Atmospheric Sciences [A]

A14D  MW:3014   Monday
Evaluation of Air Quality Models and Assessment of Emissions Inventories Using Bottom- Up and Top-Down Approaches III: Source and State Data Assimilation of Satellite and in Situ Measurements in Atmospheric Chemistry
Presiding: K W Bowman, Jet Propulsion Laboratory; J A de Gouw, NOAA Earth System Research Laboratory

A14D-01 INVITED 

Emission Rate and Chemical State Assessments by Nested 4D-Variational Chemistry Data Assimilation

* Elbern, H (he@eurad.uni-koeln.de), Rhenish Institute for Environmental Research at the University of Cologne, Aachener Strasse 209, Cologne, NRW D-50935, Germany Strunk, A (as@eurad.uni-koeln.de), Rhenish Institute for Environmental Research at the University of Cologne, Aachener Strasse 209, Cologne, NRW D-50935, Germany

The presentation demonstrates the potential and limits of an advanced inversion method to estimate pollutant precursor sources from observations, both in situ and satellite tropospheric columns. Ozone, sulphur dioxide, and partly nitrogen oxides observations are taken to infer source strength estimates. As methodology, the four--dimensional variational data assimilation technique has been generalised and employed to include emission rate optimisation, in addition to chemical state estimates as usual objective of data assimilation. To this end, the optimisation space of the variational assimilation system has been complemented by emission rate correction factors of 19 emitted species at each emitting grid point, involving the University of Cologne mesoscale EURAD model. For validation, predictive skills were assessed for several ozone episodes, comparing forecast performances of pure initial value optimisation, pure emission rate optimisation, and joint emission rate/initial value optimisation. Validation procedures rest on both measurements withheld from data assimilation and prediction skill evaluation of forecasts after the inversion procedures. Results show that excellent improvements can be claimed for sulphur dioxide forecasts, after emission rate optimisation. Significant improvements can be claimed for ozone forecasts after initial value and joint emission rate/initial value optimisation of precursor constituents. The additional benefits applying joint emission rate/initial value optimisation are moderate, and very useful in typical cases, where upwind emission rate optimisation is essential. The poor representativity of NOx observations enforced augmentation of the 4D-var system by multi level nesting techniques. The improvements of the analysis result with increasing horizontal resolution, starting from a 54 km mother grid down to 6 km finest grid. http://www.atmos-chem-phys.net/7/3749/2007/acp-7-3749-2007.html

A14D-02 INVITED 

Multi-year emission inversion for reactive gases using the adjoint model method

* Muller, J (jfm@aeronomie.be), Belgian Institute for Space Aeronomy, Ave. Circulaire 3, Brussels, 1180, Belgium Stavrakou, T (jenny@aeronomie.be), Belgian Institute for Space Aeronomy, Ave. Circulaire 3, Brussels, 1180, Belgium

Although computationally expensive and difficult to program, the adjoint model technique is very appealing for addressing the problem of source inversion of reactive gases (like CO, NOx and the non-methane volatile organic compounds, NMVOCs) using atmospheric models. In particular, it allows accounting for the non-linear relationship existing between the emissions of such compounds and the concentrations of species observed from space (like CO, NO2 and HCHO), which involves complex transport and chemical processes. Moreover, the method has no limitation regarding the number of control parameters to be optimized using atmospheric observations. We present the development of an inverse modeling framework based on the IMAGES 3d global CTM and its adjoint. Applications included the joint optimization of CO and NOx sources using NO2 and CO observations; the comparison of the synthetic "big region" scheme with the more general, grid-based inversion scheme making use of spatial and temporal correlations between errors on the emission parameters; the use of one decade of satellite measurements of NO2 and HCHO for the inversion of NOx emissions from 4 categories and of short- lived NMVOC emissions from biogenic and pyrogenic sources. Future perspectives will be also discussed.

