Evaluation of 2002 Multi-pollutant Evaluation of 2002 Multi-pollutant Platform: Air Toxics, Mercury, Platform: Air Toxics, Mercury, Ozone, and Particulate MatterOzone, and Particulate Matter

US EPA / OAQPS / AQAD / AQMG

Sharon Phillips, Kai Wang, Carey Jang, Norm Possiel, Madeleine Strum, and Tyler Fox

7th Annual CMAS Conference – October 6-8, 2008

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OutlineOutline2002 modeling platform and components2002 modeling platform and components Criteria Air Pollutants Only “CAP-only”Criteria Air Pollutants Only “CAP-only” Criteria Air Pollutants + Hazardous Air Pollutants Criteria Air Pollutants + Hazardous Air Pollutants

“CAP+HAP”“CAP+HAP”

Model Evaluation of 2002 CMAQ CAP & Model Evaluation of 2002 CMAQ CAP & CAP+HAP predictions with ambient dataCAP+HAP predictions with ambient data

Possible causes for model performance Possible causes for model performance issues and analyses to further exploreissues and analyses to further explore

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2002 Modeling Platform2002 Modeling PlatformDeveloped jointly between OAQPS & ORDDeveloped jointly between OAQPS & ORD

Promotes multi-pollutant assessmentsPromotes multi-pollutant assessments Integrated inventory (criteria and air toxics)Integrated inventory (criteria and air toxics) ““One-atmosphere” CMAQ with AERMOD / Fine scale grid modeling for One-atmosphere” CMAQ with AERMOD / Fine scale grid modeling for

selected urban areas (e.g. Detroit MP Study)selected urban areas (e.g. Detroit MP Study) Currently moving towards 2005 MP modeling platform (CMAQv4.7)Currently moving towards 2005 MP modeling platform (CMAQv4.7)

Provides consistency, transparency, and efficient Provides consistency, transparency, and efficient development of baselines for:development of baselines for:

OAR regulatory assessmentsOAR regulatory assessments CMAQ evaluations & research efforts by ORDCMAQ evaluations & research efforts by ORD Accountability efforts across EPAAccountability efforts across EPA Public health & exposure assessmentsPublic health & exposure assessments

Provides data and examples for others (e.g., Provides data and examples for others (e.g., State/local agencies)State/local agencies)

Emissions data: http://www.epa.gov/ttn/chief/emch/index.html#2002Emissions data: http://www.epa.gov/ttn/chief/emch/index.html#2002

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Components of 2002 MP Modeling PlatformComponents of 2002 MP Modeling Platform2002 National Emissions Inventory (NEI) v32002 National Emissions Inventory (NEI) v3

Criteria (CAPs) and HAPsCriteria (CAPs) and HAPs

2002 Meteorological Data2002 Meteorological Data MM-5 and MCIP v3.1MM-5 and MCIP v3.1 36km US, 12 km EUS, 12km WUS (from WRAP)36km US, 12 km EUS, 12km WUS (from WRAP)

Emissions Models, Tools and Ancillary DataEmissions Models, Tools and Ancillary Data Emissions Modeling Framework (EMF)Emissions Modeling Framework (EMF) Emissions processing: SMOKE version 2.3.2 Emissions processing: SMOKE version 2.3.2 Biogenics: BEIS 3.13Biogenics: BEIS 3.13 Onroad/nonroad emissions: NMIM (w/ MOBILE6 & NONROAD 2005)Onroad/nonroad emissions: NMIM (w/ MOBILE6 & NONROAD 2005) EGU projections: IPM 3.0EGU projections: IPM 3.0 Ancillary data: speciation, temporal, spatial allocationAncillary data: speciation, temporal, spatial allocation

