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					Impact of lightning-NO 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 and Thomas Pierce
        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

                   2011 CMAS Meeting
                     26 October 2011
        Motivation for Including Lightning NOx in CMAQ
• 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
  w/o LNOx have large errors at rural locations (Napelenok et al., 2008).
• CMAQ-calculated N deposition is much too low without LNOx (e.g.,
  Low-bias in CMAQ nitric acid wet deposition at NADP sites cut in half
  when LNOx was added).
• LNOx can add several ppbv to summertime surface O3 concentrations
• CMAQ NO2 amounts are too low (high) at rural (urban) locations
  (Castellanos et al., 2011; Huijnen et al., 2010) suggesting that the
  lifetime of NO2 (Henderson et al., 2011) and/or the transport of NOx
  (Gilliland et al., 2008) is underestimated by regional models. How will
  LNOx affect these biases?
                          LNOx Production
•   Lightning-NO production is assumed to be proportional to convective
    precip rate multiplied by a scaling factor chosen so that monthly avg
    model flash rates match monthly avg NLDN-based total flash rates.

•   NLDN-based total flash rate is est by multiplying NLDN CG flash rate
    by Z+1, where Z is the climatological IC/CG ratio (Boccippio et al.,
    2001) determined by taking the ratio between satellite-retrieved
    (Optical Transient Detector) total flash rates and NLDN CG flash rates.

•   IC and CG flashes are assumed to produce 500 moles of N per flash, a
    value that is consistent with cloud resolved modeling of observed
    convective events [DeCaria et al., 2005; Ott et al., 2009] & with larger-
    scale modeling of INTEX-A [Hudman et al., 2007; Allen et al., 2010].

•   Vertical dist of emissions is assumed to be proportional to the
    pressure convoluted by the segment altitude distribution of flashes in
    the vicinity of the North Alabama LMA (Koshak et al., 2010)
              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)

• 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)
           OMI tropospheric NO2 products
1.DP-GC product [Lamsal et al., 2010]
2. v2.0 DOMINO product [Boersma et al., 2007; Boersma et al., 2011]

DP-GC and DOMINO products begin with same slant column & use
same method to remove stratospheric column.
Different methods used to convert tropospheric slant cols to overhead
 Yield different tropospheric vertical column amounts

R=0.47   R=0.79
                    Sensitivity of urban/rural ratio to hor/vert smoothing

1. U/R ratios ↓                                                                 3. U/R ratios ↓
when LNOx                                                                       when avgk is
is added                                                                        applied because
as LNOx                                                                         U/R ratios are
is larger part                                                                  largest near
of rural col                                                                    surface where
than urban                                                                      OMI is
column                                                                          relatively
2. U/R ratios ↓
when mapped
onto 0.25x0.25
grid because
mixes rural and
urban locations

                  4. Relative to OMI, CMAQ has high bias at urban sites.
                  Biases at rural sites are relatively small after accounting for LNOx
                  and the smoothing inherent in DOMINO averaging kernels.
  How much do uncertainties in CB05 chemistry contribute to CMAQ’s
  inability to capture the high amounts of UT NOx measured during the
                    INTEX-A period (An upper bound)?

• CMAQv4.7.1 with CB-05 chemistry and AERO5 aerosols
  was used to simulate the summer of 2004.

• Three simulations: 1) standard chemistry without
  lightning-NO, 2) standard chemistry with lightning-NO,
  and 3) updated chemistry with lightning-NO

• Updated chemistry: Organic nitrate (ON) yield from the
  oxidation of paraffins (PAR) was reduced from 15% to
  3%. The decrease in ON production reduces NO
  consumption, increases the NOx lifetime, and is in better
  agreement with observations (Henderson et al., 2011).
                                             UT NOx by
                                             75-100 pptv
                                             (X4 increase);

                                             however, a
                                             120-500 pptv
                                             low-bias remains.
Adjusting chemistry increases UT NOx by
20-30 pptv reducing model biases by 5-16%    Low-bias is still
if data are unbiased and by 10-33% if data   60-300 pptv
are assumed to be 30% too high due to        after accounting for
MPN interference (Browne et al., 2011)       MPN interference
Mean summer 2006 enhancement of
 8-hr maxO3 in CMAQ due to LNOx

     O3 enhancement (ppbv)

                                       Adding LNOx

                                        for precip
                                        bias leads
                                        to better fit

Eastern US: Longitudes east of 100W
Nitrate         Ammonium
Biases          biases
NE: +5%         NE: +20%
SE: +19%        SE: +40%
West –(5-10)%   West: -(20-25)%

