Atmospheric Sciences [A]

A23C  MS:Exh Hall B   Tuesday
Evaluation of Air Quality Models and Assessment of Emissions Inventories Using Bottom- Up and Top-Down Approaches IV Posters
Presiding: R A Washenfelder, Cooperative Institute for Research in Environmental Sciences, University of Colorado at Boulder

A23C-1459 

Coupling an ocean wave model with a global aerosol transport model: A sea salt aerosol parameterization perspective

* Witek, M L (mwit@igf.fuw.edu.pl), University of Warsaw Institute of Geophysics, Pasteura 7, Warsaw, 02093, Poland Flatau, P J (pflatau@ucsd.edu), Scripps Institution of Oceanography, University of California, San Diego, 8602 La Jolla Shores Drive, La Jolla, CA 92037, United States Teixeira, J (Teixeira@nurc.nato.int), NATO Undersea Research Centre, Viale San Bartolomeo 400, La Specia, 19126, Italy Westphal, D L (douglas.westphal@nrlmry.navy.mil), Marine Meteorology Division, Naval Research Laboratory, Monterey, 7 Grace Hopper Avenue, Monterey, CA 93943, United States

A new approach to sea salt parameterization is proposed which incorporates wind-wave characteristics into the sea salt emission function and can be employed globally and under swell-influenced conditions. The new source function was applied into Navy Aerosol Analysis and Prediction System model together with predictions from the global wave model Wave Watch III. The squared surface wind velocity U10 and the wave's orbital velocity Vorb=πHs/Tp are shown to be the key parameters in the proposed parameterization. Results of the model simulations are validated against multi-campaign shipboard measurements of the sea salt aerosol. The validations indicate a good correlation between Vorb and the measured surface concentrations. The model simulations with the new parameterization exhibit an improved agreement with the observations when compared to a wind-speed-only approach. The proposed emission parameterization has the potential to improve the simulations of sea salt emission in aerosol transport models.

A23C-1460 

Accuracy of the Operational NOAA-EPA National Air Quality Forecasting System during Summer 2005 and 2006 in Philadelphia

* Huff, A K (huffa@battelle.org), Battelle Memorial Institute, 2101 Wilson Blvd Suite 800, Arlington, VA 22201, United States Ryan, W F (wfr1@psu.edu), Pennsylvania State University, Department of Meteorology, University Park, PA 16802, United States Bahrmann, C P (cbahrmann@psu.edu), Pennsylvania State University, Department of Meteorology, University Park, PA 16802, United States

The NOAA-EPA National Air Quality Forecasting System (NAQFS) is a numerical ozone forecast model that consists of a coupled version of NOAA's North American Mesoscale (NAM)-12 model and EPA's Community Multiscale Air Quality model (CMAQ). NAQFS runs twice daily at 0600 UTC and 1200 UTC and predicts hourly ozone abundances as mixing ratios in units of parts per billion (ppb). Model output is typically processed to provide 1-hour and 8-hour average ozone forecasts that correspond to the national ambient air quality standards (NAAQS) for ozone. Now in its third season as an operational model, NAQFS is designed to assist air quality meteorologists by providing accurate and dependable forecast guidance. Before air quality meteorologists are willing to rely upon a new tool like NAQFS to assist them in preparing forecasts for the public, however, the model must be evaluated in the typical operational setting for air quality forecasting - the metropolitan scale. To address this need, results will be presented from a pilot statistical study of Summer 2005 and 2006 NAQFS performance in the Philadelphia forecast area. The accuracy, bias, and skill of the model has been determined by comparing 8-hour average ozone forecasts from the 1200 UTC run of NAQFS to corresponding observed ozone values. Overall, the model shows the best skill in suburban areas, where ozone levels tend to peak across the metropolitan region. NAQFS was not reliable in 2005 during Code Orange and Red events, when ozone levels were greater than 84 ppb. In 2006, NAQFS accuracy increased during these cases, which was most likely a result of the NAM's changeover from the Eta model to the Weather and Forecasting (WRF) model. The most probable sources of error that impacted NAQFS performance in 2005 and 2006 will be discussed, including shortcomings in emissions databases and poorly characterized atmospheric chemistry. Preliminary results from the 2007 summer ozone season will also be provided.

A23C-1461 

Using the NAME Lagrangian Particle Dispersion model, and aircraft measurements to assess the accuracy of trace gas emission inventories from the U.K.

* O'Sullivan, D A (debbie.osullivan@metoffice.gov.uk), Met Office, FitzRoy Road, Exeter, EX1 3PB, United Kingdom * O'Sullivan, D A (debbie.osullivan@metoffice.gov.uk), University of East Anglia, Earlham road, Norwich, NR4 7TJ, United Kingdom Harrison, M (mark.harrison@metoffice.gov.uk), Met Office, FitzRoy Road, Exeter, EX1 3PB, United Kingdom Ploson, D (d.polson@ceh.ac.uk), Center for Ecology and Hydrology, Bush Estate, Edinburgh, EH26 OQB, United Kingdom Oram, D (d.e.oram@uea.ac.uk), University of East Anglia, Earlham road, Norwich, NR4 7TJ, United Kingdom Reeves, C (c.reeves@uea.ac.uk), University of East Anglia, Earlham road, Norwich, NR4 7TJ, United Kingdom

A top-down approach using a combination of aircraft data and atmospheric dispersion modelling has been used to estimate emissions for 24 halogenated trace gases from the United Kingdom. This has been done using data collected during AMPEP/FLUXEX, a U.K based measurement campaign which took place between April and September 2005. The primary objective relating to this work was to make direct airborne measurements of concentration enhancements within the boundary layer arising from anthropogenic pollution events, and then to use mass balance methods to determine an emission flux. This was done by analysing Whole Air Samples (WAS) collected in the boundary layer upwind and downwind of the UK at frequent intervals around the coast using the technique of gas chromatography mass spectrometry (GCMS). Emissions were then calculated using a simple box-model approach and also using NAME (Numerical Atmospheric-dispersion Modelling Environment) which is a Lagrangian particle model using 3 hourly 3D meteorology fields from the Met Office Unified Model. By using such an approach it is also possible to identify the most likely main source regions in the UK for the compounds measured. Among the trace gases studied are many which through their effects on stratospheric ozone, and their large radiative forcing have a direct impact on global climate such as CFC's 11, 12, 113 and 114, HCFC's 21, 22, 141b and 142b, HFC's 134a and 152a, methyl chloroform, methyl bromide and carbon tetrachloride. Also the emissions of some short lived gases with have direct effects on human health, such as tetrachloroethene, and trichloroethene, have been derived. The UK emissions estimates calculated from this experimental and modelling work are compared with bottom-up and other top-down emission inventories for the UK and Europe. It was found that the estimates from this study were often higher than those in bottom-up emission inventories derived from industry. In addition for a number of trace gases, for example HCFC-21 and the HFC's, there are no accurate emissions estimates available due to privacy laws which in the UK restrict the availability of the production and sales data required to construct bottom-up emission inventories. Therefore for some of the compounds included in this study, this work provides the first available estimate of UK emissions.

A23C-1462 

Esimating the emission of photopollutants from the city of Lagos from aircraft observations

* Evans, M J (mat@env.leeds.ac.uk), School of Earth And Environment, University of Leeds, Leeds, LS6 9JT, United Kingdom Hopkins, J (jk61@york.ac.uk), Department of Chemistry, University of York, York, YO10 5DD, United Kingdom Lee, J (jdl3@york.ac.uk), Department of Chemistry, University of York, York, YO10 5DD, United Kingdom Lewis, A (acl5@york.ac.uk), Department of Chemistry, University of York, York, YO10 5DD, United Kingdom Marsham, J (jmarsham@leeds.ac.uk), School of Earth And Environment, University of Leeds, Leeds, LS6 9JT, United Kingdom Parker, D (doug@env.leeds.ac.uk), School of Earth And Environment, University of Leeds, Leeds, LS6 9JT, United Kingdom Stewart, D (D.Stewart@uea.ac.uk), School of Environment, University of East Anglia, Norwich, NR4 7TJ, United Kingdom Capes, G (gerard.capes@postgrad.manchester.ac.uk), School of Earth, Atmospheric and Environmental Sciences, University of Manchester, Manchester, M13 9PL, United Kingdom Williams, P (paul.i.williams@manchester.ac.uk), School of Earth, Atmospheric and Environmental Sciences, University of Manchester, Manchester, M13 9PL, United Kingdom Crosier, J (J.Crosier@manchester.ac.uk), School of Earth, Atmospheric and Environmental Sciences, University of Manchester, Manchester, M13 9PL, United Kingdom

The city of Lagos, Nigeria is the second most populated city in Africa and by 2020 is likely to be the most populated. During the AMMA campaign in 2006 the UK BAe146 aircraft flew an orbit around the city observing the concentration of key photo-pollutants. This allowed the fluxes and thus emissions from the city to be calculated. We calculate CO, NOx and VOC emissions to be on the order of 1 Tg (CO) yr-1, 0.01 Tg (N) yr-1, 0.2 Tg (VOC) yr-1 respectively. Based upon a principal components analysis of the observations we split the emissions due to evaporative, low temperature combustion and high temperature combustion.