Boundary Condition ConcentrationsBoundary Condition Concentrations 2002 simulations of GEOS-Chem: 22002 simulations of GEOS-Chem: 2° x 2° grids & 30 layers up to stratosphere° x 2° grids & 30 layers up to stratosphere 36-km US domain for CAPS, mercury, and some HAPS (e.g. formaldehyde)36-km US domain for CAPS, mercury, and some HAPS (e.g. formaldehyde) For toxics not simulated by GEOS-Chem we used concs based on remote For toxics not simulated by GEOS-Chem we used concs based on remote

measurements and literature values (joint effort b/n AQAG & ORD)measurements and literature values (joint effort b/n AQAG & ORD)

Air Quality ModelAir Quality Model CMAQ v4.6 (base CAP only & “proto-type” multi-pollutant version) CMAQ v4.6 (base CAP only & “proto-type” multi-pollutant version) CB-05 chemical mechanism with mercury and chlorine chemistryCB-05 chemical mechanism with mercury and chlorine chemistry Ozone, PM, and additional 38 HAPsOzone, PM, and additional 38 HAPs

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36km Domain Boundary

12km East Domain Boundary

12km West Domain Boundary

Model Domains

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Model Performance AnalysisModel Performance AnalysisPMPM2.52.5 Species: SO Species: SO44, NO, NO33, TNO, TNO33, OC, EC, SO, OC, EC, SO22

STN, CASTNet, IMPROVE, NADPSTN, CASTNet, IMPROVE, NADPOzone: 1 hr-max & 8 hr-maxOzone: 1 hr-max & 8 hr-max

AQS, SEARCHAQS, SEARCHHAPs: Mercury, Formaldehyde, Acetaldehyde, Benzene, HAPs: Mercury, Formaldehyde, Acetaldehyde, Benzene, etc., + metalsetc., + metals

MDN, NATTS, STN, IMPROVEMDN, NATTS, STN, IMPROVE

Graphics and Statistics: AMET 1.1 Graphics and Statistics: AMET 1.1 (www.cmascenter.org)(www.cmascenter.org) hourly, daily, monthly, seasonal & annualhourly, daily, monthly, seasonal & annual Spatial tile maps comparing observed and predicted species Spatial tile maps comparing observed and predicted species

concentrations/deposition concentrations/deposition Scatter plots of observations vs predictionsScatter plots of observations vs predictions Time-series plots of observations vs predictionsTime-series plots of observations vs predictions Statistics:Statistics:

Normalized Mean Bias (NMB) / Fractional Bias (FB)Normalized Mean Bias (NMB) / Fractional Bias (FB)Normalized Mean Error (NME) / Fractional Error (FE)Normalized Mean Error (NME) / Fractional Error (FE)Root Mean Square Error (RMSE)Root Mean Square Error (RMSE)

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Examples of Model Performance For Examples of Model Performance For Selected CAPsSelected CAPs

Based on 2002 CAP-only CMAQ Based on 2002 CAP-only CMAQ Modeling at 12 km EUS & WUSModeling at 12 km EUS & WUS

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Highlights of 2002 Model Evaluation for CAPsHighlights of 2002 Model Evaluation for CAPsOzoneOzone

Under predicted for 1-hr & 8-hr daily max. especially OUnder predicted for 1-hr & 8-hr daily max. especially O33 > 60 ppb > 60 ppbSulfate PMSulfate PM

Under predicted (~ up to 20%) in all seasons in the East & WestUnder predicted (~ up to 20%) in all seasons in the East & WestSulfur DioxideSulfur Dioxide

Over predicted (~ 15 to 65%) in all seasons in the East & WestOver predicted (~ 15 to 65%) in all seasons in the East & WestNitrate PMNitrate PM

Over predicted (~ 5 to 40%) in Fall, Winter, and in northern areas of Over predicted (~ 5 to 40%) in Fall, Winter, and in northern areas of the East in the Springthe East in the Spring

Organic CarbonOrganic Carbon Over predicted in the North and under predicted in South and West Over predicted in the North and under predicted in South and West

in the Winterin the Winter Under predicted in all areas (~ 25 to 65%) in Fall, Spring & SummerUnder predicted in all areas (~ 25 to 65%) in Fall, Spring & Summer

