Impact of Lightning-NO Emissions on Eastern
United States Photochemistry During the Summer
of 2006 as Determined Using the CMAQ Model
Dale Allen, Dept. of Atmos and Oceanic Sci, UMD-College Park
Kenneth Pickering, Atmos Chem and Dyn Branch, NASA-GSFC
Robert Pinder, Atmos Modeling and Analysis Div, U.S. EPA
Barron Henderson, Dept. of Env Sci and Eng, UNC Chapel Hill
William Koshak, Earth Science Office, NASA-MSFC
Thomas Pierce, Atmos Modeling and Analysis Div, U.S. EPA
2010 CMAS Meeting
October 11-13, 2010
Outline
• Motivation & Background
• Describe method used to parameterize lightning-NO emissions
within CMAQ
• Show impact of lightning-NO emissions on tropospheric
composition over the U.S. during the summer of 2006 by
comparing results of EPA simulations with and without
lightning-NO emissions
• Compare model trace gas distributions with
tropospheric NO2 columns from OMI aboard Aura
ozone measurements from IONS field campaign
tropospheric ozone profiles from TES aboard Aura
• Estimate the contribution of lightning-NO emissions to 8-hour
maximum ozone
• Discuss future plans
Motivation for Including Lightning NOx in
CMAQ
•
Lightning NOx emissions have been added to EPA’s Community Multi-scale Air
Quality (CMAQ) model, motivated by the following:
•
In the summer over the US, production of NO by lightning (LNOx) is
responsible for 60-80% of upper tropospheric (UT) NOx and 20-30% of UT
ozone (Zhang et al., 2003; Allen et al., 2010).
•
Mid- and upper-tropospheric ozone production rates are highly sensitive to
NOx mixing ratios.
•
Inversion-based estimates of NO emissions from CMAQ simulations without
lightning-NO emissions have large errors at rural locations (Napelenok et al.,
2008).
•
CMAQ-calculated nitrogen deposition is much too low when lightning-NO
emissions are not included (e.g., Low-bias in CMAQ-calculated nitric acid wet
deposition at NADP sites cut in half when lightning-NO was added).
•
Lightning-NO emissions can add several ppbv to summertime surface ozone
concentrations
CMAQ simulation of summer 2006
• Simulations of 2006 air quality performed at EPA under the
management of Wyat Appel and Shawn Roselle as part of the Air
Quality Model Evaluation International Initiative (AQMEII)
http://aqmeii.jrc.ec.europa.eu/doc/AQMEII_activity_description.pdf
• Version 4.7.1 of CMAQ used with CB-05 chemical mechanism
• NEI-based emissions with year specific power plant emissions from
CEMS and satellite-derived wildfire emissions
• Chemical boundary conditions from GEMS (European-led
assimilation effort)
• http://ozone.meteo.be/meteo/view/en/1550484-GEMS.html
• Met fds from v3.1 of WRF ARW with KF convective parameterization
CMAQ Lightning-NO emission Parameterization
k:
PROD:
LF:
Precon:
threshold:
G:
αi,j:
LNOx = k* PROD*LF, where
Conversion factor (Molecular weight of N / Avogadros #)
Moles of NO produced per flash
Total flash rate (IC + CG), where
LF = G * αi,j * (preconi,j – threshold), where
Convective precipitation rate from WRF
Value of precon below which the flash rate is set to zero.
Scaling factor chosen so that domain-avg WRF flash rate
matches domain averaged observed flash rate.
Local scaling factor chosen so that monthly avg modelcalc flash rate for each grid box equals local observed
flash rate
For these retrospective simulations, the observed flash rate is the NLDNbased total flash rate for June, July, and August 2006.
Operational forecasts could use satellite-retrieved or NLDN-based
climatological flash rates for a season as observations.
What is the NLDN-based total flash rate?
• Hourly cloud-to-ground flash rates (CG) from the National
Lightning Detection Network (US only) are mapped onto the
CMAQ grid.
• Hourly total flash rates (CG +IC) are estimated by multiplying
the CG flash rate by (Z+1), where Z is the climatological IC/CG
ratio Boccippio et al. [2001] determined by comparing satelliteretrieved (Optical Transient Detector instrument) total flash
rates with NLDN CG flash rates.
• Cautionary note:
• Errors in NLDN-based total flash rate can be substantial as 1)
IC flashes > CG flashes , 2) 1995-1999 data set, 3) OTD only
samples a few percent of total flashes
LNOx Production Per Flash
•
Globally, lightning produces 2-8 Tg N / year (Schumann and
Huntrieser, 2007) with a 5 Tg N / year source corresponding to a mean
source of ~250 moles of N / flash.