A14D-03 

Chemical Data Assimilation of MOPITT CO and MODIS AOD Retrievals in the Community Atmosphere Model

* Arellano, A F (arellano@ucar.edu), Atmospheric Chemistry Division, National Center for Atmospheric Research (ACD/NCAR), PO Box 3000, Boulder, CO 80307-3000, United States Hess, P G (hess@ucar.edu), Atmospheric Chemistry Division, National Center for Atmospheric Research (ACD/NCAR), PO Box 3000, Boulder, CO 80307-3000, United States Edwards, D P (edwards@ucar.edu), Atmospheric Chemistry Division, National Center for Atmospheric Research (ACD/NCAR), PO Box 3000, Boulder, CO 80307-3000, United States Anderson, J L (jla@ucar.edu), Institute for Mathematics Applied to Geosciences, PO Box 3000, Boulder, CO 80307-3000, United States Raeder, K (raeder@cgd.ucar.edu), Institute for Mathematics Applied to Geosciences, PO Box 3000, Boulder, CO 80307-3000, United States Emmons, L K (emmons@ucar.edu), Atmospheric Chemistry Division, National Center for Atmospheric Research (ACD/NCAR), PO Box 3000, Boulder, CO 80307-3000, United States Pfister, G G (pfister@ucar.edu), Atmospheric Chemistry Division, National Center for Atmospheric Research (ACD/NCAR), PO Box 3000, Boulder, CO 80307-3000, United States Campos, T (campos@ucar.edu), Atmospheric Chemistry Division, National Center for Atmospheric Research (ACD/NCAR), PO Box 3000, Boulder, CO 80307-3000, United States Diskin, G (g.s.diskin@larc.nasa.gov), Chemistry and Dynamics Branch, NASA Langley Research Center, NASA Langley Research Center, Hampton, VA 23681-2199, United States

We explore the potential of an ensemble-based data assimilation system for multi-species chemical data assimilation. The system consists of an online global chemical transport model, the Community Atmosphere Model (CAMv3.4) with chemistry from the Model of OZone And Related chemical Tracers (MOZARTv4), and a community ensemble Kalman filter (EnKF) assimilation package, the Data Assimilation Research Testbed (DART) being developed at the National Center for Atmospheric Research (NCAR). Our initial application focuses on jointly assimilating meteorological observations from the existing global meteorological network and satellite retrievals of CO from the Measurement of Pollution in the Troposphere (MOPITT) instrument and aerosol optical depth (AOD) from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument. We begin by first assimilating meteorological observations and MOPITT retrievals and explore the impact of the assimilation on better representing aerosol transport and combustion-related aerosol sources in CAM. We then investigate the additional impact of assimilating MODIS AOD retrievals on the modeled concentrations of sulfate, organic carbon, black carbon, dust, sea-salt aerosols and CO. Unlike previous analyses, the EnKF scheme is potentially capable of statistically updating the individual states of each aerosol types from the ensemble estimate of AOD and CO sensitivities. We present results of our analysis, both from observing system simulation experiments (OSSEs) and an assimilation of real observations focusing on April 2006 test period. This coincides with the Inter- continental Chemical Transport Experiment (INTEX-B) conducted over Hawaii and the northeastern Pacific. We verify the modeled aerosol and CO distributions using observations of CO and aerosol species from this campaign in conjunction with observations of AOD from the Aerosol Robotic Network (AERONET).

A14D-04 

RAQMS chemical data assimilation studies of trans-pacific pollution transport during the 2006 INTEX-B field mission