A23C-1463 

Investigation of properties of biomass and wildfires to improve global estimates of biomass burning emissions

* Shcherbyna Petrenko, M (mshcherb@purdue.edu), Purdue University, Department of Earth and Atmospheric Science 550 Stadium Mall Drive, West Lafayette, IN 47907, Chin, M (mian.chin@nasa.gov), NASA Goddard Space Flight Center, Code 613.3, Greenbelt, MD 20771, Diehl, T (thomas.diehl@nasa.gov), NASA Goddard Space Flight Center, Code 613.3, Greenbelt, MD 20771, Kucsera, T (tlk@hyperion.gsfc.nasa.gov), NASA Goddard Space Flight Center, Code 613.3, Greenbelt, MD 20771, Soja, A (a.j.soja@larc.nasa.gov), NASA Langley Research Center, NASA Langley Research Center, Hampton, VA 23681,

Biomass burning emission is one of the largest uncertainties in modeling the spatial and temporal variations of aerosols and their optical properties. Widely used approach used to determine emissions from forest fires involves estimates of burned area, amount of burned biomass and species-specific emission factors. Further transport and distribution of emitted species has also been shown to depend on the emission injection height. Modeled chemical, physical and optical effects of aerosols generated during wildfires depend on concentrations and characteristics of the emitted particles that go as an input into the model. We present here a study of several parameters that determine spatial distribution of biomass-burning emissions, their concentrations and properties. Parameters examined in this project include 1) ecozone-specific carbon consumption, 2) fire severity (low, medium, and high), 3) emission factors for carbonaceous aerosols, 4) diurnal cycle of wildfires, and 5) emission injection height. The resultant emissions from the combinations of the given factors were compared to other sources, such as Global Fire Emission Dataset version 2 (GFEDv2); resultant global distribution if potential emission injection height is compared to the distribution proposed by Dentener et al. (2006) for use in Aerosol Intercomparison experiment (AeroCom). The results of this study will be incorporated into the Goddard Chemistry Aerosol Radiation and Transport (GOCART) model, and potentially other global models, to study the chemistry, transport, and air quality and climate effects of biomass burning emissions.

A23C-1464 

Observational Evaluation of Mobile Source Emissions

* Frost, G J (Gregory.J.Frost@noaa.gov), NOAA Earth System Research Laboratory, Chemical Sciences Division, 325 Broadway, R/CSD4, Boulder, CO 80305, United States * Frost, G J (Gregory.J.Frost@noaa.gov), University of Colorado, Cooperative Institute for Research in Environmental Sciences, CB216, Boulder, CO 80309, United States McKeen, S (Stuart.A.McKeen@noaa.gov), NOAA Earth System Research Laboratory, Chemical Sciences Division, 325 Broadway, R/CSD4, Boulder, CO 80305, United States McKeen, S (Stuart.A.McKeen@noaa.gov), University of Colorado, Cooperative Institute for Research in Environmental Sciences, CB216, Boulder, CO 80309, United States Trainer, M (Michael.K.Trainer@noaa.gov), NOAA Earth System Research Laboratory, Chemical Sciences Division, 325 Broadway, R/CSD4, Boulder, CO 80305, United States Aikin, K (Kenneth.C.Aikin@noaa.gov), NOAA Earth System Research Laboratory, Chemical Sciences Division, 325 Broadway, R/CSD4, Boulder, CO 80305, United States Aikin, K (Kenneth.C.Aikin@noaa.gov), University of Colorado, Cooperative Institute for Research in Environmental Sciences, CB216, Boulder, CO 80309, United States Peischl, J (Jeff.Peischl@noaa.gov), NOAA Earth System Research Laboratory, Chemical Sciences Division, 325 Broadway, R/CSD4, Boulder, CO 80305, United States Peischl, J (Jeff.Peischl@noaa.gov), University of Colorado, Cooperative Institute for Research in Environmental Sciences, CB216, Boulder, CO 80309, United States Ryerson, T (Thomas.B.Ryerson@noaa.gov), NOAA Earth System Research Laboratory, Chemical Sciences Division, 325 Broadway, R/CSD4, Boulder, CO 80305, United States Holloway, J (John.S.Holloway@noaa.gov), NOAA Earth System Research Laboratory, Chemical Sciences Division, 325 Broadway, R/CSD4, Boulder, CO 80305, United States Holloway, J (John.S.Holloway@noaa.gov), University of Colorado, Cooperative Institute for Research in Environmental Sciences, CB216, Boulder, CO 80309, United States Petron, G (Gabrielle.Petron@noaa.gov), NOAA Earth System Research Laboratory, Global Monitoring Division, 325 Broadway, R/GMD1, Boulder, CO 80305, United States Petron, G (Gabrielle.Petron@noaa.gov), University of Colorado, Cooperative Institute for Research in Environmental Sciences, CB216, Boulder, CO 80309, United States Tans, P (Pieter.Tans@noaa.gov), NOAA Earth System Research Laboratory, Global Monitoring Division, 325 Broadway, R/GMD1, Boulder, CO 80305, United States Harley, R (harley@ce.berkeley.edu), University of California, Department of Civil and Environmental Engineering, Berkeley, CA 94720-1710, United States

Ambient ratios of NOx, CO, and CO2 sampled by aircraft in Houston and Dallas during the 2000 and 2006 Texas Air Quality Study (TexAQS) are compared with each other and with observations at a Houston highway tunnel. From these measurements we estimate 2000 and 2006 emissions for Houston and Dallas mobile sources. The observations demonstrate time-of-day variations in the relative contributions from gasoline and diesel combustion which are consistent with known traffic patterns. We incorporate CO2 emissions derived from the Federal Highway Administration's motor vehicle fuel use statistics into the EPA's National Emission Inventory (NEI), resulting in an emission data set for NOx, CO, and CO2 with 4-km spatial and hourly temporal resolution. Comparison of the emission ratios derived from the TexAQS observations with this inventory allows a direct evaluation of the NEI mobile source NOx and CO emissions.

A23C-1465 

Evidence of a Late-Summer Decrease in NOx/CO Emission Ratios From Boreal Fires

* Lapina, K (klapina@mtu.edu), Civil and Environmental Engineering Department, Michigan Technological University, 1400 Townsend Drive, Houghton, MI 49931, United States Honrath, R (reh@mtu.edu), Civil and Environmental Engineering Department, Michigan Technological University, 1400 Townsend Drive, Houghton, MI 49931, United States Owen, C (rcowen@mtu.edu), Civil and Environmental Engineering Department, Michigan Technological University, 1400 Townsend Drive, Houghton, MI 49931, United States Val Martin, M (mvalmart@mtu.edu), Atmospheric Chemistry Modeling Group, Division of Engineering and Applied Sciences, Harvard University, Pierce Hall, 29 Oxford St., Cambridge, MA 02138-2901, United States Hyer, E J (edward.hyer@nrlmry.navy.mil), Naval Research Lab, Marine Meteorology Division, 7 Grace Hopper Avenue, Monterey, CA 93943, United States Fialho, P (fialho.paulo@gmail.com), Climate, Meteorology and Global Change Center, Group of Chemistry and Physics of the Atmosphere, University of the Azores, Terra Chã, PT9701-851, Portugal Barata, F (barataf@gmail.com), Climate, Meteorology and Global Change Center, Group of Chemistry and Physics of the Atmosphere, University of the Azores, Terra Chã, PT9701-851, Portugal

NOx emissions from boreal fires are critical to ozone production, but their accurate estimation is currently not possible, due to large uncertainties in emission factors. In this work, we use measurements of CO and NOy at the free tropospheric Pico Mountain observatory in the central North Atlantic during the active boreal fire seasons of 2004 and 2005 to constrain NOx/CO emission ratios in North American boreal fires. Observed ΔNOy/ΔCO enhancement ratios in aged boreal fire plumes indicate that NOx/CO emission ratios declined significantly as the fire season progressed. This is consistent with our understanding that an increased amount of fuel is consumed via smoldering combustion during late summer, as deeper burning of the drying organic soil layer occurs, leading to an overall increase in CO and a decrease in NOx fire emission factors. A major growth in overall fuel consumption in the late summer is also expected, due to deeper burning. Emissions of CO and NOx from the 2004 and 2005 North American boreal fires were estimated using the Boreal Wildland-Fire Emissions Model, taking into account this late-summer increase in depth of burning. The long-range transport of these emissions to the sampling site was modeled using FLEXPART. These simulations were generally consistent with the observations, but the modeled seasonal decline in the ΔNOy/ΔCO enhancement ratio was less than observed. Comparisons using alternative fire emission injection height scenarios suggest that plumes with the highest CO levels at the Pico Mountain observatory resulted from large fires where emissions were lofted well above the boundary layer.

A23C-1466 

Applications of Satellite Remote Sensing Data for Biogenic Emission Estimates in Southeastern Texas

* Feldman, M S (feldman@che.utexas.edu), Center for Energy and Environmental Resources University of Texas at Austin, 10100 Burnet Road, Bldg. 133, R7100, Austin, TX 78758, Howard, T), Center for Space Research University of Texas at Austin, 3925 West Braker Lane, Suite 200, Austin, Tx 78759, Mullins, G), Center for Space Research University of Texas at Austin, 3925 West Braker Lane, Suite 200, Austin, Tx 78759, McDonald-Buller, E (ecmb@mail.utexas.edu), Center for Energy and Environmental Resources University of Texas at Austin, 10100 Burnet Road, Bldg. 133, R7100, Austin, TX 78758, Allen, D T (allen@che.utexas.edu), Center for Energy and Environmental Resources University of Texas at Austin, 10100 Burnet Road, Bldg. 133, R7100, Austin, TX 78758,

Biogenic hydrocarbons, including isoprene, monoterpenes, and oxygenated compounds, are emitted in substantial quantities by vegetation and dominate the overall volatile organic compound emission inventory in Southeastern Texas. Spatial distributions of biogenic emissions in Texas are heterogeneous, and biogenic emission processes are affected by the characterization of land cover, leaf area index, drought stress, and surface temperatures. On a regional scale, biogenic emissions, particularly isoprene, in the presence of high levels of nitrogen oxides (NOx), will produce elevated ground-level ozone concentrations. The sensitivity of biogenic emission estimates and air quality model predictions to the characterization of land use/land cover (LULC) in southeastern Texas is examined. A LULC database has been developed for the region based on source imagery collected by the Landsat 7 Enhanced Thematic Mapper-Plus sensor between 1999 and 2003, and data from field studies used for species identification and quantification of biomass densities. This database and the LULC database currently used in regulatory air quality models by the State of Texas are compared. Effects of the LULC data on biogenic emission estimates and modeled ozone concentrations are examined using the Global Biosphere Emissions and Interactions System and the Comprehensive Air Quality Model with extensions during an August 22-September 6, 2000 episode developed for the Houston/Galveston area. These results are also compared to biogenic emission estimates from the recently created Model of Emissions of Gases and Aerosols from Nature (MEGAN), which includes a global vegetation map compiled from recent satellite data and ecosystem inventories. Biogenic emissions estimated from the new LULC dataset showed good general spatial agreement with those from the currently used LULC dataset but significantly lower emissions (~40% less hourly emissions across the modeling domain), primarily due to differences in biomass density of key species like Quercus (Oak). Predicted ozone concentrations using the biogenic emissions produced from the new LULC dataset are as much as 25 ppb lower in some areas on some days, depending on meteorological conditions. Along with coordinated data collection during the Texas Air Quality Study II (TexAQS II), this study demonstrates how satellite remote sensing data can be applied in air quality models and assessments to provide new insights on the magnitude and spatial distribution of biogenic hydrocarbons. Satellite data and image classification techniques provide useful tools for mapping and monitoring changes in LULC. However, field validation is necessary to link species and biomass densities to the classification system used for accurate biogenic emissions estimates, especially in areas such as riparian corridors that contain concentrations of key species.

