1. Meteorological drivers of surface ozone biases in the Southeast US
Katie Travis
IGC8
5/3/2017
Co-authors: Daniel Jacob, Mike Newchurch, Shi Kuang, Anne Thompson, Tom Ryerson, Jintai Lin

2. Models Cannot Successfully Capture Surface Ozone in the Southeast US
2001
SurfaceMDA8 O3
Observations
Multi-model Mean
The southeast U.S. has been a trouble spot for chemical transport models for a long time as shown by this multi-model comparison from Arlene Fiore’s CTM model evaluation of 2001 o3. It is also a unique region, characterized by high isoprene emissions and high anthropogenic Nox compared to other parts of the countries. This bias has been loosely attributed to uncertainties in NOx-O3-VOC chemistry. Not only is this a difficult region for models due to the complex isoprene chemistry that takes place, but it is a region where the chemical regime is changing very quickly. I am showing this plot from Russell et al, 2012 of the decline in OMI NO2 tropospheric column densities from 2005 to OMI NO2 implies a decrease in Nox of approximately 30% over this timeperiod. For comparison, EPA’s national emission trends indicate a decline of 28% over this period, with an additional 10% decrease through 2013.
Global and regional CTMs overestimate O3 by 10-20ppb.
, with an additional 10% decrease through 2013.
Fiore et al, 2009
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Model difficulties have been attributed to uncertainties in NOx-O3-VOC chemistry/emissions/deposition.
Recent studies have similar biases (Canty et al., 2015, Lin et al., 2017).
This is of concern for the design of air quality regulations.

3. MDA8 Ozone at CASTNET Sites
O3, NOx, and HNO3
Uncertainties in Modeling Ozone in the Southeast US are Significantly Reduced thanks to SEAC4RS
PI. J. Dibb
PI. T. Ryerson
PI. T. Ryerson
MDA8 Ozone at CASTNET Sites
Observations
Model
Original NOx
Unique Tracers of Isoprene Oxidation
PI. P. Wennberg
Travis et al. (2016)
*See Fisher et al., 2016
Reduced MDA8 ozone by ~10ppb. Successfully captured SEAC4RS ozone production efficiency of ~17 (unscaled = 15).
Largely due to reduction (~50%) to EPA NEI NOx inventory confirmed by previous and subsequent studies.
Observations of nitrate wet deposition fluxes indicate that the EPA NEI inventory may be biased across the entire US.

4. We have a successful NOx simulation in the Southeast US but a bias in surface O3
PI T. Ryerson
Surface O3 remains biased by 8 ppb.
Implied gradient suggests need for a surface correction from the lowest model grid-point (~60m) to the measurement altitude (~10m).
Model misses low tail below 25 ppb (6% of obs).
Just 1 exceedance of 70 ppb in 2013 (24 in 2011).

5. Surface Correction is Significant for MDA8 Ozone
Height of the first model grid-point
 The model has a mean positive bias which is due in part to the vertical
gradient of concentrations between the lowest model
grid-point (z1  = 70 m) and the CASTNet measurement altitude
(zC  = 10 m). This gradient can be quantified from the
resistance-in-series formulation for dry deposition used in
GEOS-Chem.
Brasseur and Jacob (2016)
We recalculate RA from the first model grid point to 10m to obtain the model value at this altitude.
Correction is larger when the atmosphere is more stable.
Correction is 3 ppb in the Southeast US.

6. August-September 2013 was a cool and wet year, but not an outlier
The relatively low surface ozone measured at CASTNET sites in August-September 2013 reflects lower-than-average but not anomalous conditions.
About 30% wetter, 1oC cooler
Wet and cool also means cloudier than average  2013 had approximately 50% greater low-cloud than 2011.
How do these conditions challenge model skill in capturing MDA8 ozone?

7. Weak model response to cloudy/rainy conditions cause model bias
Rainy conditions explain the low tail of MDA8. Model failure could be due to stratification from evaporative cooling.
In the Southeast US, GEOS-Chem low cloud is underestimated by a factor of 3 and rain is underestimated by ~30%.
Model response to cloud cover is ~50% of observed response. Correcting for missing cloud cover does not improve bias.

8. Model compares well with Southeast US ozonesonde from 3-12 km
Bias from 3-12 km is 1 ± 12 ppb

9. Observed gradient may be strongest on cloudy days, and is not captured by the model
Mean Profile
Cloudy observations show the largest gradient  ppb. Model cloud profiles are flat.
Increasing the sink of ozone would not change the model gradient. Slower mixing improves the profile.
Slower entrainment, ozone production, or a surface sink would still be required to reconcile model bias.

10. Conclusions
Uncertainty in modeling surface ozone in the Southeast US is significantly improved due to better constraints on isoprene chemistry and NOx budget.
EPA NOx inventory may be overestimated by as much as 50%.
Model is still biased by ~8 ppb against surface observations.
The correction for the ozone gradient below the lowest model grid- point is significant (3 ppb) and should be applied in future studies.
Rainy conditions explain the larger model bias at low values of MDA8 ozone.
The weak model response to low-cloud cover (and missing model low- cloud) explains the remaining model bias.