Elemental CarbonElemental Carbon Mostly over predicted in urban areas (~ 40%) in all seasons in the Mostly over predicted in urban areas (~ 40%) in all seasons in the

East and WestEast and West Mostly under predicted in rural areas (10 to > 40%) in all seasons in Mostly under predicted in rural areas (10 to > 40%) in all seasons in

the East and Westthe East and West

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SO4 Wet Deposition2002 Total

NADP

12-km EUS

12-km WUS

Summer MeanNMB (%) NME (%)

EUS 14.8 38.1WUS -35.2 50.1

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NO3 Wet Deposition2002 Total

12-km EUS

12-km WUS

Winter MeanNMB (%) NME (%)

EUS 8.8 37.9WUS -18.6 59.7

NADP

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CAP+HAP vs CAP-only differencesCAP+HAP vs CAP-only differencesEmission DifferencesEmission Differences

Use HAPs for speciation for select sourcesUse HAPs for speciation for select sources Use formaldehyde, acetaldehyde and methanol for all sourcesUse formaldehyde, acetaldehyde and methanol for all sources Very small spatial/temporal profile differences in some Very small spatial/temporal profile differences in some

geographic areasgeographic areas

Model DifferencesModel Differences Chlorine chemistryChlorine chemistry Added air toxicsAdded air toxics

Differences in PredictionsDifferences in Predictions Slight differences in Summer & Winter Ozone (Northeast, CA, Slight differences in Summer & Winter Ozone (Northeast, CA,

UT)UT) Slight differences in Winter NOSlight differences in Winter NO33 (Northeast, GA, UT) (Northeast, GA, UT) Negligible differences in Summer SONegligible differences in Summer SO44 Some differences in Winter & Summer Formaldehyde & Some differences in Winter & Summer Formaldehyde &

AcetaldehydeAcetaldehyde

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2002 July Ozone: CAP+HAP – CAP-only

July: CAP+HAP slightly less ozone in Northeast, more ozone in Utah in vicinity of large source of chlorine emissions.

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2002 January Formaldehyde: CAP+HAP – CAP-only

Difference in CMAQ FORM Difference in FORM Emissions

CMAQ differences in winter appear to be due to differences in speciation of residential wood combustion CAP VOC vs formaldehyde in the HAP inventory (CAP << HAP).

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Examples of Model Performance For Examples of Model Performance For Selected HAPsSelected HAPs

Based on 2002 CAP+HAP CMAQ Based on 2002 CAP+HAP CMAQ Modeling for the 12 km EUSModeling for the 12 km EUS

2002 Formaldehyde – EUS 12km

Winter – Monthly MeanSummer – Monthly Mean

High observations – may be due to short-term releases, near-source monitors, or instrument issues

NMB = - 51.3% NME = 55.2%

NMB = - 31.5% NME = 64.1%

2002 Formaldehyde – EUS 12km

Same data, but without high observed values

Summer – Monthly Mean Winter – Monthly Mean

NMB = - 35.6% NME = 42.1%

NMB = - 15.7% NME = 56.9%

2002 Acetaldehyde – EUS 12km

Winter – Monthly MeanSummer – Monthly Mean

Slightly higher concs. observed at sites in MA & GA

NMB = 54.9% NME = 77.9%

NMB = - 27.8% NME = 44.2%

2002 Benzene – EUS 12km

Winter – Monthly MeanSummer – Monthly Mean

Slightly higher concs. observed at 1 site in TX & IN

NMB = 41.0% NME = 55.0%

NMB = - 27.3% NME = 58.3%

Slightly higher concs. observed at 3 sites in TX & 1 site IN

2002 Lead PM2.5 – EUS 12km

Winter – Monthly MeanSummer – Monthly Mean

NMB = - 53.8% NME = 62.6%

NMB = - 33.8% NME = 54.6%

Slightly higher concentrations observed at Birmingham, AL

2002 Chromium PM2.5 – EUS 12km

Winter – Monthly MeanSummer – Monthly Mean

NMB = - 47.3% NME = 72.3%

NMB = - 14.0% NME = 82.6%

Slightly higher concentrations observed at same site in Birmingham, AL

2002 Carbon Tetrachloride – EUS 12km

Winter – Monthly MeanSummer – Monthly Mean

NMB = - 73.0% NME = 73.0%

NMB = - 59.7% NME = 60.6%

Influence of detection level in observations

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Examples of Model Performance Examples of Model Performance For Mercury Wet DepositionFor Mercury Wet Deposition