A23C-1467 

Aerosol Analysis with the High Resolution Time-of-Flight Aerosol Mass Spectrometer at the Urban SuperSite (T0) in Mexico City during MILAGRO

* Aiken, A C (allison.aiken@colorado.edu), Dept. of Chemistry, University of Colorado, 215 UCB, Boulder, CO 80309, United States * Aiken, A C (allison.aiken@colorado.edu), CIRES, CU-Boulder, 216 UCB, Boulder, CO 80309, United States Salcedo, D (dara@ciq.uaem.mx), Centro de Investigaciones Quimicas, U. Autonoma del Estado de Morelos, Cuernavaca, 62209, Mexico Huffman, J A (alex.huffman@colorado.edu), Dept. of Chemistry, University of Colorado, 215 UCB, Boulder, CO 80309, United States Huffman, J A (alex.huffman@colorado.edu), CIRES, CU-Boulder, 216 UCB, Boulder, CO 80309, United States Ulbrich, I (ingrid.ulbrich@colorado.edu), Dept. of Chemistry, University of Colorado, 215 UCB, Boulder, CO 80309, United States Ulbrich, I (ingrid.ulbrich@colorado.edu), CIRES, CU-Boulder, 216 UCB, Boulder, CO 80309, United States DeCarlo, P F (peter.decarlo@colorado.edu), CIRES, CU-Boulder, 216 UCB, Boulder, CO 80309, United States DeCarlo, P F (peter.decarlo@colorado.edu), ATOC, CU-Boulder, 311 UCB, Boulder, CO 80309, United States Cubison, M (michael.cubison@colorado.edu), CIRES, CU-Boulder, 216 UCB, Boulder, CO 80309, United States Docherty, K (kenneth.docherty@colorado.edu), CIRES, CU-Boulder, 216 UCB, Boulder, CO 80309, United States Sueper, D (donna.sueper@colorado.edu), CIRES, CU-Boulder, 216 UCB, Boulder, CO 80309, United States Sueper, D (donna.sueper@colorado.edu), Aerodyne Research, 45 Manning Rd., Billerica, MA 01821, United States Worsnop, D R (worsnop@aerodyne.com), Aerodyne Research, 45 Manning Rd., Billerica, MA 01821, United States Trimborn, A (trimborn@aerodyne.com), Aerodyne Research, 45 Manning Rd., Billerica, MA 01821, United States Northway, M (mnorthway@aerodyne.com), Aerodyne Research, 45 Manning Rd., Billerica, MA 01821, United States Prevot, A (andre.prevot@psi.ch), Paul Scherrer Institut, 5232 Villigen, PSI, 0000, Switzerland Szidat, S (soenke.szidat@iac.unibe.ch), Paul Scherrer Institut, 5232 Villigen, PSI, 0000, Switzerland Szidat, S (soenke.szidat@iac.unibe.ch), U. of Bern, 3012, Bern, 0000, Switzerland Wehrli, M N), U. of Bern, 3012, Bern, 0000, Switzerland Wiedinmyer, C (christin@ucar.edu), NCAR, P.O. Box 3000, Boulder, CO 80307, United States Wang, J (jian@bnl.gov), BNL, P.O. Box 5000, Upton, NY 11973, United States Zheng, J (junzheng@ariel.met.tamu.edu), Texas A&M, 3150 TAMU, College Station, TX 77843, United States Fortner, E (edfornter@tamu.edu), Texas A&M, 3150 TAMU, College Station, TX 77843, United States Zhang, R (zhang@ariel.met.tamu.edu), Texas A&M, 3150 TAMU, College Station, TX 77843, United States Gaffney, J S (jsgaffney@ualr.edu), U. Arkansas, 2801 S. University Avenue, Little Rock, AR 72204, United States Marley, N A (namarley@ualr.edu), U. Arkansas, 2801 S. University Avenue, Little Rock, AR 72204, United States Sosa Iglesias, G E (gsosa@imp.mx), IMP, Eje Central Norte Lazaro Cardenas 152, Mexico City, D.F 07730, Mexico Jimenez, J L (jose.jimenez@colorado.edu), Dept. of Chemistry, University of Colorado, 215 UCB, Boulder, CO 80309, United States Jimenez, J L (jose.jimenez@colorado.edu), CIRES, CU-Boulder, 216 UCB, Boulder, CO 80309, United States

Non-refractory submicron (approx. PM1) ambient aerosol was analyzed from March 10 - 30, 2006 in Mexico City at the T0 (IMP) urban supersite with the High-Resolution Time-of-Flight Aerosol Mass Spectrometer (HR-ToF-AMS, DeCarlo et al., 2006). The HR-ToF-AMS can resolve the elemental composition of most mass fragments, especially for the low m/z (below 100) where the majority of the signal occurs in the AMS when using electron ionization (EI). Mass concentrations and size distributions of inorganic species (Ammonium, Chloride, Nitrate, Sulfate) are similar to results from MCMA-2003 (Salcedo et al., 2006). Positive Matrix Factorization (PMF) analysis of the Organic mass indicates that primary emissions and urban SOA formation are important for this dataset, while the impact of large biomass burning plumes is more episodic and correlates with satellite fire counts. A regional highly oxygenated organic aerosol is also observed. C-14 filter analysis results are generally consistent with the PMF results. Organic amines are detected in the aerosol during some mornings. Lead is also detected and correlates well with measurements from other techniques. The chemically-resolved aerosol volatility is characterized using a thermal denuder in front of the AMS. A new organic elemental analysis technique developed by our group is also applied to the organic aerosol (Aiken et al., 2007) to determine the oxygen-to-carbon (O/C) and organic mass to organic carbon (OM/OC) ratios.

A23C-1468 

Herbivory As A Driver For Biogenic Methanol Flux From North American Temperate Tree Species

* Oikawa, P (pyo6n@virginia.edu), University of Virginia, Department of Biology P.O. Box 400328, Charlottesville, VA 22904, United States Lerdau, M (mlerdau@virginia.edu), University of Virginia, Department of Biology P.O. Box 400328, Charlottesville, VA 22904, United States Mak, J (jemak@notes.cc.sunysb.edu), SUNY at Stony Brook, Marine and atmospheric sciences Stony Brook University, Stony Brook, NY 11794, United States

Ecological relationships of plants and herbivores have implications for biosphere-atmosphere interactions. For instance, plant monoterpene emission response to herbivory can significantly impact air quality /(Litvak et al. /(1999/) Ecol. Appl. 9/(4/):1147-1159/). Studies on biogenic methanol emission response to herbivory have observed significant methanol emissions directly following herbivore attack and even larger emissions 24hrs later /(Penuelas et al. /(2005/) New Phytol. 167:851-857/). We investigated gypsy moth defoliation impacts on methanol emissions in the abundant North American temperate tree species big tooth aspen Populus grandidentata. Specifically, we measured methanol emission response to herbivory on both short and long time scales at a field site in northern Michigan. Our results suggest herbivory can significantly increase methanol emissions on both short and long time scales. Unlike previous investigations, we did not observe methanol emissions 24hrs post-attack to be significantly higher than emissions detected directly following attack. When compared to mechanical wounding, herbivory did not elicit a quantitatively different methanol emission response in this species. These results suggest that herbivory in temperate forests may be an important driver for biogenic methanol flux and may therefore be helpful in improving models of methanol dynamics.

A23C-1469 

PIT-MS Measurements of VOCs at a Suburban Ground Site (T1) in Mexico City During the MILAGRO 2006 Campaign: Emission Ratios and Source Apportionment

* Welsh-Bon, D (daniel.welshbon@noaa.gov), NOAA Earth System Research Laboratory, DSRC, Bldg 33 325 Broadway, Boulder, CO 80305-3328, United States * Welsh-Bon, D (daniel.welshbon@noaa.gov), Cooperative Institute for Research in Environmental Sciences, University of Colorado 216 UCB, Boulder, CO 80309-0216, United States Warneke, C (carsten.warneke@noaa.gov), NOAA Earth System Research Laboratory, DSRC, Bldg 33 325 Broadway, Boulder, CO 80305-3328, United States Warneke, C (carsten.warneke@noaa.gov), Cooperative Institute for Research in Environmental Sciences, University of Colorado 216 UCB, Boulder, CO 80309-0216, United States de Gouw, J A (Joost.DeGouw@noaa.gov), NOAA Earth System Research Laboratory, DSRC, Bldg 33 325 Broadway, Boulder, CO 80305-3328, United States de Gouw, J A (Joost.DeGouw@noaa.gov), Cooperative Institute for Research in Environmental Sciences, University of Colorado 216 UCB, Boulder, CO 80309-0216, United States Kuster, W (William.C.Kuster@noaa.gov), NOAA Earth System Research Laboratory, DSRC, Bldg 33 325 Broadway, Boulder, CO 80305-3328, United States Vargas, O (olvargas@gatech.edu), Georgia Institute of Technology, Georgia Institute of Technology, Atlanta, GA 30332, United States Huey, G (greg.huey@eas.gatech.edu), Georgia Institute of Technology, Georgia Institute of Technology, Atlanta, GA 30332, United States Jimenez, J L (jose.jimenez@colorado.edu), Cooperative Institute for Research in Environmental Sciences, University of Colorado 216 UCB, Boulder, CO 80309-0216, United States Ulbrich, I M (Ingrid.Ulbrich@colorado.edu), Cooperative Institute for Research in Environmental Sciences, University of Colorado 216 UCB, Boulder, CO 80309-0216, United States

