Prakash V. Bhave, Ph.D. Physical Scientist EMEP Workshop – PM Measurement & Modeling April 22, 2004 Measurement Needs for Evaluating Model Calculations.

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Presentation transcript:

Prakash V. Bhave, Ph.D. Physical Scientist EMEP Workshop – PM Measurement & Modeling April 22, 2004 Measurement Needs for Evaluating Model Calculations of Carbonaceous Aerosol

Policy-Relevant Questions* What fraction of PM 2.5 mass is carbonaceous? What fraction of carbonaceous aerosol is primary vs. secondary? What are the source contributions to primary carbon? What fraction of secondary organic aerosol is anthropogenic vs. biogenic? What fraction of carbon in urban areas is transported from upwind locations?  Existing models can answer these questions, but we need measurements to evaluate the answers * NCEA Carbonaceous PM Workshop Series

Reconstruction of carbonaceous mass  Organic mass contains C, H, O, and N atoms  Carbon is measured; rest is estimated  OM/OC ratios of 1.2 – 2.5 have been proposed  Ratio increases with age of aerosol [Turpin & Lim, 2001]  Speciated or FTIR measurements can help Evaluation approach  In model formulation, OM/OC ratios are known  Convert model predictions to OC, and evaluate against carbon measurements Carbonaceous Fraction of PM 2.5

CMAQ Model Results – Average of 2001 Annual Simulation (TC/PM 2.5,dry )

Carbonaceous Fraction of PM 2.5 STN data averaged from April ’02 – March ’03 * Courtesy of Joann Rice, EPA/OAQPS OC/EC inter-network inconsistencies (STN vs. IMPROVE) - STN OC data are not blank-corrected - Different thermal-optical protocols

Primary vs. Secondary CMAQ–2001 Annual Average (Primary Carbon / Total Carbon)

OC pri & OC sec cannot be measured directly Several indirect estimation methods exist EC tracer method Primary vs. Secondary  Estimate (OC/EC) pri from emissions/transport model [S.Yu, et al., 2004]  Make use of the plentiful, ambient OC and EC data

OC/EC in source profiles must be consistent with the ambient monitors Semi-continuous OC/EC data are needed to check model predictions of diurnal OC sec patterns  Most models predict the OC sec peak at nighttime [Pun et al., 2003] OC & EC data from SEARCH network (IMPROVE TOR method) Primary vs. Secondary

OC/EC splits in the inventory inconsistent with ambient sampling protocols Primary vs. Secondary PM2.5 Weight % 1999 Emissions TC (tons) Primary OC/EC Sampling Protocol NEI99 Source ProfileOCEC Non-road Diesel Exhaust18.70%74.11%86, TOR Agricultural Burning53.24%7.50%73, various Heavy-duty Diesel Exhaust18.93%75.00%38, TOR Non-road Gasoline Exhaust65.50%8.01%17, TOT Light-duty Gasoline Exhaust47.35%19.01%10, TOR Soil Dust4.54%0.37%8, various Paved Road Dust14.73%1.12%6, TOR Jet Fuel Combustion24.34%65.87%6, unknown Wood Waste Boilers9.81%20.19%4, thermal Natural Gas Combustion50.00%0.00%3,865-N/A Solid Waste Combustion0.57%3.50%2, TOR Residual Oil Combustion19.93%19.33%2, TOR Wood Products - Drying65.83%4.39%1, various Fiberglass Manufacturing28.00%2.00%1, thermal Food & Agriculture Handling30.00%0.00%1,353-N/A Other SourcesN/A 10, various

- CMAQ results using source apportionment capability (Aug. 1, 1999) - Evaluations will provide direct feedback to emission inventory improvement - Validated results can support control strategy development Apportionment of Primary Carbon Diesel exhaust fractionBiomass combustion fraction

