Atmospheric inverse models

Heimann M, Kaminski T. 1999. Inverse modelling approaches to infer surface trace gas fluxes from observed atmospheric mixing ratios. In Bouwman AF, ed. Approaches to Scaling of Trace Gas Fluxes in Ecosystems. Amsterdam Elsevier. 

Hein R, Crutzen PJ, Heimann M. 1997. An inverse modeling approach to investigate the global atmospheric methane cycle. Global Bio geochemical Cycles 11 43-76. 

Houweling S, Kaminski T, Dentener F, Lelieveld I, Heimann M. 1999. Inverse modeling of methane sources and sinks using the adjoint of a global transport model. Journal of Geophysical Research-Atmospheres 104 26137-26160. 

Complex reaction kinetics often incorporate processes of the preceding type and the inverse. Modeling the earth s atmosphere necessitates a detailed knowledge of its photochemistry, including the vibrational excitation and deexcitation of N2, 02, OH, and so on in E-V-R transitions with atoms and molecules. This has been reviewed by a number of authors,6 9 and an informative survey is given in Chapter 6, of the first volume of this book.10... 

Bousquet P., Peylin P., Ciais P., Ramonet M., and Monfray P. (1999) Inverse modelling of annual atmospheric CO2 sources and sinks 2. Sensitivity study. J. Geophys. Res. Atmos. 104(D21), 26179-26193. 

Inverse modeling atmospheric data Poor in tropics Monthly to annual No High North South Low East-West... 

A second top-down method for determining oceanic and terrestrial sinks is based on spatial and temporal variations in concentrations of atmospheric CO2 obtained through a network of flask air samples (Masarie and Tans, 1995 Cooperative Atmospheric Data Integration Project—Carbon Dioxide, 1997). Together with models of atmospheric transport, these variations are used to infer the geographic distribution of sources and sinks of carbon through a technique called inverse modeling. 

Figure 6 Terrestrial and oceanic sources and sinks of carbon inferred from inverse calculations with an atmospheric transport model and spatial and temporal variations in CO2 concentrations. The net fluxes inferred over each region have been averaged into 7.5°-wide latitude strips (Ciais et al., 2000) (reproduced by permission of the Ecological Society of America from Bcol. Appl, 2000, 10, 1574-1589).

One classic Gaussian plume model for smokestack emissions is the Pas-quill-Gifford model, which applies for steady emissions of a chemical over relatively level terrain. If no chemical sinks exist in the air (i.e., no reactions are degrading the chemical) and if there is an unlimited mixing height (i.e., no atmospheric inversion exists, and the plume can be mixed upward indefinitely), the Pasquill- Gifford model can be expressed in the form... 

A combination of the forward and inverse modelling approaches allows to solve some environmental and nuclear risk problems more effectively compared with the traditional ways based on the forward modelling. For the inverse modelling problem, most of the western scientists (Persson et al., 1987 [491] Prahm et al., 1980 [509] Seibert, 2001 [569]) use the common back- trajectory techniques, suitable only for the Lagrangian models. The Novosibirsk scientific school established by G.I. Marchuk in Russia has suggested a fruitful theoretical method for inverse modelling, based on adjoint equations (Marchuk, 1982 [391], 1995 [392] Penenko, 1981 [486]) and suitable for the Eulerian models. This approach has further been used and improved by several authors (Baklanov, 1986 [20], 2000 [25] Pudykiewicz, 1998 [512] Robertson and Lange, 1998 [538]) for estimation of source-term parameters in the atmospheric pollution problems. 

Bousquet, R, Ciais, P., Peylin, R, Ramonet, M., and Monfray, P. (1999a). Inverse modelling of annual atmospheric CO2 sources and sinks. 1. Method and control inversion./. Geophys. Res. 104,26161-26178. Bousquet, R, Peylin, R, Ciais, R, Ramonet, M., and Monfray, P. (1999b). Inverse modelling of annual atmospheric CO2 sources and sinks, 2, Sensitivity study. /. Geophys. Res. 104, 26179-26193. 

Kaminski, X, Heimann, M., and Giering, R. (1999). A coarse grid three-dimensional global inverse model of the atmospheric transport 2. Inversion of the transport of COj in the 1980s. /. Geophys. Res.-Atmos. 104, 18555-18581. 

Recently, Rayner et al. (1999) developed a 3D time-dependent inversion model to determine interannual variability in the regional terrestrial and oceanic uptake of fossil-fuel CO2 over the last two decades. The Rayner et al. study is used here as a benchmark against which the potential for improved precision and spatial resolution of flux estimates from atmospheric composition measurements is explored. 

EF)i is the emission factor (amount of emissions per unit activity, for example, kg sulfur emitted per kg coal burned), and Pu, P2i... are parameters that apply to the specified source types and species in the inventories (for example, sulfur content of the fuel, efficiency of the eontrol technology). Top-down methodologies, also known as inverse modeling, derive emission estimates by inverting measurements in combination with additional information, such as the results of atmospheric transport and transformation models. 

DoD laboratories have limited capabilities to develop or refine environmental agent dispersion or infection outbreak models. DTRA has recently funded significant R D activity to develop and test improved atmospheric dispersion models, including inverse models that predict agent release point and size from downwind concentration data. Most groundbreaking environmental dispersion research is currently performed in other US Government laboratories (e.g. National Center for Atmospheric Research (NCAR), LLNL, Sandia National Laboratory (SNL), Los Alamos National Laboratory (LANL)) or in academic or private sector laboratories. 

Mikaloff Fletcher, S.E., Tans, P.P., Bruhwiler, L.M., Miller, J.B., Heimann, M., 2004. CH4 sources estimated from atmospheric observations of CH4 and its C/ C isotopic ratios 1. Inverse modeling of source processes. Global Biogeochem. Cycles. 18, GB4004. http // dx.doi.org/10.1029/2004GB002223. 

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