Volatile organic compounds (VOCs) were measured by several different methods at a suburban ground site (T1) in Mexico City located approximately 30 km north east of the city center during the MILAGRO campaign in March, 2006. Small alkanes and alkenes were measured using an on-line gas chromatography instrument with flame- ionization detection (GC-FID) and by canister collection and subsequent GC analysis. Aromatic hydrocarbons and oxygenated VOCs were quantified by proton-transfer ion-trap mass spectrometry (PIT-MS). For most measured species, a strong diurnal variation was observed with very high mixing ratios at night when VOC emissions accumulated in a shallow boundary layer, and lower mixing ratios during the day when VOCs were mixed in a deeper boundary layer and were removed by photochemistry. However, diurnal patterns in VOC measurements were substantially different for oxygenated VOCs. Emission ratios with CO for the primary VOC emissions are determined for Mexico City and compared to typical values observed for cities in the United States. It was found that the VOC emission ratios are generally higher in Mexico City. Positive Matrix Factorization (PMF) analysis can be used to evaluate differences in diurnal cycles between primary and secondary chemical species. PMF clearly distinguishes compounds with only primary emissions (e.g. alkanes, alkenes, and aromatics) from oxygenated species (e.g. acetaldehyde, acetone), which have both direct emission sources and a large proportion of secondary formation. It also groups both primary and secondary species by their reactivities/lifetimes. Finally, PMF can be used to provide chemical information about unknown ions (for m/z's contributing to PIT-MS signal but not typically monitored by PTR-MS) into these categories, facilitating their chemical identification.

A23C-1470 

Simulating Inorganic Aerosol Components Using ISORROPIA II in a Chemical Transport Model (PMCAMx) - Evaluation for the MILAGRO Campaign 2006 in Mexico City

* Karydis, V A (vlkarydis@chemeng.upatras.gr), Dept. of Chemical Engineering, University of Patras, 1 Karatheodori,Rio, Patra, 26504, Greece Tsimpidi, A P (tsimpidi@chemeng.upatras.gr), Dept. of Chemical Engineering, University of Patras, 1 Karatheodori,Rio, Patra, 26504, Greece Nenes, A (nenes@eas.gatech.edu), School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, 311 Ferst Drive, Atlanta, GA 30332-0100, United States Nenes, A (nenes@eas.gatech.edu), School of Earth and Atmospheric Sciences, Georgia Institute of Technology, 311 Ferst Drive, Atlanta, GA 30332-0340, United States Pandis, S N (spyros@chemeng.upatras.gr), Dept. of Chemical Engineering, University of Patras, 1 Karatheodori,Rio, Patra, 26504, Greece Zavala, M (miguelz@MIT.EDU), Dept. of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology (MIT), 77 Massachusetts Avenue, Cambridge, MA 02139, United States Zavala, M (miguelz@MIT.EDU), Molina Center for Energy and the Environment (MCE2), 3262 Holiday Ct., Suite 2001, La Jolla, CA 92037, United States Lei, W (wflei@MIT.EDU), Dept. of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology (MIT), 77 Massachusetts Avenue, Cambridge, MA 02139, United States Lei, W (wflei@MIT.EDU), Molina Center for Energy and the Environment (MCE2), 3262 Holiday Ct., Suite 2001, La Jolla, CA 92037, United States Molina, L T (ltmolina@MIT.EDU), Dept. of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology (MIT), 77 Massachusetts Avenue, Cambridge, MA 02139, United States Molina, L T (ltmolina@MIT.EDU), Molina Center for Energy and the Environment (MCE2), 3262 Holiday Ct., Suite 2001, La Jolla, CA 92037, United States

Aerosols have a significant role in the atmosphere having adverse impacts on human health and directly affecting air quality, visibility and climate change. One of the most challenging tasks for the available models is the prediction of the partitioning of the semivolatile inorganic aerosol components (ammonia, nitric acid, hydrochloric acid, etc) between the gas and aerosol phases. Moreover, the effects of mineral aerosols in the atmosphere remain largely unquantified. As a result, most current models have serious difficulties in reproducing the observed particulate nitrate and chloride concentrations. The aerosol thermodynamic model ISORROPIA has been improved as it now simulates explicitly the chemistry of Ca, Mg, and K salts and is linked to PMCAMx (Gaydos et al., 2007). PMCAMx also includes the inorganic aerosol growth module (Gaydos et al., 2003; Koo et al., 2003a) and the aqueous-phase chemistry module (Fahey and Pandis, 2001). The hybrid approach (Koo et al., 2003b) for modeling aerosol dynamics is applied in order to accurately simulate the inorganic components in coarse mode. This approach assumes that the smallest particles are in equilibrium while the condensation/evaporation equation is solved for the larger ones. PMCAMx is applied in Mexico City Metropolitan Area (MCMA) covering a 180x180x6 km region. The emission inventory used has as a starting point the MCMA 2004 official emissions inventory (CAM, 2006) and includes more accurate dust and NaCl emissions. The March 2006 dataset (MILAGRO Campaign) is used to evaluate the inorganic aerosol module of PMCAMx in order to test our understanding of aerosol thermodynamics and the equilibrium assumption. Gaydos, T., Pinder, R., Koo, B., Fahey, Κ., Yarwood, G., and Pandis, S. N., (2007). Development and application of a three-dimensional Chemical Transport Model, PMCAMx. Atmospheric Environment, 41, 2594- 2611. Gaydos, T., Koo, B., and Pandis, S. N., (2003). Development and application of an efficient moving sectional approach for the solution of the atmospheric aerosol condensation/evaporation equations. Atmospheric Environment, 37, 3303-3316. Fahey, K. and Pandis, S. N., (2001). Optimizing model performance: variable size resolution in cloud chemistry modelling. Atmospheric Environment 35, 4471-4478. Koo, B., Pandis S. N., and Ansari, A. (2003a). Integrated approaches to modelling the organic and inorganic atmospheric aerosol components. Atmospheric Environment, 37, 4757-4768. Koo, B., Gaydos, T.M., Pandis, S.N., (2003b). Evaluation of the equilibrium, hybrid, and dynamic aerosol modeling approaches. Aerosol Science and Technology 37, 53–64.

A23C-1471 

Eddy Covariance Flux Measurements of Urban Aerosols During the MILAGRO Mexico City Field Campaign

* Grivicke, R (rgrivicke@mail.wsu.edu), Washington State University, Dept of Civil & Environmental Engineering, Pullman, WA 99164-2910, United States Pressley, S (spressle@wsu.edu), Washington State University, Dept of Civil & Environmental Engineering, Pullman, WA 99164-2910, United States Jimenez, J (jose.jimenez@colorado.edu), Dept. of Chemistry & CIRES, University of Colorado, Boulder, CO 80309, United States Nemitz, E (en@ceh.ac.uk), Centre for Ecology and Hydrology, Penicuik, Midlothian, EH26 0QB, United Kingdom Alexander, L (lizabeth.alexander@pnl.gov), Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA 99352, United States Velasco, E (evalasco@mce2.org), Molina Center for Energy and the Environment, La Jolla, La Jolla, CA 92037, United States Allwine, E (allwineg@wsu.edu), Washington State University, Dept of Civil & Environmental Engineering, Pullman, WA 99164-2910, United States Jobson, T (tjobson@wsu.edu), Washington State University, Dept of Civil & Environmental Engineering, Pullman, WA 99164-2910, United States Westberg, H (westberg@mail.wsu.edu), Washington State University, Dept of Civil & Environmental Engineering, Pullman, WA 99164-2910, United States Ramos, R (rramos@clintonfoundation.org), Sistema de Monitorea Atmosferico de la Ciudad de Mexico, D.F., Mexico City, D.F 11800, Mexico Molina, L (ltmolina@mit.edu), Molina Center for Energy and the Environment, La Jolla, La Jolla, CA 92037, United States Lamb, B (blamb@wsu.edu), Washington State University, Dept of Civil & Environmental Engineering, Pullman, WA 99164-2910, United States

Expansive urban development in the fast growing number of megacities around the world raises concerns regarding the pollution levels in such sites. The Mexico City MILAGRO 2006 (Megacity Initiative: Local and Global Research Observations) field campaign was a worldwide initiative aiming to understand sources, chemical nature and evolution of pollution in one of the largest urban developments. As part of the MILAGRO campaign, urban fluxes of aerosols and related trace gases were measured near the centre of Mexico City at 42 m above street level. Aerosol concentrations (1 min. averages) and aerosol fluxes (10 Hz, selected ion monitoring) were measured with an Aerodyne quadrupole aerosol mass spectrometer operated in an alternating 30 minute mode of ambient concentrations and fluxes. The fluxes were derived using eddy covariance calculations. The aerosol flux data were supported by additional flux measurements of CO2 and a number of gas phase VOC species using a combination of techniques, including Proton Transfer Reaction Mass Spectrometry using a disjunct eddy covariance technique and GC-FID analysis of samples from a disjunct eddy accumulation sampler. Preliminary results of aerosol concentrations and flux measurements indicate that the urban landscape is a significant source of organic aerosols.

