SCIENCE/TECHNICAL/MANAGEMENT 1. OBJECTIVES & EXPECTED SIGNIFICANCE 1.1 Research Objectives Introduction. A major goal of planetary exploration is a fundamental understanding of planetary environments, both at present and in the past. This information is needed for defining the scientific goals for future exploration. For example, one such goal is understanding planetary habitability and the origin of life, which is part of the history of our planet and the Solar System. Titan occupies a unique place because it possibly resembles the chemical environment at the time of the origin of life on Earth in having (1) a thick N2 atmosphere, (2) a reducing atmospheric composition, (3) energy sources for driving disequilibrium chemistry and (4) an aerosol layer for shielding the surface from solar UV radiation. Indeed, Titan is Nature’s laboratory for organic synthesis, simulating an environment that has been permanently destroyed on Earth due to the emergence and evolution of life (Coustenis and Taylor 1999; Lunine, 2005; Lorenz and Mitton 2008). Methane, the parent molecule of hydrocarbons, is ubiquitous in reducing atmospheres. Photolysis of methane results in synthesis of more complex hydrocarbons. This chemistry has the following implications: (1) The hydrocarbon chemistry is unique and rich and the same reactions apply to all atmospheres in the outer Solar System; (2) The hydrocarbon chemistry inevitably leads to formation of high molecular weight products (CxHy), eventually giving rise to organic aerosols; (3) The higher hydrocarbons and aerosols exert a profound influence on atmospheric radiation by shielding the surface from UV radiation, and by creating a thermal inversion in the middle atmosphere, which, in turn, strongly impacts atmospheric circulation. The Cassini measurements provide an opportunity to study in depth the chemistry and energetics of Titan’s atmosphere to test the above ideas and to explore the consequences of this chemistry for atmospheric evolution, and the chemical nature of the surface of Titan (Tobie et al. 2006; Lorenz et al. 2008). The proposed research is a step towards the “big picture” envisioned in Fig. 1, which illustrates the interactions between photochemistry, transport, surface processing and cryovolcanism (Choukroun and Sotin 2012). Significant recent results from Cassini are: (1) quantitative information on the spatial and temporal distribution of chemical species in the stratosphere, mesosphere and thermosphere, (2) quantitative estimates of carbon reservoirs in the lakes and dunes, and (3) quantitative measurements of isotopic fractionations for key H, C, O and N containing species. These highlights and how they impact the “big picture” in Fig. 1 will be elaborated as follows. Titan, like the Earth, Fig. 1. Illustration of the CH4 cycle on Titan, including experiences a pronounced seasonal interactions between photochemistry, transport, surface and cycle, as illustrated in Fig. 2. Cassini sub-surface processing, and cryovolcanism. Taken from Choukroun and Sotin (2012). arrived at Titan in 2004, about 2 years 1 after winter solstice (given by Ls = 270). Fig. 3 shows altitude-latitude cross-sections of the temperature and chemical species C2H2, HCN, HC3N, C3H4 and C4H2. The temperature and the chemical species all show enhanced values in the northern polar region. The characteristics of the observations suggest a meridional circulation that consists of a rising branch in the summer pole and a descending branch in the winter pole, as presented in Fig. 4. The higher temperature in the northern polar region is the result of adiabatic compression. Chemical species are enhanced due to photochemical production in the sunlit part of the stratosphere, followed by transport to the winter polar vortex, where they are partly shielded from photolysis. One of Cassini’s significant achievements is the quantification of carbon reservoirs on the surface of Titan, as summarized in Table 1. The surface reservoirs contain a total of about 10 global equivalent Fig. 2. Seasonal cycle of Titan. Vernal equinox is defined by L = 0. s layer meters (GELm) of carbon, which is of the same order of magnitude as the amount of CH4 in the present atmosphere. However, atmospheric CH4 on Titan has a mean lifetime about 20 Myr (see, e.g., Wilson and Atreya 2009), and the cumulative loss over the age of the Solar System is on the order of 120-1200 GEL-m (Lorenz and Lunine 1996), which is incompatible with the known surface carbon reservoirs. This fundamental conflict forces us to abandon the Copernican (or Uniformitarianism) Principle (Bondi, 1952) and to accept the episodic nature of outgassing of CH4 on Titan. Fig. 5 shows a model of episodic outgassing of CH4 that is