•   For a 500 mole per flash lightning-NO source, mean tropospheric NO2
    columns agree with satellite-retrieved columns to within -5 to +13%.
•   Contribution of LNOx to mean model column is ~25%, ranging from
    ~10% in the northern states to >45% along the Gulf of Mexico and in
    the southwestern states.
•   CMAQ columns have a high-bias wrt DOMINO columns over urban
    areas. Biases at other locations were minor after accounting for the
    impacts of lightning-NO emissions and the averaging kernel on model
•   Chemistry explains less than 1/3 of upper tropospheric NO2
    underpredictions by CMAQ during the INTEX-A period
•   UT O3 is biased high wrt eastern U.S. sonde data. While LNOx
    contributes to bias, most of it is likely due to the specification of BC
    and noise introduced by vertical velocity calculation within CMAQ.
•   LNOx increases wet dep of nitrate by 43%, total dep of N by 10%, &
    changes 30% low-bias wrt NADP measurements to 2% high-bias.
•   On poor AQ days (O3>60 ppbv), LNOx contributes >6.5 ppbv to 8hrO3
    at 10% of western sites and 3% of eastern sites

Wyat Appel & Shawn Roselle of EPA: AQMEII simulations
Ana Prados of UMBC: Gridding OMI std product
Anne Thompson: IONS ozonesonde data,
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
Adding LNOx

Adjusting for
precip bias
lessens scatter
but increases
              Processing of DOMINO & CMAQ fields

•   Gridded DOMINO fields created by mapping version 2.0 level 2 DOMINO
    fields onto 0.25°x0.25° grid.
•   DOMINO retrievals over snow/ice or with cloud radiance fractions > 50%
    filtered out (Boersma et al., 2009)
•   Mean value in each grid box obtained using algorithm that gives more
    weight to near-nadir pixels and to pixels with low geometric cloud fractions
    (Celarier and Retscher, 2009).
•   CMAQ profiles extracted at location of high-quality DOMINO pixels &
    weighted in same manner. CMAQ output interpolated onto TM4 vertical
    grid (TM4 model used to obtain a priori profiles for DOMINO product) .
•   When appropriate, averaging kernel is applied to tropospheric model sub-
    columns before weighting is performed (Allen et al., 2010; Boersma et al.,
•   CMAQ tropospheric NO2 column determined by summing sub-columns
    within the troposphere, where the number of tropospheric layers is included
    in DOMINO data product.
             CMAQ Lightning-NO Parameterization
                        LNOx = k* PROD*LF, where
k:              Conversion factor (Molecular weight of N / Avogadros #)
PROD:           Moles of NO produced per flash
LF:             Total flash rate (IC + CG), where

                LF = G * αi,j * (preconi,j – threshold), where
Precon:          Convective precipitation rate from WRF
threshold:       Value of precon below which the flash rate is set to zero.
G:               Scaling factor chosen so that domain-avg WRF flash rate
                 matches domain averaged observed flash rate.
αi,j:            Local scaling factor chosen so that monthly avg model-
                 calc flash rate for each grid box equals local observed
                 flash rate

For these retrospective simulations, the observed flash rate is the NLDN-
      based 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.
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 CMAQ-
                                        predicted cloud top

Segment altitude distribution for
all flashes from Koshak et al. [2010]
          Comparison of CMAQ & OMI tropospheric column O3

Trpps =
150 hPa

           OMI Level-2 daily ozone profile data courtesy of X. Liu
           Bias: -1.6 DU

                     Adding LNOx
                     NE US: -14%  +11%
Note:                SE US: -19%  +28%
Adding LNOx causes   MW/GP US: -32%  +2%
                     RM/W US: -31%  -2%

Wetdep(OxN) 50%↑     SE bias is reduced to
Totdep(OxN) 22%↑     -3% if adjustment is made
Totdep(N) 11%↑       for a high-bias in SE US
                     CMAQ precip
increases UT          Low-bias
ozone by 5-7 ppbv     is reduced
                      with LNOx
Adjusting chemistry   However
increases UT O3       many
by 2-2.5 ppbv.        factors
Changes small in      to UT
lower troposphere     biases in
In general, the
contribution of
LNOx to 8hrO3
decreases on
bad AQ days
over the
eastern U.S.
• Motivation & Background
• Describe method used to parameterize lightning-NO
  within CMAQ
• Show impact of lightning-NO on tropospheric
  composition, air quality, and nitrogen deposition
  over the U.S. during the summer of 2006
• Use OMI NO2 fields to investigate the cause of biases
  between modeled and “observed” NO2 mixing ratios
  at urban and rural locations
• Investigate the impact of uncertainties in chemistry
  on upper tropospheric NOx distributions in the
  context of the INTEX-A mission

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