A23C-1472 

A New Direct Coupled Regional-scale Meteorology and Chemistry Model

* Li, J (lijing@rias.atm.nacu.edu.tw), The Institute of Atmospheric Physics National Central University, No.300, Jhongda Rd., Jhongli, 320, Taiwan Hsu, S (garyhsu@rias.atm.ncu.edu.tw), The Institute of Atmospheric Physics National Central University, No.300, Jhongda Rd., Jhongli, 320, Taiwan Liu, T (tliu@cc.ncu.edu.tw), The Institute of Atmospheric Physics National Central University, No.300, Jhongda Rd., Jhongli, 320, Taiwan Chiang, C (chiang@rias.atm.ncu.edu.tw), The Institute of Atmospheric Physics National Central University, No.300, Jhongda Rd., Jhongli, 320, Taiwan Chang, J (julius@ncu.edu.tw), The Institute of Atmospheric Physics National Central University, No.300, Jhongda Rd., Jhongli, 320, Taiwan

WRF/Chem was first developed in the US and generously made available to the international research community a short time ago. Starting from this, many groups have contributed new components and subroutines to this model. Based on WRF/Chem, a new online integrated model system named WRF/ChemT was established in Taiwan. It is significantly different from WRF/Chem in the following important aspects. For an online model, all chemical species emission must be direct coupled to WRF meteorology. All publicly available versions of WRF/Chem do not have this fundamental coupling. For these WRF/Chem models all emission data must first be preprocessed by SMOKE or other emission models driven by MM5 or WRF meteorologies in offline manner. WRF/ChemT has a self-consistent online emission process. We replaced the old emission driver with NCU driver, the plume rise of point sources and biogenic VOCs emission are calculated online. So that meteorology model, emission model and chemistry transport model are coupled directly in WRF/ChemT. Cloud impact on actinic flux should be consistent with WRF cloud-aerosol submodel used, not just moisture parameterization. Photolysis rates in WRF/ChemT are self consistent in every sub modules. New dry deposition routines were developed including addition of a vertical mixing scheme named the Asymmetrical Convective Model (ACM) which is used in CMAQ. The advantage of using ACM submodel had been demonstrated in earlier studies. Computational inefficiency has been a lingering problem for WRF/Chem. We have worked on this aspect of WRF/Chem development and by using a new chemical solver and also reorganizing the operator splitting computational algorithm we have made significant computational speed gain. WRF/chemT is about a factor of 4 faster in the chemistry solver and a factor of 2 faster in chemical species transport. When added together it is about a factor of 2 faster than WRF/Chem(version 2.1.2), i. e. gas-phase chemistry and meteorology are now equally fast. WRF/ChemT was evaluated and applied in regional air quality research in Taiwan. The comparison with WRF/Chem and selected current applications will be discussed in this report.

A23C-1473 

Analysis of Air Toxics From NOAA WP-3 Aircraft Measurements During the TexAQS 2006 Campaign: Comparison With Emission Inventories and Additive Inhalation Risk Factors

* Del Negro, L A (delnegro@lakeforest.edu), Lake Forest College, 555 N Sheridan Rd, Lake Forest, IL 60045, United States Warneke, C (Carsten.Warneke@noaa.gov), NOAA, ESRL, Chemical Sciences Division, 325 Broadway RCSD7, Boulder, CO 80305, United States Warneke, C (Carsten.Warneke@noaa.gov), Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO 80309, United States de Gouw, J A (Joost.deGouw@noaa.gov), NOAA, ESRL, Chemical Sciences Division, 325 Broadway RCSD7, Boulder, CO 80305, United States de Gouw, J A (Joost.deGouw@noaa.gov), Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO 80309, United States Atlas, E (eatlas@rsmas.miami.edu), Rosenstiel School of Marine & Atmospheric Science, University of Miami, Miami, FL 33149, United States Lueb, R (rlueb@rsmas.miami.edu), Rosenstiel School of Marine & Atmospheric Science, University of Miami, Miami, FL 33149, United States Zhu, X (xzhu@rsmas.miami.edu), Rosenstiel School of Marine & Atmospheric Science, University of Miami, Miami, FL 33149, United States Pope, L (lpope@rsmas.miami.edu), Rosenstiel School of Marine & Atmospheric Science, University of Miami, Miami, FL 33149, United States Schauffler, S (sues@ucar.edu), Earth Observing Laboratory, National Center for Atmospheric Research, Boulder, CO 80307, United States Hendershot, R (rogerh@ucar.edu), Earth Observing Laboratory, National Center for Atmospheric Research, Boulder, CO 80307, United States Washenfelder, R (Rebecca.Washenfelder@noaa.gov), Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO 80309, United States Fried, A (fried@ucar.edu), Earth Observing Laboratory, National Center for Atmospheric Research, Boulder, CO 80307, United States Richter, D (dr@ucar.edu), Earth Observing Laboratory, National Center for Atmospheric Research, Boulder, CO 80307, United States Walega, J G (walega@ucar.edu), Earth Observing Laboratory, National Center for Atmospheric Research, Boulder, CO 80307, United States Weibring, P (weibring@ucar.edu), Earth Observing Laboratory, National Center for Atmospheric Research, Boulder, CO 80307, United States

Benzene and nine other air toxics classified as human carcinogens by the International Agency for Research on Cancer (IARC) were measured from the NOAA WP-3 aircraft during the TexAQS 2006 campaign. In-situ measurements of benzene, measured with a PTR-MS instrument, are used to estimate emission fluxes for comparison with point source emission inventories developed by the Texas Commission on Environmental Quality. Mean and median mixing ratios for benzene, acetaldehyde, formaldehyde, 1,3-butadiene, carbon tetrachloride, chloroform, 1,2-dichloroethane, dibromoethane, dichloromethane, and vinyl chloride, encountered over the city of Houston during the campaign, are combined with inhalation unit risk factor values developed by the California Environmental Protection Agency and the United States Environmental Protection Agency to estimate the additive inhalation risk factor. This additive risk factor represents the risk associated with lifetime (70 year) exposure at the levels measured and should not be used as an absolute indicator of risk to individuals. However, the results are useful for assessments of changing relative risk over time, and for identifying dominant contributions to the overall air toxic risk.

A23C-1474 

An Examination of NOx, SO2, and CO Emissions from East Texas Power Plants

* Peischl, J (jeff.peischl@noaa.gov), Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO 80309, United States * Peischl, J (jeff.peischl@noaa.gov), NOAA, Earth System Research Laboratory, Chemical Sciences Division, 325 Broadway, Boulder, CO 80305, United States Ryerson, T B (thomas.b.ryerson@noaa.gov), NOAA, Earth System Research Laboratory, Chemical Sciences Division, 325 Broadway, Boulder, CO 80305, United States Holloway, J S (john.s.holloway@noaa.gov), Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO 80309, United States Holloway, J S (john.s.holloway@noaa.gov), NOAA, Earth System Research Laboratory, Chemical Sciences Division, 325 Broadway, Boulder, CO 80305, United States Aikin, K C (kenneth.c.aikin@noaa.gov), Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO 80309, United States Aikin, K C (kenneth.c.aikin@noaa.gov), NOAA, Earth System Research Laboratory, Chemical Sciences Division, 325 Broadway, Boulder, CO 80305, United States Frost, G J (gregory.j.frost@noaa.gov), Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO 80309, United States Frost, G J (gregory.j.frost@noaa.gov), NOAA, Earth System Research Laboratory, Chemical Sciences Division, 325 Broadway, Boulder, CO 80305, United States Fehsenfeld, F C (fred.c.fehsenfeld@noaa.gov), Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO 80309, United States Fehsenfeld, F C (fred.c.fehsenfeld@noaa.gov), NOAA, Earth System Research Laboratory, Chemical Sciences Division, 325 Broadway, Boulder, CO 80305, United States

Emissions from several East Texas power plants were measured from aircraft during the 2000 and 2006 Texas Air Quality Studies. One-second measurements were made of NOy, SO2, CO, and CO2 during these flights. NOy (total reactive nitrogen) is used as a proxy for power plant NOx (NO + NO2) emissions to account for any reactions that may have occurred between emission and measurement. Emission ratios of NOy, SO2, and CO to CO2 were calculated from the closest down-wind transects of plumes from seven power plants. Emission ratios were also calculated with hourly data from the Continuous Emission Monitoring System (CEMS). The aircraft data show substantial (25-80 percent) reductions in NOx emissions from four of the power plants between 2000 and 2006, whereas SO2 and CO emissions from all plants appear to be largely unchanged during this time. Emission ratios calculated from the aircraft and from hourly CEMS data in 2006 agree to within an average of approximately 10 percent, which suggests the CEMS data are a fair representation of power plant emissions.

A23C-1475 

Ozone and PM 2.5 Verification in NAM-CMAQ Modeling System at NCEP

* Tsidulko, M (Marina.Tsidulko@noaa.gov), SAIC(NOAA/NCEP/EMC), 5200 Auth Rd, Camp Springs, MD 20746, United States McQueen, J (Jeff.Mcqueen@noaa.gov), NOAA/NCEP/EMC, 5200 Auth Rd, Camp Springs, MD 20746, United States Lee, P), SAIC(NOAA/NCEP/EMC), 5200 Auth Rd, Camp Springs, MD 20746, United States DiMego, G), NOAA/NCEP/EMC, 5200 Auth Rd, Camp Springs, MD 20746, United States

Verification of ozone predictions from NAM-CMAQ NCEP/EPA Air Quality Forecast System is presented. Daily 1- hour and 8-hours averages, as well as daily peak ozone forecasts are compared with AIRNOW observations. Two versions of the system: operational for East US and experimental for Continental US are compared. Impact of recent changes in both NAM and CMAQ models on air quality forecasts is estimated. Verification is done for summer 2007. Predictions for different sub-regions are evaluated and related to meteorological elements verification. Boundary layer heights evaluation with radiosonde and aircraft data is also presented. Aerosol forecasts from developmental version of the AQ system are verified with AIRNOW observations for several episodes in summer 2007.