postulated to be stored as clathrate hydrates in the interior of Titan (Tobie et al. 2006). According to this model, Titan has three major episodes of outgassing: first, near the time of formation; second, during the time of convection in the silicate core; third, during the time of convection in the outer icy layer. During most of the past history of the Solar System, Titan’s dense atmosphere might have collapsed, entering a snowball state resembling that of Triton (Lorenz et al. 1997). Human observers arrive at a privileged time during the third episode of outgassing, perhaps gaining a sobering insight into the transience and Table 1. Carbon Inventory on Titan in global equivalent fragility of the only other dense N2 layer (GEL) meters based on Table 1 of Lorenz et al. (2008). atmosphere in the Solar System, a lesson that may be important for Reservoir Inventory (GEL-m) humanity contemplating the destiny of Atmospheric CH4 10 its own atmosphere (see, e.g., Chapter CH4/C2H6 in lakes 0.4-4 10 of Yung and DeMore 1999). Sand dunes 2.5-10 Is there independent Cumulative loss of CH4 120-1200 confirmation of the overthrow of the 2 Copernican Principle for Titan? The answer may lie in the interpretation of the isotopic fractionation data for selected atmospheric species summarized in Table 2. Of special significance are the remarkable measurements of four isotopologues of methane, CH4, CH3D, 13CH4, and 13CH3D, providing unprecedented accuracy as well as internal consistency for the ratios D/H and 12C/13C, by Nixon et al. (2012). The authors concluded that, based on the observed 12 13 C/ C, CH4 entered the atmosphere 60-1600 Myr ago (model 1) if atmospheric CH4 is depleted according to the currently known chemistry. An alternative model (model 2) that Fig. 3. Altitude-latitude cross-sections of temperature and chemical includes hydrodynamic escape of species C2H2, HCN, HC3N, C3H4 and C4H2 around the period 2004 to CH4 implies an even shorter 2007, corresponding to Ls from 300 to 330. Taken from Fig. 3 of history of 10 Myr. Note that both Teanby et al. (2008). models suggest that CH4 in the atmosphere of Titan is transient, although the difference between models 1 and 2 is significant (see later discussion). The isotopic data thus provide compelling evidence that the CH4 is young. Unresolved Problems. Despite the great progress described above, there remain major unsolved problems. There is no model that Table 2. Isotopic composition of selected chemical quantitatively relates the observed species in the atmosphere of Titan (adapted from chemical species and their seasonal Bézard et al. 2013). For comparison, reference values for the terrestrial atmosphere are listed. variability (e.g., Figs. 2 and 3) to the atmospheric circulation (e.g., Fig. 4), Isotope Terrestrial chemical production and loss, and Species Titan Observation Ratio Reference formation of aerosols and their deposition D/H H2 (1.35 0.30) 10-4 1.56 10-4 on the surface. There is no model that can CH4 (1.59 0.33) 10-4 -4 satisfy the present observational C2H2 (2.09 0.45) 10 12 13 constraints and systematically interpret the C/ C CH4 86.5 ± 8.2 89.4 isotopic measurements as summarized in C2H2 84.8 ± 3.2 Table 2 in terms of the origin and C2H6 89 ± 8 14 15 evolution of the atmosphere of Titan. If for N/ N N2 270 167.0 0.6 65 ± 12 ~90% of the history of the Solar System HCN 76 ± 6 Titan’s atmosphere was in a collapsed 16 O/18O CO 499 380 60 snowball state, what is the photochemistry CO2 346 ± 110 in that state, and what are the observable 3 Fig. 4. Schematic of the dynamical processes in the northern polar region of Titan. Taken from Fig. 4 of Teanby et al. (2008). Fig. 5. Outgassing of CH4 over the history of Titan. The values, 10 and 50% (in red) refer to the fraction of clathrate mass remaining in the crust before the onset of convection. The outgassing rates are given in units of current atmospheric CH4 loss, 1.25x1010 molecules cm-2 s-1. Taken from Fig. 2a of Tobie et al. (2006). consequences today? As Nixon et al. (2012) pointed out there is a serious conflict between the short history of CH4 (10 Myr in their model 2) and a currently favored model for the origin of CO that requires 300 Myr to produce it photochemically using the influx of O+ from the top of the atmosphere (Hörst et al. 2008). Model 1 of Nixon et al. (2012) yields a longer lifetime for the CH4 atmosphere, 60-160 Myr, but this model (without CH4 escape) may be ruled out by the INMS measurements in the thermosphere of Titan (Yelle et al. 2008; Strobel 2009), unless there is a self-consistent re-interpretation of the INMS data without invoking an escape flux for CH4. Proposed Research. To address the above problems we propose a detailed study of the