* Pierce, R (brad.pierce@noaa.gov), Advanced Satellite Products Branch, NOAA/NESDIS, CIMSS 1225 West Dayton St, Madison, WI 53706, United States Al-Saadi, J A (j.a.al-saadi@nasa.gov), Chemistry and Dynamics Branch, Science Directorate, NASA Langley Research Center, Hampton, VA 23681, United States Schaack, T (todd.schaack@ssec.wisc.edu), Space Science and Engineering Center, University of Wisconsin-Madison 1225 West Dayton St., Madison, WI 53706, United States Bowman, K (kevin.bowman@jpl.nasa.gov), Jet Propulsion Laboratory, NASA, 4800 Oak Grove Drive, Pasadena, CA 91109, United States Avery, M (m.a.avery@larc.nasa.gov), Chemistry and Dynamics Branch, Science Directorate, NASA Langley Research Center, Hampton, VA 23681, United States Sachse, G (glen.w.sachse@nasa.gov), Chemistry and Dynamics Branch, Science Directorate, NASA Langley Research Center, Hampton, VA 23681, United States Thompson, A (anne@met.psu.edu), Department of Meteorology, Penn State University 510 Walker Building, University Park, PA 16802, United States Jaffe, D (djaffe@u.washington.edu), University of Washington-Botell, 18115 Campus Way NE, Bothell, WA 98011, United States Bhartia, P (pawan.k.bhartia@nasa.gov), Atmospheric Dynamics and Chemistry Branch, Laboratory for Atmospheres, NASA Goddard Space Flight Center, Greenbelt, MD 20771, United States Boone, C (cboone@uwaterloo.ca), Department of Chemistry, University of Waterloo Chemistry 2 Building, Waterloo, ON N2L 3G1, Canada Rinsland, C (curtis.p.rinsland@nasa.gov), Chemistry and Dynamics Branch, Science Directorate, NASA Langley Research Center, Hampton, VA 23681, United States Campos, T (campos@ucar.edu), Atmospheric Chemistry Division, National Center for Atmospheric Research 1850 Table Mesa Dr., Boulder, CO 80305, United States Weinheimer, A (wein@ucar.edu), Atmospheric Chemistry Division, National Center for Atmospheric Research 1850 Table Mesa Dr., Boulder, CO 80305, United States Emmons, L (emmons@ucar.edu), Atmospheric Chemistry Division, National Center for Atmospheric Research 1850 Table Mesa Dr., Boulder, CO 80305, United States

This talk presents a summary of chemical data assimilation studies utilizing the Real-time Air Quality Modeling System (RAQMS) to characterize trans-pacific pollution transport, photochemistry and continental US air quality during the 2006 NASA INTEX-B field mission. The RAQMS chemical analysis includes assimilation of cloud cleared OMI total column ozone measurements and ozone and carbon monoxide profiles from TES nadir global survey measurements. The chemical analyses are used in conjunction with airborne, surface and satellite measurements to show evidence of upper tropospheric pollution fluxes and efficient mixing of polluted and stratospheric air masses over the central Pacific, and enhanced pollution along the west coast of the US.

A14D-05 

Determination of Biogenic Emissions from Aircraft Measurements During TEXAQS2006 and ICARTT2004 Campaigns and Comparison with Biogenic Emission Inventories

* Warneke, C (carsten.warneke@noaa.gov), NOAA ESRL Chemical Sciences Division, 325 Broadway, Boulder, CO 80305, United States * Warneke, C (carsten.warneke@noaa.gov), CIRES University of Colorado, 216 UCB, Boulder, CO 80305, United States McKeen, S (Stuart.A.McKeen@noaa.gov), NOAA ESRL Chemical Sciences Division, 325 Broadway, Boulder, CO 80305, United States McKeen, S (Stuart.A.McKeen@noaa.gov), CIRES University of Colorado, 216 UCB, Boulder, CO 80305, United States de Gouw, J A (Joost.deGouw@noaa.gov), NOAA ESRL Chemical Sciences Division, 325 Broadway, Boulder, CO 80305, United States de Gouw, J A (Joost.deGouw@noaa.gov), CIRES University of Colorado, 216 UCB, Boulder, CO 80305, United States Del Negro, L (delnegro@lakeforest.edu), Lake Forest College, 555 N. Sheridan Rd., Lake Forest, Il 60045, United States Brioude, J (Jerome.Brioude@noaa.gov), NOAA ESRL Chemical Sciences Division, 325 Broadway, Boulder, CO 80305, United States Brioude, J (Jerome.Brioude@noaa.gov), CIRES University of Colorado, 216 UCB, Boulder, CO 80305, United States Stark, H (Harald.Stark@noaa.gov), NOAA ESRL Chemical Sciences Division, 325 Broadway, Boulder, CO 80305, United States Stark, H (Harald.Stark@noaa.gov), CIRES University of Colorado, 216 UCB, Boulder, CO 80305, United States Trainer, M K (Michael.K.Trainer@noaa.gov), NOAA ESRL Chemical Sciences Division, 325 Broadway, Boulder, CO 80305, United States Fehsenfeld, F C (Fred.C.Fehsenfeld@noaa.gov), NOAA ESRL Chemical Sciences Division, 325 Broadway, Boulder, CO 80305, United States Fehsenfeld, F C (Fred.C.Fehsenfeld@noaa.gov), CIRES University of Colorado, 216 UCB, Boulder, CO 80305, United States Wiedinmyer, C (christin@ucar.edu), NCAR ACD, 1850 Table Mesa DR, Boulder, CO 80307, United States Vanchindorj, U (vulziisa@ucar.edu), NCAR ACD, 1850 Table Mesa DR, Boulder, CO 80307, United States Guenther, A B (guenther@ucar.edu), NCAR ACD, 1850 Table Mesa DR, Boulder, CO 80307, United States