A23C-1476 

Contribution of Dust Particles to the Heterogeneous Removal of Acidic Gases From the Atmosphere During the MIRAGE Experiment

* Hodzic, A (alma@ucar.edu), National Center for Atmospheric Research, Atmospheric Chemistry Division, Boulder, CO 80301, United States Flocke, F M (ffl@ucar.edu), National Center for Atmospheric Research, Atmospheric Chemistry Division, Boulder, CO 80301, United States Madronich, S (sasha@ucar.edu), National Center for Atmospheric Research, Atmospheric Chemistry Division, Boulder, CO 80301, United States Fast, J (jerome.fast@pnl.gov), Pacific Northwest National Laboratory, P.O. Box 999, Richland, WA 99352, United States Zheng, W (zheng@ucar.edu), National Center for Atmospheric Research, Atmospheric Chemistry Division, Boulder, CO 80301, United States Weinheimer, A (weinheimer@ncar.edu), National Center for Atmospheric Research, Atmospheric Chemistry Division, Boulder, CO 80301, United States Montzka, D (montzka@ucar.edu), National Center for Atmospheric Research, Atmospheric Chemistry Division, Boulder, CO 80301, United States Knapp, D (david@ucar.edu), National Center for Atmospheric Research, Atmospheric Chemistry Division, Boulder, CO 80301, United States Mauldin, L (mauldin@ncar.edu), National Center for Atmospheric Research, Atmospheric Chemistry Division, Boulder, CO 80301, United States Wennberg, P (wennberg@gps.caltech.edu), California Institute of Technology, 1200 East California Bouldevard, Pasadena California, CA 91125, United States Crounse, J D (crounjd@caltech.edu), California Institute of Technology, 1200 East California Bouldevard, Pasadena California, CA 91125, United States McCabe, D), California Institute of Technology, 1200 East California Bouldevard, Pasadena California, CA 91125, United States Clarke, A (tclarke@soest.hawaii.edu), University of Hawaii, 1000 Pope Road, Honolulu, HI 96822, United States Hostetler, C A (Chris.A.Hostetler@nasa.gov), NASA Langley Research Center, MS 435, Hampton, VA 23681, United States Hair, J W (Johnathan.W.Hair@nasa.gov), NASA Langley Research Center, MS 435, Hampton, VA 23681, United States

The significance of the removal of acidic trace gases via heterogeneous processes, and its influence on the regional budget of several aerosol and gas-phase pollutants, is investigated downwind of Mexico City. According to experimental studies, the uptake of HNO3 onto reactive dust components, such as calcium and magnesium carbonates, results in an irreversible repartitioning of nitrate to a more stable particle phase and represent an important sink for nitrogen oxide species. These reactions are rarely considered in chemistry-transport models, and here we investigate how they can affect models" ability to predict the oxidizing potential of the atmosphere (NOx to NOy ratio), the atmospheric ozone balance, and coarse nitrate aerosol formation. Results from the MIRAGE field campaign show a tendency of lower HNO3 to NOy ratios with increasing dust loading in the Mexico City plume. In general, the HNO3 fraction of total NOy often does not increase with distance from the city which would be expected from gas-phase chemical processing. This evidence for heterogeneous removal is corroborated by ground-based measurements performed during MILAGRO indicating that mineral dust is often associated with coarse nitrate. We introduce this heterogeneous reaction in the WRF-CHEM model and analyze its impact on the formation of nitrogen oxide species, ozone, and coarse aerosol components, by comparison of model simulations with ground and airborne measurements in the vicinity of Mexico City. Several values of the nitric acid uptake coefficient are tested in order to investigate the sensitivity to this parameter. Model performance in simulating nitrates is evaluated with and without the heterogeneous reactions included.

A23C-1477 

Small marine craft emission factors observed from the NOAA R/V Ronald H. Brown during TexAQS/GoMACCS 2006

* Lerner, B M (brian.lerner@noaa.gov), NOAA Earth System Research Laboratory, 325 Broadway R/CSD7, Boulder, CO 80305, * Lerner, B M (brian.lerner@noaa.gov), University of Colorado Cooperative Institute for Research in Environmental Sciences, UCB 216, Boulder, CO 80309-0216, Lack, D (daniel.lack@noaa.gov), NOAA Earth System Research Laboratory, 325 Broadway R/CSD7, Boulder, CO 80305, Lack, D (daniel.lack@noaa.gov), University of Colorado Cooperative Institute for Research in Environmental Sciences, UCB 216, Boulder, CO 80309-0216, Murphy, P C (paul.c.murphy@noaa.gov), NOAA Earth System Research Laboratory, 325 Broadway R/CSD7, Boulder, CO 80305, Murphy, P C (paul.c.murphy@noaa.gov), University of Colorado Cooperative Institute for Research in Environmental Sciences, UCB 216, Boulder, CO 80309-0216, Williams, E J (eric.j.williams@noaa.gov), NOAA Earth System Research Laboratory, 325 Broadway R/CSD7, Boulder, CO 80305, Williams, E J (eric.j.williams@noaa.gov), University of Colorado Cooperative Institute for Research in Environmental Sciences, UCB 216, Boulder, CO 80309-0216,

During the TexAQS/GoMACCS 2006 field campaign, the NOAA R/V Ronald H. Brown often encountered small marine recreational craft and small fishing vessels while sailing close to the Texas coast, especially in Galveston Bay. Measurement of a suite of trace gases at high time resolution (1 Hz) allowed us to calculate emission factors (EFs), relative to carbon dioxide, for nitrogen oxides (NOx), sulfur dioxide (SO2) and carbon monoxide (CO) for distinct exhaust plumes from these sources. Photoacoustic aerosol absorption spectroscopy (PAS) measurements made concurrently allowed for the first quantification of mass EFs for light-absorbing particles from fishing craft. As previously observed along the New England coast, gasoline-powered recreational vessels showed significantly higher NOx/CO2 and lower CO/CO2 EFs than current emissions inventories predict, although in agreement with the most recent published literature of laboratory studies. These findings imply lower volatile organic compound emissions from these vessels, although this was not directly measured.

A23C-1478 

What does the future hold for Mexico City? Trends of emissions from mobile sources in the MCMA

* Zavala, M (miguelz@mit.edu), Massachussetts Institute of Technology, 77 Mass. Av., Cambridge, MA 02139, United States * Zavala, M (miguelz@mit.edu), Molina Center for Energy and the Environment, 3262 Holiday Court, La Jolla, CA 92037, United States Herndon, S), Aerodyne Research Inc, 45 Manning Road, Billerica, MA 01821, United States Wood, E (Ezrawood@aerodyne.com), Aerodyne Research Inc, 45 Manning Road, Billerica, MA 01821, United States Onasch, T (onasch@aerodyne.com), Aerodyne Research Inc, 45 Manning Road, Billerica, MA 01821, United States Knighton, B (bknighton@chemistry.montana.edu), Montana State University, Montana State University P.O. Box 172260, Bozeman, MT 59717, United States Molina, M J (mjmolina@ucsd.edu), University of California, San Diego, 9500 Gilman Dr., La Jolla, CA 92093, United States Kolb, C (kolb@aerodyne.com), Aerodyne Research Inc, 45 Manning Road, Billerica, MA 01821, United States Molina, L T (ltmolina@mit.edu), Massachussetts Institute of Technology, 77 Mass. Av., Cambridge, MA 02139, United States Molina, L T (ltmolina@mit.edu), Molina Center for Energy and the Environment, 3262 Holiday Court, La Jolla, CA 92037, United States

Mobile emission sources represent a significant fraction of the total anthropogenic emissions burden in megacities and have a deleterious effect on air quality at multiple spatial scales. There are, however, large uncertainties involved during the estimation of mobile emissions inventories. During the 2002/2003 MCMA and the 2006 MILAGRO field campaigns in the Mexico City Metropolitan Area (MCMA), the Aerodyne Research Inc. (ARI) Mobile Laboratory characterized on-road vehicle fleet emission indices in fleet-average mode for various vehicle classes and driving speeds using fast-response instrumentation. In 2006 the ARI mobile laboratory was also deployed in various sites across the MCMA for characterizing gases and aerosols using research grade real-time trace gas and fine particulate matter (PM) instruments. In addition to the fixed site measurements, the fast response instrumentation was also used during the transit of the mobile lab between these sites to obtain on-road vehicle emissions data in fleet-average mode. In this work, we present the measurements of emission indices in fleet-average mode taken during the MILAGRO field campaign. Measurements of NOx, CO, key VOC species and particle mass (PM1) and composition from mobile sources in the MCMA are used to validate the official Emissions Inventory. We compare on-road emission measurements from the 2002, 2003 and 2006 field campaigns and other available emission measurement studies. Given the profound changes in the composition of the vehicle fleet in Mexico City over the past two decades, the comparison provides valuable information on the present and future emission trends in the urban area.

A23C-1479 

Evaluation of Bottom-Up Mobile Emissions Inventories in the Upper Midwest

* Spak, S (snspak@wisc.edu), Center for Sustainability and the Global Environment, University of Wisconsin-Madison, 1710 University Avenue, Madison, WI 53726, United States Holloway, T (taholloway@wisc.edu), Center for Sustainability and the Global Environment, University of Wisconsin-Madison, 1710 University Avenue, Madison, WI 53726, United States Mednick, A (mednick@wisc.edu), Department of Urban and Regional Planning, University of Wisconsin-Madison, 925 Bascom Mall, Madison, WI 53706, United States Stone, B (Brian.Stone@coa.gatech.edu), City and Regional Planning Program, Georgia Institute of Technology, 247 4th Street, Atlanta, GA 30332-0155, United States

The effects of mobile emissions inventories on regional ozone, fine particulate matter, nitrate, and secondary organic aerosol are investigated using the Community Multiscale Air Quality Model (CMAQ) and a bottom-up regional inventory. This inventory, developed for an EPA STAR-funded study, Projecting the Impact of Land Use and Transportation on Future Air Quality in the Upper Midwestern United States (PLUTO), use the Nationwide Personal Transportation Survey transferability framework's demographic and vehicle activity modeling to estimate vehicle trips and miles of travel (VMT) at the census tract level in response to four census variables: income, vehicle ownership, employment rate, and density. Once grouped into demographically homogenous clusters, average daily household vehicle travel rates are derived from the national travel survey respondents captured in each cluster and used to estimate tract level vehicle travel activity. Regional VMT and emissions estimates are compared with the US EPA's 2002 National Emissions Inventory onroad mobile inventory, developed with the National Mobile Inventory Model, which clusters by county. CMAQ is run in a 2002 annual simulation at 36 km x 36 km resolution over Illinois, Indiana, Michigan, Minnesota, Ohio, and Wisconsin. Impacts of mobile emissions inventories on air quality model performance are established through comparison with surface observations from AQS and STN networks. In evaluating mobile emissions inventories, this study provides insight into the sensitivity of simulated air quality to a range of mobile emissions estimates, and allows for an attribution of CMAQ error to uncertainty in mobile emissions.