photochemistry of the atmosphere of Titan using the Caltech/JPL KINETICS model, including the following tasks: (1) Meridional transport in the atmosphere of Titan taken from outputs of state-of-the-art general circulation models (GCMs); (2) Updated photochemistry in the 4 atmosphere of Titan; (3) Modeling the isotopic fractionation of key chemical species in the atmosphere of Titan; (4) Evolution of the atmosphere of Titan. These four related tasks address the key unsolved problems discussed above. They are particularly relevant to NASA's Planetary Atmospheres program because they contribute to “the determination of compositions, dynamics, energetics, and chemical behaviors of planetary atmospheres” and “the understanding of the origins and evolution of the atmospheres of planets and their satellites.” The details will be given in the following sections. 1.2 Scientific Significance of Proposed Research The proposed work is motivated by the question: What are the rigorous quantitative tests of our models for planetary atmospheres? A correct understanding of the current atmospheres provides the key for understanding synergistic interactions between chemistry, radiation and dynamics, as well as isotopic fractionation and atmospheric evolution. Studying other planets may not provide all the answers for the Earth, but it will certainly enrich our understanding by extending the parameter space, especially to include conditions believed to have existed in the early history of Earth, such as a mildly reducing atmosphere at the time of the origin of life and snowball episodes (Liang et al. 2006). Our experience in modeling Titan’s atmosphere suggests that the fundamental challenge is to understand the complex hydrocarbon chemistry that leads to the formation of photochemical products, which in turn affects the dynamics in the atmosphere and chemical nature of the surface of Titan (Lorenz et al. 2008). This research is a step towards understanding the “big picture” envisioned in Fig. 1. 1.3 Summary of Work Performed in the Previous Grant Period The complete list of publications and conference presentations supported by existing NASA award NNG06GF33G is listed in the References and Citations. The work proposed here is expected to build on previous accomplishments supported by NASA. Contributions to Human Resources. Former graduate students Xi Zhang and Michael Line were partly supported by this grant; they completed their Ph.D.s in 2013. Zhang is now a Bisgrove Postdoctoral Scholar at the University of Arizona; Line will be a postdoc at UC Santa Cruz. Summer student Elias Ellison and current graduate students Joshua Kammer and Cheng Li are partly supported by this grant. 2. TECHNICAL APPROACH & METHODOLOGY We propose to use the Caltech/JPL CTM (chemical transport model) to simulate the latitudinal and seasonal distribution of the H, C, N, O species and aerosols. Here is a brief description of our model. In the current operating mode, the CTM is a time dependent model of the global atmosphere in two dimensions (pressure and latitude), composed of four modules: the chemical module, the solar radiative module, the infrared radiative module, and the transport module. The photochemical module, the solar radiative module, and the infrared radiative module all are able to be used in the 2-D model as in the 1-D model, with only minor code adjustments. 2.1 Task I: Meridional Transport in the Atmosphere of Titan There is urgent need for a realistic, physics-based CTM to explain the meridional distribution of the hydrocarbons. An innovative feature of the proposed research is the coupling of our photochemical model to transport derived from full physics GCMs. No previous 2D model of Titan extends above 500 km (Lebonnois et al. 2001, 2003, 2009; Hourdin et al. 2004; 5 Crespin et al. 2008), even though the peak of CH4 photolysis is at 800 km. We propose to build the first 2D model that includes the stratosphere, mesosphere and thermosphere. Outputs from Titan GCMs. The meridional circulation in our 2D model will be derived from the outputs of two general circulation models (GCMs): a TitanWRF for the troposphere, stratosphere and mesosphere, and a thermosphere general circulation model (TGCM) for the thermosphere. TitanWRF is a global GCM, developed from the terrestrial, limited-area WRF (Weather, Research and Forecasting) model as described in Richardson et al. (2007) and Newman et al. (2011). The model has 54 vertical layers from the surface to about 420 km in a Fig. 6a. Mass streamfunction (in kg/s) from year 75 of standard TitanWRF v2 simulation, averaged over 12 Titan days around the winter (Ls = 270°) solstice. Positive streamfunction values indicate clockwise rotation. Taken from Fig. 8 of