Isoprene and monoterpenes were measured with a PTR-MS instrument onboard the NOAA WP-3 aircraft during the TEXAQS2006 and ICARTT2004 campaigns. Isoprene emission fluxes are estimated using a mixed boundary layer approach, which takes the isoprene lifetime into account. The results are directly compared to the EPA BEIS- 3 inventory (EPA Biogenic Emissions Inventory System). In addition, the EPA BEIS-3 data were incorporated in a Lagrangian particle dispersion model (FLEXPART) and the mixing ratios calculated from the model are compared to the measurements. This model calculation takes transport, but not chemistry into account and can also be used to determine the transport of isoprene and its oxidation products over several hours. Both methods indicate that EPA BEIS-3 overestimates the emission fluxes estimated from the aircraft measurements. The difference is dependent on the day and the location but for all flights an agreement to better than a factor of two was found. Clear discrepancies were observed for specific locations, such as some forested areas north-west of Houston, Texas, or at the border between Canada and the US in the New England area. Other isoprene emission inventories were also compared to the emission fluxes estimated from the aircraft measurements. An inventory compiled by Wiedinmyer et al. for the Texas area using different land cover data clearly improved the comparison. The emission fluxes estimated from the measurements are also compared to the Model of Emissions of Gases and Aerosols from Nature (MEGAN).

A14D-06 

Airborne High Spectral Resolution Lidar Aerosol Measurements and Comparisons with Transport Models

* Ferrare, R (richard.a.ferrare@nasa.gov), NASA Langley Research Center, NASA/LaRC, Hampton, VA 23681, United States Hostetler, C (chris.a.hostetler@nasa.gov), NASA Langley Research Center, NASA/LaRC, Hampton, VA 23681, United States Hair, J (Johnathan.W.Hair@nasa.gov), NASA Langley Research Center, NASA/LaRC, Hampton, VA 23681, United States Cook, A (Anthony.L.Cook@nasa.gov), NASA Langley Research Center, NASA/LaRC, Hampton, VA 23681, United States Harper, D (David.B.Harper@nasa.gov), NASA Langley Research Center, NASA/LaRC, Hampton, VA 23681, United States Burton, S (s.p.burton@larc.nasa.gov), SSAI/NASA/LaRC, One Enterprise Pkwy., Hampton, VA 23669, United States Obland, M (m.d.obland@larc.nasa.gov), NASA Langley Research Center, NASA/LaRC, Hampton, VA 23681, United States Rogers, R (r.r.rogers@larc.nasa.gov), SSAI/NASA/LaRC, One Enterprise Pkwy., Hampton, VA 23669, United States Kleinman, L (kleinman@bnl.gov), Brookhaven National Laboratory, Atmospheric Sciences Division, Upton, NY 11973, United States Clarke, A (tclarke@soest.hawaii.edu), University of Hawaii, Dept. of Oceanography, Hawaii, HI 96822, United States Fast, J (Jerome.Fast@pnl.gov), Pacific Northwest National Lab, PO Box 999, Richland, WA 99352, United States Chin, M (mian.chin@nasa.gov), NASA Goddard Space Flight Center, Code 613.3, Greenbelt, MD 20771, United States Carmichael, G (gcarmich@engineering.uiowa.edu), University of Iowa, CGRER, Iowa City, IA 52442, United States Tang, Y (ytang@cgrer.uiowa.edu), University of Iowa, CGRER, Iowa City, IA 52442, United States Emmons, L (emmons@ucar.edu]), National Center for Atmospheric Research, Atmospheric Chemistry Division, Boulder, CO 80307, United States Pierce, B (Brad.Pierce@noaa.gov), NOAA/NESDIS, 1225 W. Dayton St., Madison, WI 53707, United States Kittaka, C (chieko.kittaka-1@nasa.gov), SSAI/NASA/LaRC, One Enterprise Pkwy., Hampton, VA 23669, United States