Needs for Model Evaluation Data types  Source-specific organic tracers (e.g., levoglucosan, hopanes, cholesterol, etc.) [Schauer, et al.]  Primary biogenic carbon (e.g., carbohydrates, vegetative detritus) [M. Hernandez; W. Rogge, et al.]  Semi-continuous wood smoke source tracers? Spatial resolution  Several urban sites (e.g., each Supersite)  Some representative rural sites Temporal resolution  24h data at urban sites for ~1 month per season  2-6h composites at urban sites to check diurnal variation  Monthly composites at rural sites to check seasonality Apportionment of Primary Carbon

SOA: Biogenic vs. Anthropogenic What fraction of SOA is anthropogenic?  Great uncertainty within model parameterizations  Nashville: July 16-18,1995 model inter-comparison yields values of 10% - 40% [Pun et al., 2003] Uncertainties too large to justify controls directed specifically at anthropogenic SOA

Needs for Model Evaluation Data types  14 C can help provide a measure of biogenic SOA; need collocated wood smoke & vegetative detritus data  Source-specific SOA tracers [Edney et al.] SOA: Biogenic vs. Anthropogenic Reprinted from: Edney & Kleindeinst OAQPS Model Eval Workshop, Chapel Hill, Feb.10, 2004

CMAQ–2001 Annual Average (Anthropogenic fraction of OC sec ) SOA: Biogenic vs. Anthropogenic

Carbon fraction of PM 2.5 OC, EC data are plentiful; some network inconsistencies OM/OC uncertain, but not essential for model evaluation Primary vs. secondary? Consistent definition of OC and EC across ambient networks and source data Semi-continuous OC & EC Primary source apportionment Source-specific tracers Increase spatial & temporal resolution of organic tracer measurements Anthropogenic vs. biogenic SOA Tracers for aromatic and monoterpene oxidation 14 C collocated with wood smoke & detritus markers Summary of Measurement Needs

Acknowledgements Atmospheric Modeling Division (NOAA/EPA) Emissions Monitoring & Analysis Division – Air Quality Modeling Group (OAQPS) Computer Sciences Corporation Disclaimer Notice: This work has been funded wholly by the United States Environmental Protection Agency. It has been subjected to Agency review and approved for presentation.

Carbonaceous Fraction of PM 2.5 Urban Network (STN) PM 2.5 = 10.5  g/m 3 CMAQ Model PM 2.5 = 11.5  g/m Network Median Values (~7000 observations) Carbon Value is “blank-corrected” by 1  g/m 3

Apportionment of Primary Carbon Gasoline exhaust fractionCoal combustion fraction - CMAQ results using source apportionment capability (Aug. 1, 1999)

Apportionment of Primary Carbon Oil combustion fractionNatural gas combustion fraction - CMAQ results using source apportionment capability (Aug. 1, 1999)

Apportionment of Primary Carbon Food cooking fractionPaved road dust fraction - CMAQ results using source apportionment capability (Aug. 1, 1999)

Apportionment of Primary Carbon Crustal material fractionMiscellaneous source fraction - CMAQ results using source apportionment capability (Aug. 1, 1999)

Fresno Indy S.L. Tulsa Missoula SLC Bronx Charlotte Baltimore Atlanta Cleveland Richmond Birmingham 16 rural IMPROVE sites 13 urban STN sites Local vs. Regional Contribution Reprinted from: N. Frank OAQPS Model Eval Workshop, Chapel Hill, Feb.10, 2004 Differences between urban (STN) and paired rural site (IMPROVE)

Differences between urban and paired rural site(s) - Carbonaceous mass dominates the “urban excess” Local vs. Regional Contribution Reprinted from: N. Frank OAQPS Model Eval Workshop, Chapel Hill, Feb.10, 2004

CMAQ Results at 1km resolution (OC+EC) Along Pennsylvania - New Jersey border Local vs. Regional Contribution Urban contribution 5.4  g/m 3 Urban contribution 10.1  g/m 3