date: 12/13/2013 10:00:00 AMMatrix: Solid
Analyses Result Qualifier Units Date AnalyzedRL
Client: CDM Smith Inc.Lab Order: 13120303
Lab ID: 13120303-001A
DF
Print Date: February 25, 2014
Tag Number:
STAT Analysis Corporation2242 West Harrison St., Suite 200, Chicago, IL 60612-3766Tel: (312) 733-0551 Fax: (312) 733-2386 [email protected]
Report Date: February 25, 2014
Accreditation Numbers: IEPA ELAP 100445; ORELAP IL300001; AIHA 101160; NVLAP LabCode 101202-
Grain Size D422 Analyst: SUBPrep Date:Clay Sized Particles * 1/24/2014%17.1Gravel Sized Particles * 1/24/2014%32.0Sand Sized Particles * 1/24/2014%43.6Silt Sized Particles * 1/24/2014%7.3
Qualifiers: J - Analyte detected below quantitation limitsB - Analyte detected in the associated Method Blank
S - Spike Recovery outside accepted recovery limitsR - RPD outside accepted recovery limits
ND - Not Detected at the Reporting Limit
E - Value above quantitation range* - Non-accredited parameter H - Holding time exceededHT - Sample received past holding time
RL - Reporting / Quantitation Limit for the analysis
3 of 8
D60 (mm) D30 (mm) D10 (mm) Cu Cc
2.7 0.2
SAMPLE ID: PPTDOC-KCBX-South
43.6 7.3 17.1
% + 3" % Gravel % Sand % Silt
GRAIN SIZE ANALYSIS (ASTM D422)
System:
Black coarse to fine sand-sized particles, and coarse to fine gravel-sized particles, some fines, moist
% Clay
Soil Classification:
100.0
3/4" 100.0
58.0
3/8" 100.0
37.2
#4
32.1
#200 24.4
#40
Percent Passing
#20 47.8
#60
Visual Soil Description:
0.0 32.0
#140 28.0
#10
Sieve Size
1"
68.0
0
10
20
30
40
50
60
70
80
90
100
0.0010.0100.1001.00010.000100.0001000.000
PE
RC
EN
T F
INE
R
GRAIN SIZE - mm
1.5
"1
.0"
3/4
"
3/8
"
No
. 1
0
No
. 4
0
No
. 1
00
No
. 2
00
No
. 4
4 of 8
Project: PPT DOC
Client Sample ID: PPTDOC-KCBX-North
Collection Date: 12/13/2013 10:15:00 AMMatrix: Solid
Analyses Result Qualifier Units Date AnalyzedRL
Client: CDM Smith Inc.Lab Order: 13120303
Lab ID: 13120303-002A
DF
Print Date: February 25, 2014
Tag Number:
STAT Analysis Corporation2242 West Harrison St., Suite 200, Chicago, IL 60612-3766Tel: (312) 733-0551 Fax: (312) 733-2386 [email protected]
Report Date: February 25, 2014
Accreditation Numbers: IEPA ELAP 100445; ORELAP IL300001; AIHA 101160; NVLAP LabCode 101202-
Grain Size D422 Analyst: SUBPrep Date:Clay Sized Particles * 1/24/2014%5.6Gravel Sized Particles * 1/24/2014%22.6Sand Sized Particles * 1/24/2014%59.3Silt Sized Particles * 1/24/2014%12.4
Qualifiers: J - Analyte detected below quantitation limitsB - Analyte detected in the associated Method Blank
S - Spike Recovery outside accepted recovery limitsR - RPD outside accepted recovery limits
ND - Not Detected at the Reporting Limit
E - Value above quantitation range* - Non-accredited parameter H - Holding time exceededHT - Sample received past holding time
RL - Reporting / Quantitation Limit for the analysis
5 of 8
D60 (mm) D30 (mm) D10 (mm) Cu Cc
1.12 0.27 0.0400 28.00 1.63
SAMPLE ID: PPTDOC-KCBX-North
59.3 12.4 5.6
% + 3" % Gravel % Sand % Silt
GRAIN SIZE ANALYSIS (ASTM D422)
System:
Black coarse to fine sand-sized particles, some coarse to medium gravel-sized particles, little fines, moist
% Clay
Soil Classification:
100.0
3/4" 100.0
65.7
3/8" 100.0
48.1
#4
32.4
#200 18.0
#40
Percent Passing
#20 57.1
#60
Visual Soil Description:
0.0 22.6
#140 21.3
#10
Sieve Size
1"
77.4
0
10
20
30
40
50
60
70
80
90
100
0.0010.0100.1001.00010.000100.0001000.000
PE
RC
EN
T F
INE
R
GRAIN SIZE - mm
1.5
"1
.0"
3/4
"
3/8
"
No
. 1
0
No
. 4
0
No
. 1
00
No
. 2
00
No
. 4
6 of 8
7 of 8
8 of 8
B‐1
Appendix B
Slag Data
C‐1
Appendix C
Modeling Results Figures
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