Photochemical Model Assessment of PM2.5 Ammonium Nitrate in - - PowerPoint PPT Presentation

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Photochemical Model Assessment of PM2.5 Ammonium Nitrate in - - PowerPoint PPT Presentation

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Photochemical Model Assessment of PM2.5 Ammonium Nitrate in California Kirk Baker Heather Simon U.S. Environmental Protection Agency 10/11/2010 1 Monday, October 11, 2010 1 California PM2.5 Many nonattainment counties for the 24-hr

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Photochemical Model Assessment of PM2.5 Ammonium Nitrate in California Kirk Baker Heather Simon

U.S. Environmental Protection Agency

1 Monday, October 11, 2010

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California PM2.5

  • Many nonattainment

counties for the 24-hr PM2.5 NAAQS located in the central Valley of California

  • Elevated 24-hr PM2.5
  • ften composed of

ammonium nitrate and organic carbon in this area

2 Monday, October 11, 2010

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Background

MODELING SYSTEM

  • Evaluate regulatory modeling system performance for PM2.5 in

California

  • MM5 meteorology
  • SMOKE emissions modeling based emissions on 2005 NEI
  • CMAQ v4.7 photochemical modeling
  • Annual 2005 modeling of western U.S. with 12 km sized grid cells

AMBIENT DATA

  • 24-hr avg speciated PM2.5: IMPROVE and CSN (STN,ESPN)
  • Hourly PM2.5 nitrate ion & black carbon at Fresno
  • Hourly surface meteorology: T, WS, WD, MR, Fog, Haze
  • Upper air soundings at Hanford, CA

3 Monday, October 11, 2010

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Modeling system underpredicting PM2.5 nitrate ion in the winter in central California

ug/m3

Monthly average PM2.5 NO3 bias (model-obs) for Feb. 2005

4 Monday, October 11, 2010

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Hourly PM2.5 Nitrate at Fresno

5 Monday, October 11, 2010

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Possible Causes of Nitrate Bias

  • Chemistry related issues

– Formation of HNO3: chemistry( gas-phase, heterogeneous, cloud/fog) or NOx emissions – Gas/particle partitioning: NH4 emissions or met

  • How well is the hourly meteorology characterized at

Fresno

– Temperature and relative humidity important for nitrate partitioning – Any clear connection between performance issues in meteorological variables and PM2.5 performance problems?

  • Transport/Dilution

6 Monday, October 11, 2010

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HNO3 Formation: chemistry

  • CMAQ gas and

heterogeneous chemistry already over-predict this chemistry

  • This process also occurs in

clouds/fog

– Does model under-predict fog

  • ccurrences in SJV?
  • Days with highest nitrate

bias for this Fresno episode (Feb 1-5, 2005) did not have any reported fog

7 Monday, October 11, 2010

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Emissions: NH3 and NOX

  • Can emissions inaccuracies explain

these nitrate under-predictions?

  • Modeling system currently applies a

national ammonia emissions profile to California by month and hour of the day

8 Monday, October 11, 2010

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Emissions Sensitivities

  • Sensitivity runs were

performed in which NOx and NH3 emissions were increased by 50% across the board

  • Increasing NH3 and NOx

emissions does not significantly affect nitrate levels below ~4 ug/m3, but causes over- predictions in nitrate when concentrations are between 4-8 ug/m3

  • Increasing NH3 and NOx

emissions by 50% is not enough to correct for under-predictions of high nitrate concentrations

9 Monday, October 11, 2010

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PM2.5 Nitrate – Emissions Sensitivities

  • Emissions adjustments do not substantively “improve” model

performance of hourly PM2.5 nitrate ion

10 Monday, October 11, 2010

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Hourly PM2.5 Nitrate at Fresno

11 Monday, October 11, 2010

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Temperature

12 Monday, October 11, 2010

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Relative Humidity

PM2.5 Nitrate ion bias compared to relative humidity bias

13 Monday, October 11, 2010

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Wind Speed

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Wind Speed

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Wind Speed

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Speciated PM2.5 by Hour of the Day

  • No direct measurements of PBL in the central valley
  • Hourly elemental carbon measurements provide an indirect characterization of

the tendency of the modeling system to capture diurnal variability in mixing height

17 Monday, October 11, 2010

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Temperature (C)

Model Layer

Vertical Temperature Performance at Hanford, CA (near Fresno)

18 Monday, October 11, 2010

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Measurements

  • How accurate are

measurements of PM2.5 nitrate ion at Fresno?

  • Multiple methods

making hourly PM2.5 nitrate ion measurements

  • Additional 24-hr

measurements from CSN network site

  • Large variability

between measurement methods

19 Monday, October 11, 2010

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Conclusions

  • RH and wind speed influence model estimates of PM2.5

nitrate ion in central California during the winter

  • Increased NOX did not improve performance during

these episodes

  • Increases in ammonia emissions do not help with PM2.5

nitrate under estimation events and actually degrade model performance

  • EC temporal profiles compare well but model tends to
  • verestimate EC which suggests PBL may not be

contributing to under estimation events

  • Quite a bit of variability in PM2.5 measurements at

Fresno

  • Next steps of investigation: deposition (may be affected by phase of

nitrate)

20 Monday, October 11, 2010