A23C-1480 

Evaluation of the GEM-AQ air quality model on a global scale; extensive and intensive parameter comparisons with AERONET and MODIS

* O'Neill, N T (norm.oneill@USherbrooke.ca), Universite de Sherbrooke CARTEL, 2500 Boul. de l'Universite, Sherbrooke, PQ J1K2R1, Canada Lupu, A (alex.lupu@maqnet.ca), York University Dept of Earth & Space Science & Engineering, Faculty of Science & Eng, Lumbers Building, 325 115 Ottawa Road, Downsview, ON M3J1P3, Canada Neary, L (lori@nimbus.yorku.ca), York University Dept of Earth & Space Science & Engineering, Faculty of Science & Eng, Lumbers Building, 325 115 Ottawa Road, Downsview, ON M3J1P3, Canada Thulasiraman, S (Thulasi.Raman.Srinivasan@USherbrooke.ca), Universite de Sherbrooke CARTEL, 2500 Boul. de l'Universite, Sherbrooke, PQ J1K2R1, Canada McConnnell, J C (jcmcc@yorku.ca), York University Dept of Earth & Space Science & Engineering, Faculty of Science & Eng, Lumbers Building, 325 115 Ottawa Road, Downsview, ON M3J1P3, Canada Kaminski, J ( jacek@nimbus.yorku.ca), York University Dept of Earth & Space Science & Engineering, Faculty of Science & Eng, Lumbers Building, 325 115 Ottawa Road, Downsview, ON M3J1P3, Canada

The Canadian air quality model (GEM-AQ) includes an aerosol physics module which incorporates five size- resolved aerosol components and dynamic emission inventories for smoke and dust. A recent 5-year global run permitted a comparison of total optical depths, fine mode fraction (FMF) and SWIR (short wave infrared) Angstrom exponents with AERONET and MODIS retrievals over the Northern hemisphere. This communication will focus (i) on the similarities and differences obtained between measurements and model for both extensive (optical depth) and intensive (FMF and SWIR Angstrom exponent) parameters and (ii) how these comparisons can yield insight into source emission characteristics.

A23C-1481 

Diagnosing MM5-CMAQ Performance for the Summer 2000 Central California Ozone Study

* Brown, N J (njbrown@lbl.gov), Atmospheric Science Department, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, United States Jin, L), Atmospheric Science Department, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, United States Tonse, S), Atmospheric Science Department, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, United States Harley, R A), Department of Civil and Environmental Engineering, Unversity of California at Berkeley, Berkeley, CA 94720, United States Bao, J), Regional Weather and Climate Applications Division, NOAA/Environmental Technology Laboratory 325 Broadway, Mail Stop: ET7, Boulder, CO 80305, United States Michelson, S A), Regional Weather and Climate Applications Division, NOAA/Environmental Technology Laboratory 325 Broadway, Mail Stop: ET7, Boulder, CO 80305, United States Wilczak, J), Regional Weather and Climate Applications Division, NOAA/Environmental Technology Laboratory 325 Broadway, Mail Stop: ET7, Boulder, CO 80305, United States

Past evaluations of the Community Multiscale Air Quality (CMAQ) modeling system have focused on the eastern United States and applications of it are usually conducted for high ozone episodes that last for a few days. In our research, we seek more comprehensive model evaluation by applying MM5-CMAQ to simulating ozone formation for an entire summer season in central California, where ozone air pollution problems are severe and air districts are out of compliance with the 8-hour ozone standard. In this paper, we have simulated ozone formation in the central California region with CMAQv4.6 for a 15-day period, which includes a five-day high ozone episode. Simulated ozone concentrations adequately match the observed patterns, except in the Bay area during the last 5-day period. Model performance does not degrade over time, but exhibits spatial trends in biases. CMAQ tends to over-predict ozone at coastal areas, and slightly under- predict it in the central valley. Wind field nudging greatly improves the chemical transport processes. When transport errors are minimized, we see similar ozone sensitivities when comparing observed and modeled ozone production efficiencies. Sensitivity analysis is performed and the most influential factors studied here are listed for different geographical regions. The Bay area is sensitive to uncertainties in all the input parameters considered here, which suggests greater challenges on correct simulating ozone concentrations in this area.

A23C-1482 

Column versus Profile Correlations Between Ozone and PV

* Hornstein, J S (john.hornstein@nrl.navy.mil), Naval Research Laboratory, 4555 Overlook Avenue, S.W. Bldg 2, Room 260, Washington, DC 20375, United States

Previous case studies have shown that tropospheric weather forecasts can be improved by exploiting space- based measurements of the ozone total column. Those studies obtained improved estimates of the PV field by exploiting the space-time dependent correlation between the ozone total column and the partial vertical average of the potential vorticity (PV): the global coverage of the space-based ozone measurements helped to compensate for the gaps in coverage in the ground based and radiosonde networks of meteorological sensors. The improved PV maps were then inverted to derive improved estimates of the wind field. The present work investigates the utility of using ozone profile data to supplement or replace the ozone total column data in such applications, by comparing the tightness of the profile correlation to that of the column correlation.

A23C-1483 

Adjoint Inversion of Global NOx Emissions with SCIAMACHY NO2

* Shim, C (cshim@jpl.nasa.gov), Jet propulsion laboratory, 4800 Oak grove dr., Pasadena, CA 91109, United States Li, Q (qli@jpl.nasa.gov), Jet propulsion laboratory, 4800 Oak grove dr., Pasadena, CA 91109, United States Henze, D (daven@caltech.edu), California Institute of Technology, 1220 E California Blvd, Pasadena, CA 91125, United States Martin, R (randall.martin@dal.ca), Dallhousie University, 6385 South Street, Halifax, NS B3H 1Z9, Canada Donkelaar, A V (aaron.van.donkelaar@dal.ca), Dallhousie University, 6385 South Street, Halifax, NS B3H 1Z9, Canada Kopacz, M (kopacz@fas.harvard.edu), Havard University, Pierce Hall, 29 Oxford St., Cambridge, MA 02138, United States Bowman, K W (kevin.w.bowman@jpl.nasa.gov), Jet propulsion laboratory, 4800 Oak grove dr., Pasadena, CA 91109, United States Eldering, A (annmarie.eldering@jpl.nasa.gov), Jet propulsion laboratory, 4800 Oak grove dr., Pasadena, CA 91109, United States

An adjoint inversion of NOx emissions is conducted with tropospheric NO2 column measurements from SCIAMACHY to constrain NOx emissions for November 2005. The adjoint of the GEOS-Chem global 3-D model of tropospheric chemistry and transport is applied for the inversion. Vertical NO2 columns are obtained by computing AMF calculation with GEOS-Chem NO2 profiles. The November time period is chosen so that a comparison between the adjoint inversion and the mass-balance method [e.g., Martin et al., 2003] would shed light into the smearing effect due to transport associated with the later approach. Simulations were conducted at 2x2.5 horizontal resolution. NOx emissions from urban/industry, biomass burning, lightning, biofuel, soil, and NH3 oxidation are chosen as state variables. GEOS-Chem underestimates SCHIAMACHY NO2 tropospheric columns by 20-30%. A posteriori of urban/industry, biomass burning, lightning and soil NOx emissions are generally higher than the a priori values with regional variations. On the other hand, a posteriori of NH3 oxidation are generally lower than the a priori values.

A23C-1484 

Quantifying the impact of aggregation errors and model transport biases on top-down estimates of carbon monoxide emissions using satellites observations

* Jiang, Z (zjiang@atmosp.physics.utoronto.ca), Department of Physics University of Toronto, 60 St. George Street, Toronto, ON M5S 1A7, Canada Jones, D B (dbj@atmosp.physics.utoronto.ca), Department of Physics University of Toronto, 60 St. George Street, Toronto, ON M5S 1A7, Canada Kopacz, M (kopacz@fas.harvard.edu), Division of Engineering and Applied Science Harvard University, 110J Pierce Hall, 29 Oxford Street, Cambridge, MA 02138, United States Liu, J (jliu@atmosp.physics.utoronto.ca), Department of Physics University of Toronto, 60 St. George Street, Toronto, ON M5S 1A7, Canada Henze, D K (daven@its.caltech.edu), Department of Chemical Engineering California Institute of Technology, 1200 E.California Blvd, Pasadena, CA 21041, United States

Inverse modeling has become a widely used method for obtaining top-down estimates of surface emissions of atmospheric CO. These top-down estimates, however, are adversely influenced by systematic errors in the inverse model, such as biases in the transport fields and aggregation errors associated with choice of regional scales on which the emissions are aggregated for optimization (discretization of the state vector). We have conducted an inverse analysis of atmospheric CO, using the GEOS-Chem model and observations from the MOPITT satellite instrument, to quantify the potential contribution of model transport error and aggregation errors on top-down source estimates. We focus on quantifying CO emissions for September and October 2000, during the biomass burning season in the southern hemisphere. We employ a sub-optimal Kalman filter to assimilate MOPITT data to adjust the initial distribution of CO at the beginning of the inversion period, and then apply a 4- dimensional variational data assimilation scheme to optimize the CO emissions on the 2x2.5 grid of the model. The high-resolution, a posteriori source estimates are compared with estimates obtained from a coarse resolution, analytical Bayesian inversion to quantify the impact of aggregation errors in the coarse resolution inversion on the source estimates. We also carry out the coarse resolution analytical inversion using two different versions of the GEOS-Chem model, driven with different transport fields, to isolate the impact on the source estimates of systematic differences in transport (associated mainly with the different convection schemes) in the models.

