[1] We use observations from two aircraft during the ICARTT campaign over the eastern United States and North Atlantic during summer 2004, interpreted with a global 3-D model of tropospheric chemistry (GEOS-Chem) to test current understanding of regional sources, chemical evolution, and export of NO x . The boundary layer NO x data provide top-down verification of a 50% decrease in power plant and industry NO x emissions over the eastern United States between 1999 and 2004. Observed NO x concentrations at 8-12 km altitude were 0.55 ± 0.36 ppbv, much larger than in previous U.S. aircraft campaigns (ELCHEM, SUCCESS, SONEX) though consistent with data from the NOXAR program aboard commercial aircraft. We show that regional lightning is the dominant source of this upper tropospheric NO x and increases upper tropospheric ozone by 10 ppbv. Simulating ICARTT upper tropospheric NO x observations with GEOS-Chem requires a factor of 4 increase in modeled NO x yield per flash (to 500 mol/ flash). Observed OH concentrations were a factor of 2 lower than can be explained from current photochemical models, for reasons that are unclear. A NO y -CO correlation analysis of the fraction f of North American NO x emissions vented to the free troposphere as NO y (sum of NO x and its oxidation products) shows observed f = 16 ± 10% and modeled f = 14 ± 9%, consistent with previous studies. Export to the lower free troposphere is mostly HNO 3 but at higher altitudes is mostly PAN. The model successfully simulates NO y export efficiency and speciation, supporting previous model estimates of a large U.S. anthropogenic contribution to global tropospheric ozone through PAN export.

Abstract. Soils have been identified as a major source (∼ 15 %) of global nitrogen oxide (NO x ) emissions. Parameterizations of soil NO x emissions (S NO x ) commonly used in the current generation of chemical transport models were designed to capture mean seasonal behaviour. These parameterizations do not, however, respond quantitatively to the meteorological triggers that are observed to result in pulsed S NO x . Here we present a new parameterization of S NO x implemented within a global chemical transport model (GEOSChem). The parameterization represents available nitrogen (N) in soils using biome specific emission factors, online wet-and dry-deposition of N, and fertilizer and manure N derived from a spatially explicit dataset, distributed using seasonality derived from data obtained by the Moderate Resolution Imaging Spectrometer. Moreover, it represents the functional form of emissions derived from point measurements and ecosystem scale experiments including pulsing following soil wetting by rain or irrigation, and emissions that are a smooth function of soil moisture as well as temperature between 0 and 30 • C. This parameterization yields global above-soil S NO x of 10.7 Tg N yr −1 , including 1.8 Tg N yr −1 from fertilizer N input (1.5 % of applied N) and 0.5 Tg N yr −1 from atmospheric N deposition. Over the United States (US) Great Plains region, S NO x are predicted to comprise 15-40 % of the tropospheric NO 2 column and increase column variability by a factor of 2-4 during the summer months due to chemical fertilizer application and warm temperatures. S NO x enhancements of 50-80 % of the simulated NO 2 column are predicted over the African Sahel during the monsoon onset (April-June). In this region the day-to-day variability of column NO 2 is increased by a factor of 5 due to pulsed-N emissions. We evaluate the model by comparison with observations of NO 2 column density from the Ozone Monitoring Instrument (OMI). We find that the model is able to reproduce the observed interannual variability of NO 2 (induced by pulsed-N emissions) over the US Great Plains. We also show that the OMI mean (median) NO 2 observed during the overpass following first rainfall over the Sahel is 49 % (23 %) higher than in the five days preceding. The measured NO 2 on the day after rainfall is still 23 % (5 %) higher, providing a direct measure of the pulse's decay time of 1-2 days. This is consistent with the pulsing representation used in our parameterization and much shorter than 5-14 day pulse decay length used in current models.

[1] We investigate the impact of climate change on wildfire activity and carbonaceous aerosol concentrations in the western United States. We regress observed area burned onto observed meteorological fields and fire indices from the Canadian Fire Weather Index system and find that May-October mean temperature and fuel moisture explain 24-57% of the variance in annual area burned in this region. Applying meteorological fields calculated by a general circulation model (GCM) to our regression model, we show that increases in temperature cause annual mean area burned in the western United States to increase by 54% by the 2050s relative to the present day. Changes in area burned are ecosystem dependent, with the forests of the Pacific Northwest and Rocky Mountains experiencing the greatest increases of 78 and 175%, respectively. Increased area burned results in near doubling of wildfire carbonaceous aerosol emissions by midcentury. Using a chemical transport model driven by meteorology from the same GCM, we calculate that climate change will increase summertime organic carbon (OC) aerosol concentrations over the western United States by 40% and elemental carbon (EC) concentrations by 20% from 2000 to 2050. Most of this increase (75% for OC and 95% for EC) is caused by larger wildfire emissions with the rest caused by changes in meteorology and for OC by increased monoterpene emissions in a warmer climate. Such an increase in carbonaceous aerosol would have important consequences for western U.S. air quality and visibility.

[1] Nitrogen oxides (NO x ≡ NO + NO 2 ) produced by lightning make a major contribution to the global production of tropospheric ozone and OH. Lightning distributions inferred from standard convective parameterizations in global chemical transport models (CTMs) fail to reproduce observations from the Lightning Imaging Sensor (LIS) and the Optical Transient Detector (OTD) satellite instruments. We present an optimal regional scaling algorithm for CTMs to fit the lightning NO x source to the satellite lightning data in a way that preserves the coupling to deep convective transport. We show that applying monthly scaling factors over $37 regions globally significantly improves the tropical ozone simulation in the GEOS-Chem CTM as compared to a simulation unconstrained by the satellite data and performs equally well to a simulation with local scaling. The coarse regional scaling preserves sufficient statistics in the satellite data to constrain the interannual variability (IAV) of lightning. After processing the LIS data to remove their diurnal sampling bias, we construct a monthly time series of lightning flash rates for 1998-2010 and 35 S-35 N. We find a correlation of IAV in total tropical lightning with El Niño but not with the solar cycle or the quasi-biennial oscillation. The global lightning NO x source AE IAV standard deviation in GEOS-Chem is 6.0 AE 0.5 Tg N yr À1 , compared to 5.5 AE 0.8 Tg N yr À1 for the biomass burning source. Lightning NO x could have a large influence on the IAV of tropospheric ozone because it is released in the upper troposphere where ozone production is most efficient.