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Travis, Katherine R.

Publications and source records attributed to Travis, Katherine R..

Constraining Remote Oxidation Capacity with ATom Observations

The global oxidation capacity, defined as the tropospheric mean concentration of the hydroxyl radical (OH), controls the lifetime of reactive trace gases in the atmosphere such as methane and carbon monoxide (CO). Models tend to underestimate the methane lifetime and CO concentrations throughout the troposphere, which is consistent with excessive OH. Approximately half the oxidation of methane and non-methane volatile organic compounds (VOCs) is thought to occur over the oceans where oxidant chemistry has received little validation due to a lack of observational constraints. We use observations from the first two deployments of the NASA ATom aircraft campaign during July–August 2016 and January–February 2017 to evaluate the oxidation capacity over the remote oceans and its representation in the GEOS-Chem chemical transport model. The model successfully simulates the magnitude and vertical profile of remote OH within the measurement uncertainties. Comparisons against the drivers of OH production (water vapor, ozone, and NOy concentrations, ozone photolysis frequencies) also show minimal bias with the exception of wintertime NOy, for which a model overestimate may indicate insufficient wet scavenging and/or missing loss on seasalt aerosol but large uncertainties remain that require further studies of NOy partitioning and removal in the troposphere. During the ATom-1 deployment, OH reactivity (OHR) below 3 km is significantly enhanced, and this is not captured by the sum of its measured components (cOHRobs) or by the model (cOHRmod). This enhancement could suggest missing reactive VOCs but cannot be explained by new estimates of ocean VOC sources and additional modeled reactivity in this region would be difficult to reconcile with the full suite of ATom measurement constraints. The model generally reproduces the magnitude and seasonality of cOHRobs but underestimates the contribution of oxygenated VOC, mainly acetaldehyde, which is severely underestimated throughout the troposphere despite its calculated lifetime of less than a day. Missing model acetaldehyde in previous studies was attributed to measurement uncertainties that have been largely resolved. Observations of peroxyacetic acid (PAA) provide new support for remote levels of acetaldehyde. The underestimate in modeled acetaldehyde and PAA is present throughout the year in both hemispheres and peaks during Northern Hemisphere summer. The addition of ocean VOC sources in the model increases annual surface cOHRmod by 10 % and improves model-measurement agreement for acetaldehyde particularly in winter but cannot resolve the model summertime bias. Doing so would require a 100 Tg yr−1 source of a long-lived unknown precursor throughout the year with significant additional emissions in the Northern Hemisphere summer. Improving the model bias for remote acetaldehyde and PAA is unlikely to fully resolve previously reported model global biases in OH and methane lifetime, suggesting that future work should examine the sources and sinks of OH over land.

Travis, Katherine R.↗

Glyoxal Yield from Isoprene Oxidation and Relation to Formaldehyde: Chemical Mechanism, Constraints from SENEX Aircraft Observations, and Interpretation of OMI Satellite Data

Glyoxal (CHOCHO) is produced in the atmosphere by the oxidation of volatile organic compounds(VOCs). Like formaldehyde (HCHO), another VOC oxidation product, it is measurable from space by solar backscatter. Isoprene emitted by vegetation is the dominant source of CHOCHO and HCHO in most of the world. We use aircraft observations of CHOCHO and HCHO from the Southeast Nexus (SENEX) campaign over the southeast US in summer 2013 to better understand the CHOCHO time-dependent yield from isoprene oxidation, its dependence on nitrogen oxides (NO (sub x) triple bonded to NO plus NO2), the behavior of the CHOCHO-HCHO relationship, the quality of Ozone Monitoring Instrument (OMI) CHOCHO satellite observations, and the implications for using CHOCHO observations from space as constraints on isoprene emissions. We simulate the SENEX and OMI observations with the Goddard Earth Observing System chemical transport model (GEOSChem) featuring a new chemical mechanism for CHOCHO formation from isoprene. The mechanism includes prompt CHOCHO formation under low-NO (sub x) conditions following the isomerization of the isoprene peroxy radical (ISOPO2).The SENEX observations provide support for this prompt CHOCHO formation pathway, and are generally consistent with the GEOS-Chem mechanism. Boundary layer CHOCHO and HCHO are strongly correlated in the observations and the model, with some departure under low-NO (sub x) conditions due to prompt CHOCHO formation. SENEX vertical profiles indicate a free-tropospheric CHOCHO background that is absent from the model. The OMI CHOCHO data provide some support for this free-tropospheric background and show southeast US enhancements consistent with the isoprene source but a factor of 2 too low. Part of this OMI bias is due to excessive surface reflectivities assumed in the retrieval. The OMI CHOCHO and HCHO seasonal data over the southeast US are tightly correlated and provide redundant proxies of isoprene emissions. Higher temporal resolution in future geostationary satellite observations may enable detection of the prompt CHOCHO production under low-NO (sub x) conditions apparent in the SENEX data.

