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Prakash V. Bhave, Ph.D. Physical Scientist PM Model Performance Workshop February 10, 2004 Postprocessing Model Output for Comparison to Ambient Data.

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Presentation on theme: "Prakash V. Bhave, Ph.D. Physical Scientist PM Model Performance Workshop February 10, 2004 Postprocessing Model Output for Comparison to Ambient Data."— Presentation transcript:

1 Prakash V. Bhave, Ph.D. Physical Scientist PM Model Performance Workshop February 10, 2004 Postprocessing Model Output for Comparison to Ambient Data

2 Horizontal Transport Cloud Processing Chemical Reactions Photo- chemistry Deposition Gas-Phase Emissions Aerosol Emissions Condensation & Evaporation Vertical Mixing Air Quality Model Gridded Values of: Aerosol Concentration Particle Size Distribution Chemical Composition Model Output Emissions Model Meteorology Model Input Ambient Sampling Point Values of: PM 2.5 Mass Conc PM 2.5 Chemical Comp. Observations Laboratory Analysis Model Evaluation Traditional PM Model Evaluations Air Quality Model Ambient Sampling Laboratory Analysis Input

3 Model TuningModel Postprocessing Modification of model inputs or atmospheric chemical & physical formulae to improve agreement between model results and observations. e.g., multiply NH 3 emissions by 2 and rerun the model e.g., raise or lower the minimum eddy diffusivity and rerun the model e.g., modify a rate constant and/or reaction probability and rerun the model Modification of model outputs to simulate ambient sampling conditions, sampling artifacts, and analytical biases. Notes: Inputs are unchanged Atmospheric processing is unchanged No need to rerun the air quality model

4 Emissions Model Meteorology Model Input Horizontal Transport Cloud Processing Chemical Reactions Photo- chemistry Deposition Gas-Phase Emissions Aerosol Emissions Condensation & Evaporation Vertical Mixing Air Quality Model Ambient Sampling Point Values of: PM 2.5 Mass Conc PM 2.5 Chemical Comp. Observations Laboratory Analysis Enhancing PM Model Evaluations - Adjust for site T,RH - Inlet Collection - Substrate Artifacts - Lab Analyses Postprocessing PM 2.5 Mass Conc PM 2.5 Chemical Comp. Output for Eval. Model Evaluation

5 H2OH2O NO 3 SVOC Nonvolatile Material Models predict both gas and particle-phase concentrations Gas/particle partitioning of semi-volatile species is a function of T, RH What if the met model provides a gridded temperature field that is warmer than at the site? i.e., T model > T ambient Ambient Equilibration

6

7 PM 2.5 Inlet Simulation PM 2.5 = 16.7  g/m 3

8 PM 2.5 Inlet Simulation PM 2.5 = 15.5  g/m 3

9 PM 2.5 Inlet Simulation

10 PM 2.5 = 14.9  g/m 3

11 Other Postprocessing Steps Substrate Artifacts  Adsorption/desorption from substrate during sampling  Have been characterized experimentally  Can be estimated with moderate difficulty Chemical Analyses  Lab conditions = 20-23 ºC, 30-40% RH  Exceeds CRH of NH 4 HSO 4, NH 4 NO 3, NaHSO 4,  Aerosol water content can be estimated Organic Mass/Carbon Ratio  Measurements reported as Organic Carbon  Models assume some ratio (e.g., POA = 1.2 in NEI, SOA b = 1.475 in CMAQ, SOA a = 1.67 in CMAQ)

12 Acknowledgements Pete Finkelstein, ORD John Irwin, OAQPS Brian Timin, OAQPS Rob Gilliam, ORD Brian Eder, ORD Ken Schere, ORD S.T. Rao, ORD 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.

13 Atmospheric Processes Modeling Horizontal Transport Cloud Processin g Chemical Reactions Photo- chemistry Deposition Gas-Phase Emissions Aerosol Emissions Condensation & Evaporation Vertical Mixing


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