The NASA Langley Research Center (LaRC) airborne High Spectral Resolution Lidar (HSRL) measured aerosol distributions and optical properties during several field experiments in 2006 and 2007. These experiments include: 1) the joint Megacity Initiative: Local and Global Research Observations (MILAGRO) /Megacity Aerosol Experiment in Mexico City (MAX-MEX)/Intercontinental Chemical Transport Experiment-B (INTEX B) experiment, 2) the Texas Air Quality Study (TEXAQS)/Gulf of Mexico Atmospheric Composition and Climate Study (GoMACCS), 3) the San Joaquin Valley experiment, 4) the Cumulus Humilis Aerosol Processing Study (CHAPS), and 5) the Cloud Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) and Twilight Zone (CATZ) experiment. The LaRC airborne HSRL uses the spectral distribution of the lidar return signal to measure aerosol extinction and backscatter profiles independently at 532 nm and uses standard backscatter lidar techniques to derive aerosol backscatter and extinction profiles at 1064 nm. Aerosol depolarization profiles are measured at both wavelengths. The HSRL collected over 350 hours of aerosol measurements during these experiments. Airborne HSRL data acquired during these missions were used to infer aerosol types, characterize the spatial and vertical distributions of these aerosol types, and to apportion aerosol extinction and optical thickness (AOT) among the various aerosol types. Initial results show that a mixture of nonspherical (i.e. dust) and urban aerosols accounted for over half of the AOT measured by the HSRL during the MILAGRO flights over Mexico; in contrast, during the GoMACCS and CALIPSO validation flights over Houston and the eastern U.S., respectively, urban/biomass aerosols accounted for 80-90% of the AOT. Preliminary investigations using airborne in situ measurements of aerosol microphysical properties generally support the variability of aerosol types inferred from the HSRL data. The distributions of aerosol extinction, optical thickness, and aerosol types in relation to the Planetary Boundary Layer (PBL) and free troposphere will also be discussed. The HSRL measurements were also used to help evaluate the ability of transport models to reproduce aerosol extinction and optical thickness profiles and represent horizontal and vertical variations in aerosol types. This presentation will describe how the HSRL measurements were used to assess these models as well as how the model simulations were used to help interpret the HSRL measurements. Simulations from several models will be discussed. http://science.larc.nasa.gov/hsrl/index.html

A14D-07 

Reconciling bottom-up, top-down, and direct measurements of biogenic VOC emissions

* Guenther, A (guenther@ucar.edu), NCAR, 1850 Table Mesa Drive, Boulder, CO 80027, United States Karl, T (tomkarl@ucar.edu), NCAR, 1850 Table Mesa Drive, Boulder, CO 80027, United States Wiedinmyer, C (christin@ucar.edu), NCAR, 1850 Table Mesa Drive, Boulder, CO 80027, United States Barkley, M (michael.barkley@ed.ac.uk), University of Edinburgh, King's Buildings West Mains Road, Edinburgh, EH9 3JW, United Kingdom Palmer, P (pip@ed.ac.uk), University of Edinburgh, King's Buildings West Mains Road, Edinburgh, EH9 3JW, United Kingdom Muller, J F (jfm@aeronomie.be), Belgian Institute for Space Aeronomy, Avenue Circulaire 3, Brussels, B-1180, Belgium Stavrakov, T (jenny@aeronomie.be), Belgian Institute for Space Aeronomy, Avenue Circulaire 3, Brussels, B-1180, Belgium Millet, D (millet@eps.harvard.edu), Harvard University, Pierce Hall, 29 Oxford St., Cambridge, MA 02138, United States

Biogenic Volatile Organic compound (BVOC) emissions vary considerably on spatial scales ranging from a few meters to thousands of kilometers and temporal scales ranging from seconds to years. Accurate estimates of BVOC emissions are required for many regional air quality modeling studies and global earth system investigations. We compare results from bottom-up estimates, using The Model of Emissions of Gases and Aerosols from Nature (MEGAN), with top-down estimates, based on satellite and in-situ concentration distributions, and direct flux measurements. We describe examples of both agreement and disagreement in U.S., tropical forest and other landscapes and discuss potential explanations for differences that can exceed a factor of 2. Future measurement and modeling needs are outlined and specific activities are proposed to improve efforts to reconcile these approaches and understand the controlling processes.