Based on 2002 CAP+HAP CMAQ Based on 2002 CAP+HAP CMAQ Modeling at 12 km EUSModeling at 12 km EUS

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2002 Annual Mercury Wet Deposition

12 km EUS

NMB = - 10.1% NME = 23.2%

2002 Seasonal Hg Wet Deposition – EUS 12-km

Summer

SpringWinter

Fall

Over-prediction in Winter & Spring

Under-prediction in Fall & Summer

NMB = 30.7% NME = 43.4%

NMB = 15.1% NME = 32.7%

NMB = -15.5% NME = 39.9%

NMB = -34.2% NME = 39.8%

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Identified Technical Issues with Tools Identified Technical Issues with Tools and Data for MP Analysesand Data for MP Analyses

Model performance for some non-ubiquitous HAPs Model performance for some non-ubiquitous HAPs is not as “good” as that for ozone and PM2.5is not as “good” as that for ozone and PM2.5

Uncertainties in monitoring methodsUncertainties in monitoring methods Limited measurements in time/space to characterize ambient Limited measurements in time/space to characterize ambient

concentrations (“local in nature”)concentrations (“local in nature”)Given local nature of some toxics, fine scale modeling may be neededGiven local nature of some toxics, fine scale modeling may be needed

Commensurability issues between measurements and model Commensurability issues between measurements and model predictionspredictions

Emissions and science uncertainty issues may also affect model Emissions and science uncertainty issues may also affect model performanceperformance

Limited data for estimating intercontinental transport (i.e., Boundary Limited data for estimating intercontinental transport (i.e., Boundary Conditions)Conditions)

Boundary estimates for some species are much higher than predicted Boundary estimates for some species are much higher than predicted values inside the domainvalues inside the domain

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Identified Technical Issues with Tools Identified Technical Issues with Tools and Data for MP Analysesand Data for MP Analyses

Emissions-related issuesEmissions-related issues No available HAP inventories for Canada (except Hg) No available HAP inventories for Canada (except Hg)

& Mexico& Mexico Inconsistencies between emissions factors for CAPs Inconsistencies between emissions factors for CAPs

and HAPsand HAPs Criteria/HAP emissions are not easily integratedCriteria/HAP emissions are not easily integrated

Inconsistencies in CAP/HAP emissions reported by StatesInconsistencies in CAP/HAP emissions reported by StatesInconsistencies between VOC speciation and HAP Inconsistencies between VOC speciation and HAP inventories – need for coordinated research effortinventories – need for coordinated research effort

Periodic nature of some toxic releases that are not Periodic nature of some toxic releases that are not well characterized in our inventorieswell characterized in our inventories

Uncertainties in science (e.g., mercury chemistry Uncertainties in science (e.g., mercury chemistry and re-emissions) and evolving science for and re-emissions) and evolving science for various components of the modeling systemvarious components of the modeling system

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Future EffortsFuture Efforts

Continue model evaluation efforts and Continue model evaluation efforts and investigate performance issues in conjunction investigate performance issues in conjunction with ORDwith ORD

Prepare 2002 Multi-Pollutant Platform ReportPrepare 2002 Multi-Pollutant Platform Report

Complete 2005 Multi-Pollutant Modeling Complete 2005 Multi-Pollutant Modeling PlatformPlatform

Provide feedback to the 2008 NEI integrated Provide feedback to the 2008 NEI integrated inventory process and future modeling platforms inventory process and future modeling platforms