•
However, recent cloud resolved chem modeling (DeCaria et al., 2000;
2005; Ott et al., 2007; 2009) of observed convective events (STERAO,
EULINOX, CRYSTAL-FACE) and recent modeling of the INTEX-A
period using GEOS-Chem, FLEXPART, RAQMS, MOCAGE [Singh et al.,
2007] and GMI [Allen et al., 2010] indicates that midlatitude &
subtropical lightning produces ~500 moles of N / Flash.
•
In these CMAQ simulations both IC and CG flashes are assumed to
produce 500 moles of N based on the cloud-resolved modeling cited
above.
•
Vertical dist of lightning emissions is assumed to be proportional to
pressure and to the mean vertical distribution of flash channel lengths
in the vicinity of the North Alabama Lightning Mapping Array (LMA)
Vertical partitioning of lightning-NO emissions
Vertical distribution of
flash channel length
in the vicinity of the
North Alabama LMA
is used along with a
direct relationship with
pressure to determine
the fraction of
emissions to put into
each layer from the
surface to the CMAQpredicted cloud top
Segment altitude distribution for
all flashes from Koshak et al. [2010]
NLDN-based
Total
Flash rate
WRF-based
Total
Flash rate
NLDN-based
Total
Flash rate
WRF-based
Total
Flash rate
Flash rate as a function of hour of day
OMI tropospheric NO2 products
1. OMI standard product [Bucsela et al., 2008; Celarier et al., 2008]
2. DOMINO product [Boersma et al., 2007]
3. DOMINO/ GEOS-Chem product (DP-GC) [Lamsal et al. [2010]
4. University of Bremen product [Kim et al., 2009].
Each algorithm begins with same slant columns
Different methods used to remove stratospheric columns
Different methods used to convert trop slant cols to overhead cols
 Yield different tropospheric vertical column amounts
Comparisons of inferred surface NO2 concentrations from these
products with surface layer North American measurements
[Lamsal et al. 2010] indicates that:
OMIstd >> DOMINO >> observations >> DP-GC
OMIstd 70% > observations
DOMINO 30% > observations
DP-GC 5% < observations
Note: Updated OMI standard and DOMINO products are in development.
Bias w/o
lightning
Bias with
lightning
Gulf of Mexico
Comparison of CMAQ O3 with O3 from TES aboard Aura
TES
w/o
Bias
adjust
Bias wrt
TES for
CMAQ
w/o
LNOx
CMAQ
With
LNOx
Bias wrt
TES for
CMAQ
with
LNOx
Note: Model output has been processed through TES averaging kernel
Due to limited retrievals, results are averaged over 4°x5° grid boxes
Mean summer 2006 enhancement of
8-hr maxO3 in CMAQ due to LNOx
O3 enhancement (ppbv)
Poor
AQ
days
All days
Summary
•
CMAQ’s LNOx algorithm captures diel and day-to-day fluctuations in
flash rate
•
LNOx are responsible for ~20% of modeled summertime tropospheric
NO2 column over the U.S.
•
Addition of LNOx to CMAQ eliminates bias between modeled and DPGC tropospheric NO2 columns; however, results from 2004
comparison with INTEX-A obs indicate that considerable low-bias still
remains in upper troposphere
•
Addition of lightning-NO emission contributes to 5-15 ppbv high-bias
wrt TES and IONS in upper tropospheric ozone over the eastern U.S.
•
LNOx in CMAQ contribute < 5 ppbv of O3 to 8-hour max O3 on 96% of
days. Contribution usually smaller on high O3 days
Future Work
Assess sensitivity of results to chemical mechanism by repeating
simulation using updated CB5 chem (currently CB5 overestimates
PAN & NOx to HNO3 conversion rate)
Develop on-line Lightning-NO algorithm to be included in next CMAQ
release. Options for climatological, convective-precipitation based
and observationally constrained flash rates
Develop lightning-NO algorithm suitable for operational forecasts (will
constrain using climatological flash rates)
Provide output for use in inverse studies of NO emissions and for
nitrogen deposition investigations
Acknowledgements
Wyat Appel & Shawn Roselle of EPA: AQMEII simulations
Ana Prados of UMBC: Gridding OMI std product
Anne Thompson: IONS ozonesonde data,
Dylan Jones: TES averaging kernels,
L. Lamsal: DP-GC NO2 data.
OTD/LIS data are from NASA/MSFC.
NLDN data are collected by Vaisala Inc
NASA Applied Science Air Quality Program
Flash rate as a function of day of month