A23C-1485 

Estimation of Flux Biases by Coupled MLEF-PCTM Model Using CO2 Observations

* Lokupitiya, R (ravi@atmos.colostate.edu), Department of Atmospheric Science, Colorado State University, Fort Collins, CO 80523, United States Zupanski, D (zupanski@cira.colostate.edu), Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, CO 80523, United States Denning, S (denning@atmos.colostate.edu), Department of Atmospheric Science, Colorado State University, Fort Collins, CO 80523, United States Parazoo, N (nparazoo@atmos.colostate.edu), Department of Atmospheric Science, Colorado State University, Fort Collins, CO 80523, United States Kawa, R (kawa@maia.gsfc.nasa.gov), NASA Goddard Space Flight Center, 8800 Greenbelt Road, Baltimore, MD 20771, United States Hanan, N (niall@nrel.colostate.edu), Natural Resource Ecology Laboratory, Colorado State University, Fort Collins, CO 80523, United States Zupanski, M (zupanskim@cira.colostate.edu), Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, CO 80523, United States

We used an ensemble based data assimilation system, Maximum Likelihood Ensemble Filter (MLEF), which has been coupled with Parameterized Chemistry Transport Model (PCTM), to assimilate CO2 observations. A pseudo data experiment showed that the coupled system is capable of recovering fluxes adequately in well- observed northern hemispheric regions. We assimilated 2 years of CO2 observations from 49 flask sites and 15 continuous sites to estimate separate multiplicative biases in photosynthesis, respiration, and air-sea gas exchange. Spatial covariance in the biases was updated in the assimilation process. Flux bias estimates will be presented along with their uncertainties. It is assumed that the biases have 8-week time span and they are constant throughout that time period. Results show good constraint on model biases over North America and Europe. Some other regions (e.g. the South Atlantic, tropical contents) are unconstrained.

A23C-1486 

Inverse Modeling of Accidental Releases of Atmospheric Pollutants: New Developments.

* Bocquet, M (bocquet@cerea.enpc.fr), CEREA Paris-Est University / ParisTech, Ecole Nationale des Ponts et Chaussées 6-8 avenue Blaise Pascal Champs sur Marne, Marne la Vallée, 77455, France

An account is given on new data assimilation techniques that have recently been used to identify the source of an accidental release of pollutant into the atmosphere, and forecast (possibly in real time) the subsequent dispersion plume. It could be a chemical cloud from an industrial site or a release of radionuclides from a nuclear power plant (from minor accident to core meltdown). These methods are not necessarily based on Gaussian hypotheses, for instance the source may be given as positive or bounded. In particular, the usual least squares cost function (4D-Var) is replaced with purposely devised functionals that are not necessarily quadratic. These methods have been applied successfully to the reconstruction of the Chernobyl accident, the Algeciras incident or the ETEX experiment, and outperform previous approaches. As far as state assimilation is concerned, the techniques have been applied a posteriori to the reconstruction of the ETEX plume, after all observations are acquired. The method has also been applied to the reconstruction of the dispersion plume, in the context of an emergency situation: the data have been assimilated sequentially as they arrived and a forecast is performed after each analysis. This provides with a picture of what could be achieved (forecast, risk assessment) in case of a real emergency with a Chemistry Transport Model and advanced data assimilation techniques. A second-order sensitivity study that applies to the possibly non- quadratic cost functions has also been carried out in the context of these reconstructions.

A23C-1487 

Assessing Model Errors Through Chemical Data Assimilation

* Tangborn, A (Andrew.V.Tangborn@nasa.gov), Global Modeling and Assimilation Office, Code 610.1, Goddard Space Flight Center, Greenbelt, MD 20771, United States Stajner, I (Ivanka.Stajner@nasa.gov), Global Modeling and Assimilation Office, Code 610.1, Goddard Space Flight Center, Greenbelt, MD 20771, United States Pawson, S (Steven.Pawson@nasa.gov), Global Modeling and Assimilation Office, Code 610.1, Goddard Space Flight Center, Greenbelt, MD 20771, United States Buchwitz, M (Michael.Buchwitz@iup.physik.uni-bremen.de), Institute of Environmental Physics (IUP), University of Bremen, FB1 Otto-Hahn-Allee 1 PO Box 33 04 40, Bremen, D-28334, Germany Khlystova, I (Iryna.Khlystova@iup.physik.uni-bremen.de), Institute of Environmental Physics (IUP), University of Bremen, FB1 Otto-Hahn-Allee 1 PO Box 33 04 40, Bremen, D-28334, Germany Burrows, J (burrows@iup.physik.uni-bremen.de), Institute of Environmental Physics (IUP), University of Bremen, FB1 Otto-Hahn-Allee 1 PO Box 33 04 40, Bremen, D-28334, Germany Hudman, R (hudman@fas.harvard.edu), Harvard University Division of Engineering and Applied Science, 29 Oxford St., Cambridge, MA 02138, United States

Assimilation of satellite observations of chemical constituents results in corrections to forecasts of trace gas fields from a chemical transport model. When these corrections produce significant systematic changes to the field, it is important to determine whether this is the result of bias in either the model or the satellite retrievals. Independent data sets, particularly in situ observations, can often help to point out the source of the bias. We report here on the assimilation of carbon monoxide observations from SCIAMACHY and ozone from OMI and MLS using the the GMAO constituent assimilation system. The model uses analyzed winds from the GEOS-4 meteorological assimilation system and production/loss rates from GEOS-Chem. We focus on analyzed CO and tropospheric O3 fields over the Arabian peninsula during the fall of 2004, when the analysis increments in both fields are consistently positive. Comparisons with MOZAIC in situ data are made in order to determine the source of the systematic difference between the model and observations.

A23C-1488 

Interannual Variability in Tropospheric CO: Global-Scale Analysis using GEOS-CHEM model and MOPITT Measurements

* Li, Q (ql10@duke.edu), Duke University, Nicholas School of the Environment, Durham, NC 27705, United States Kasibhatla, P (psk9@dukee.edu), Duke University, Nicholas School of the Environment, Durham, NC 27705, United States Randerson, J (jranders@uci.edu), University of California Irvine, Department of Earth System Sciences, Irvine, CA 92697, United States var der Werf, G (guido.van.der.werf at falw.vu.nl), Vrije University, Department of Hydrology and Geo-Environmental Sciences, Amsterdam, 1081 HV, Netherlands Collatz, J (Jim.Collatz@nasa.gov), NASA Goddard Space Flight Center, Goddard Space Flight Center, Greenbelt, MD 20771, United States Giglio, L (giglio@hades.gsfc.nasa.gov), NASA Goddard Space Flight Center, Goddard Space Flight Center, Greenbelt, MD 20771, United States

Biomass burning is a significant global source of a variety of chemically and radiatively important trace gases. In this study, three-dimensional atmospheric chemical transport model (CTM) are used to simulate the distribution of CO from biomass burning emissions using GFED2 biomass burning emission inventory for the 2002-2006 period. Comparison with the MOPITT (Measurements of Pollution in the Troposphere) satellite measurements shows that the model significantly underestimated the seasonal cycle, but relatively well captured the interannual variability of the troposphere CO column. An inverse analysis is then used to estimate the biomass burning CO emission anomalies in various geographical regions based on assumption that short-term interannual variations in atmospheric column CO primarily caused by the interannual variations in biomass burning CO emissions. Such a inverse model is found useful to constrain those biomass burning emissions with large anomalies such as Equatorial Asia and Siberia. The inversion indicate over 30% increase in the emission anomalies from Equatorial Asia and 25% decrease in the fire emission anomalies from southern South America. The posterior modeled CO anomalies performed reasonably well comparing to both MOPITT column and NOAA GMD (National Oceanic and Atmospheric Administration Global Monitoring Division) surface concentration anomalies.

A23C-1489 

Aerosol Simulation in the Mexico City Metropolitan Area during MCMA2003 using CMAQ/Models3

* Bei, N (bnf@mce2.org), Department of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, USA, Department of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, * Bei, N (bnf@mce2.org), Molina Center for Energy and the Environment, CA, USA, 3262 Holiday Court, La Jolla, CA 92037, Zavala, M (miguelz@mit.edu), Department of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, USA, Department of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, Zavala, M (miguelz@mit.edu), Molina Center for Energy and the Environment, CA, USA, 3262 Holiday Court, La Jolla, CA 92037, Lei, W (wflei@mit.edu), Department of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, USA, Department of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, Lei, W (wflei@mit.edu), Molina Center for Energy and the Environment, CA, USA, 3262 Holiday Court, La Jolla, CA 92037, de Foy, B (foy@eas.slu.edu), Molina Center for Energy and the Environment, CA, USA, 3262 Holiday Court, La Jolla, CA 92037, de Foy, B (foy@eas.slu.edu), Saint Louis University, Saint Louis, Missouri, USA, Saint Louis University, Saint Louis, MO 63108, Molina, L (ltmolina@mit.edu), Department of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, USA, Department of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, Molina, L (ltmolina@mit.edu), Molina Center for Energy and the Environment, CA, USA, 3262 Holiday Court, La Jolla, CA 92037,

CMAQ/Models3 has been employed to simulate the aerosol distribution and variation during the period from 13 to 16 April 2003 over the Mexico City Metropolitan Area as part of MCMA-2003 campaign. The meteorological fields are simulated using MM5, with three one-way nested grids with horizontal resolutions of 36, 12 and 3 km and 23 sigma levels in the vertical. MM5 3DVAR system has also been incorporated into the meteorological simulations. Chemical initial and boundary conditions are interpolated from the MOZART output. The SAPRC emission inventory is developed based on the official emission inventory for MCMA in 2004. The simulated mass concentrations of different aerosol compositions, such as elemental carbon (EC), primary organic aerosol (POA), secondary organic aerosol (SOA), nitrate, ammonium, and sulfate have been compared to the measurements taken at the National Center for Environmental Research and Training (Centro Nacional de Investigacion y Capacitacion Ambiental, CENICA) super-site. Hydrocarbon-like organic aerosol (HOA) and oxygenated organic aerosol (OOA) are used as observations of POA and SOA, respectively in this study. The preliminary model results show that the temporal evolutions of EC and POA are reasonable compared with measurements. The peak time of EC and POA are basically reproduced, thus validating the emission inventory and its processing through CMAQ/Models3. But the magnitude of EC and POA are underestimated over the entire episode. The modeled nitrate and ammonium concentrations are overestimated on most of the days. There is 1-2 hour difference between the simulated peak time of nitrate and ammonium aerosols compared to observations at CENICA. The simulated mass concentrations of SOA and sulfate are significantly underestimated. The reasons of the discrepancy between simulations and measurements are due to the uncertainties existing in the emission inventory, meteorological fields, and as well as aerosol formation mechanism in the case of SOA. The improvement in the emission invenory and aerosol formation mechanism are currently underway and will be presented.