A14D-08 

Assessment of Impact of Ship Emissions Over the Summertime Mediterranean

* Marmer, E (elina.marmer@jrc.it), European Commission JRC IES Climate Change Unit, TP 290, Ispra, VA 21020, Italy Vignatti, E), European Commission JRC IES Climate Change Unit, TP 290, Ispra, VA 21020, Italy Langmann, B), NUIG Department of Experimental Physics, University Road, Galway, none, Ireland Dentener, F), European Commission JRC IES Climate Change Unit, TP 290, Ispra, VA 21020, Italy Hjorth, J), European Commission JRC IES Climate Change Unit, TP 290, Ispra, VA 21020, Italy Velchev, K), European Commission JRC IES Climate Change Unit, TP 290, Ispra, VA 21020, Italy Cavalli, F), European Commission JRC IES Climate Change Unit, TP 290, Ispra, VA 21020, Italy van Aardenne, J A), European Commission JRC IES Climate Change Unit, TP 290, Ispra, VA 21020, Italy

The summertime Mediterranean atmosphere is one of the world's most polluted regions in terms of photochemical ozone formation and aerosol loading. Meteorological conditions during the summer favor the accumulation of primary emitted pollutants, high solar radiation intensity enhances the formation of secondary gases and aerosols. Removal of pollutants by precipitation is inhibited by summertime aridity. The seagoing ships as sources of air pollution and global climate change give cause for growing concern. This study investigates their contribution to the atmospheric pollution over the Mediterranean. Ship emission inventories widely differ due to different methodologies applied (top-down and bottom-up). In 2005, the JRC has launched a measurement campaign on board of a Mediterranean cruise ship, sampling ozone and black carbon, as well as aerosol size distribution. This unique data set is a valuable contribution to establishing the Mediterranean atmosphere pollution levels. We have utilized two different models and three different emission inventories to tackle this problem and to assess which of the inventories produces better results as compared to observations. The global chemistry transport model TM5 (Krol et al., 2005) with the zoomed finer resolution over Europe and the North Atlantic, samples ozone and aerosols "synchronous" with the cruise ship. Two different global ship emission inventories have been implemented, and the model results have been evaluated with the ship samples. Modelled and observed ozone values frequently exceed 60 ppb during spring and early summer. The contribution of ship emissions to the ozone levels is below 10% if the EDGAR* (with modifications for OC and BC) ship emissions are applied, it reaches well over 15% during summer in Western and Central Mediterranean with the Eyring et al. (2005) ship emission inventory, being in better agreement with the ship measurements. The opposite is true for the black carbon, its contribution from ships is below 10% applying the Eyring et al. (2005) ship emissions, but over 40% close to the main ship routes with the EDGAR* inventory, which performs better for black carbon. The advantage of the global model is its ability to simulate the cross continental transport of air pollution into the Mediterranean and thus to distinguish its contribution from the local pollution. To take advantage of a finer resolved regional Vestreng (2003) ship emission inventory we have utilized the regional atmosphere chemistry model REMOTE (Langmann, 2000). Partitioning SOx emissions into land and water sources was applied to investigate their respective impact on the sulfate aerosol concentration, the total aerosol burden and the direct radiative forcing (Marmer and Langmann, 2005). 54% of the total sulfate aerosol column burden over the Mediterranean in summer was attributed to ship emissions. The model performance was better over the Eastern Mediterranean, where land emissions dominated the atmospheric composition, while over the Western Mediterranean the simulated concentrations were underestimated, allowing the conclusion that the implemented ship emissions of SOx were underestimated. Combining both models, the three inventories and the ship and coastal measurements we quantify the impact of ship emissions and outline the strengths and weaknesses of each of the available inventories.