OMI↗

Impact of Evolving Isoprene Mechanisms on Simulated Formaldehyde: An Inter-comparison Supported by in Situ Observations from SENEX

Isoprene oxidation schemes vary greatly among gas-phase chemical mechanisms, with potentially significant ramifications for air quality modeling and interpretation of satellite observations in biogenic-rich regions. In this study, in situ observations from the 2013 SENEX mission are combined with a constrained O-D photochemical box model to evaluate isoprene chemistry among five commonly used gas-phase chemical mechanisms: CBO5, CB6r2, MCMv3.2, MCMv3.3.1, and a recent version of GEOS-Chem. Mechanisms are evaluated and inter-compared with respect to formaldehyde (HCHO), a high-yield product of isoprene oxidation. Though underestimated by all considered mechanisms, observed HCHO mixing ratios are best reproduced by MCMv3.3.1 (normalized mean bias = -15%), followed by GEOS-Chem (-17%), MCMv3.2 (-25%), CB6r2 (-32%) and CB05 (-33%). Inter-comparison of HCHO production rates reveals that major restructuring of the isoprene oxidation scheme in the Carbon Bond mechanism increases HCHO production by only approx. 5% in CB6r2 relative to CBO5, while further refinement of the complex isoprene scheme in the Master Chemical Mechanism increases HCHO production by approx. 16% in MCMv3.3.1 relative to MCMv3.2. The GEOS-Chem mechanism provides a good approximation of the explicit isoprene chemistry in MCMv3.3.1 and generally reproduces the magnitude and source distribution of HCHO production rates. We analytically derive improvements to the isoprene scheme in CB6r2 and incorporate these changes into a new mechanism called CB6r2-UMD, which is designed to preserve computational efficiency. The CB6r2-UMD mechanism mimics production of HCHO in MCMv3.3.1 and demonstrates good agreement with observed mixing ratios from SENEX (-14%). Improved simulation of HCHO also impacts modeled ozone: at approx. 0.3 ppb NO, the ozone production rate increases approx. 3% between CB6r2 and CB6r2-UMD, and rises another approx. 4% when HCHO is constrained to match observations.

isoprene↗

Why Do Models Overestimate Surface Ozone in the Southeast United States?

Ozone pollution in the Southeast US involves complex chemistry driven by emissions of anthropogenic nitrogen oxide radicals (NO(x) triple bond NO + NO2) and biogenic isoprene. Model estimates of surface ozone concentrations tend to be biased high in the region and this is of concern for designing effective emission control strategies to meet air quality standards. We use detailed chemical observations from the SEAC(exp 4)RS aircraft campaign in August and September 2013, interpreted with the GEOS-Chem chemical transport model at 0.25 deg x 0.3125 deg horizontal resolution, to better understand the factors controlling surface ozone in the Southeast US. We find that the National Emission Inventory (NEI) for NO(x) from the US Environmental Protection Agency (EPA) is too high. This finding is based on SEAC(exp 4)RS observations of NO(x) and its oxidation products, surface network observations of nitrate wet deposition fluxes, and OMI satellite observations of tropospheric NO2 columns. Our results indicate that NEI NO(x) emissions from mobile and industrial sources must be reduced by 30-60%, dependent on the assumption of the contribution by soil NO(x) emissions. Upper-tropospheric NO2 from lightning makes a large contribution to satellite observations of tropospheric NO2 that must be accounted for when using these data to estimate surface NO(x) emissions. We find that only half of isoprene oxidation proceeds by the high-NO(x) pathway to produce ozone; this fraction is only moderately sensitive to changes in NO(x) emissions because isoprene and NO(x) emissions are spatially segregated. GEOS-Chem with reduced NO(x) emissions provides an unbiased simulation of ozone observations from the aircraft and reproduces the observed ozone production efficiency in the boundary layer as derived from a regression of ozone and NO(x) oxidation products. However, the model is still biased high by 6 plus or minus 14 ppb relative to observed surface ozone in the Southeast US. Ozonesondes launched during midday hours show a 7 ppb ozone decrease from 1.5 km to the surface that GEOS-Chem does not capture. This bias may reflect a combination of excessive vertical mixing and net ozone production in the model boundary layer.

Oxidation↗

The Framework for 0-D Atmospheric Modeling (F0AM) v3.1

The Framework for 0-D Atmospheric Modeling(F0AM) is a flexible and user-friendly MATLAB-based platform for simulation of atmospheric chemistry systems. The F0AM interface incorporates front-end configuration of observational constraints and model setups, making it readily adaptable to simulation of photochemical chambers, Lagrangian plumes, and steady-state or time-evolving solar cycles. Six different chemical mechanisms and three options for calculation of photolysis frequencies are currently available. Example simulations are presented to illustrate model capabilities and, more generally, highlight some of the advantages and challenges of 0-D box modeling.

chemistry↗