Newman et al. (2011). modified sigma coordinate (a version of the model under development will be extended to ~500 km). The standard horizontal resolution is 5.625° in longitude and 5° in latitude. The model is successful in reproducing the observed superrotation of Titan’s atmosphere. The mass streamfunction for the northern winter solstice is presented in Fig. 6a, revealing a pole-to-pole circulation in the stratosphere that rises at the southern (summer-) pole and descends into the northern (winter-) pole. Fig. 6b. Top: Meridional winds on Titan from In the upper atmosphere, we will derive our 2D the stratosphere to the thermosphere, as transport from a thermosphere general circulation simulated by the Titan WRF (850-3 µbar) and -7 model (TGCM) built by Müller-Wodarg et al. Titan TGCM (3 µbar-5x10 µbar) for (2000, 2003, 2008). The TGCM extends from 500 conditions of southern hemisphere summer solstice. Bottom: same as left for zonal wind. to 1400 km (3 to 0.9x10-9 μbar); Müller-Wodarg has recently extended the model to 400 km, so that it overlaps with the TitanWRF at the lower boundary. Meridional and zonal winds from this model are shown in Fig. 6b. The TGCM is driven at its lower boundary by global time-dependent wind forcing from the Titan WRF, thus providing the first global calculations of vertical dynamical coupling in Titan's atmosphere. The model has been validated against Cassini observations of density and temperature in the thermosphere (Müller-Wodarg et al. 2008). Collaborators Newman and Müller-Wodarg will provide our team with standard GCM outputs, from which the 6 2D meridional circulation will be derived by a method developed by our group for planetary atmospheres (see below). 2D Meridional Circulation. A method developed by our group (see Jiang et al. 2004) based on the work of Held and Schneider (1999) and Schneider (2005) will be used to calculate the meridional circulation. Circulations calculated using this method have successfully simulated the variability in the total column ozone in the terrestrial atmosphere (Jiang et al. 2004). The following is a brief description of the method. Temperature, horizontal wind, meridional wind, and pressure outputs from a GCM are used to calculate the stream function. On the pressure surface, the three-dimensional (3-D) meridional mass flux, y P (l , j , p) , can be calculated by the following equation: 2p a cos j p y P (l , j , p ) = òo V (l,j , p¢)dp¢ , (1) g where a is the planet’s radius, l , j , p are the longitude, latitude and pressure (p = 0 refers to the top of the atmosphere), V is the meridional velocity, and g is the gravitational acceleration rate. Then we interpolate the 3-D meridional mass flux to isentropic surfaces, using a massconserving linear interpolation scheme (Juckes et al. 1994). The 2-D isentropic mass stream function, y q (j ,q ) , is derived by zonal averaging of the 3-D isentropic meridional mass flux, y q (l , j ,q ) , along isentropes. Finally, we interpolate the 2-D isentropic mass stream function, y q (j ,q ) , to pressure coordinates and scale by the density to produce the pressure surface stream function, y P (j , p) . Fig. 7 shows the mean streamfunction in the terrestrial atmosphere in January calculated from GCM outputs (NCEP2, Kanamitsu et al. 2002) for 1979 to 2002, an example of the mass streamfunction calculated using the above method. The air is drawn upward and poleward from the tropics and pushed downward into the extratropical troposphere by waveinduced forcing (Holton et al. 1995). This circulation is important for the transport of water vapor and ozone between the troposphere and the stratosphere. Comparing Figs. 6a and 7, we notice that the mass streamfunction on Earth is about 100 times larger that that on Titan. Modern 2D CTM. The simulations of the zonally averaged global distribution of stratospheric hydrocarbons will use a 2D CTM optimized for computational efficiency and its ability to handle a large number of atmospheric chemical species and reactions. A new version of the Caltech/JPL 2D model has been developed to provide these capabilities. This new version will be referred to as the hybrid 2D model (H-2D model). The H-2D preserves the advantages of the 1D model to rapidly compute the coupling between complex chemistry and vertical mixing Fig. 7. (a) Mass stream function for January in the terrestrial (both eddy and molecular diffusion). atmosphere (Jiang et al. 2004). The positive contours (solid The heritage of the planetary H-2D lines) are 0.1, 0.2, 0.5, 1, 2, 5, 10, 20 and 50. The negative model is two-fold: (1) the Caltech/JPL 1D contours are -0.1, -0.2, -0.5, -1, -2, -5, -10 and -20. The units model that has been broadly applied to are 109 kg/s. 7 planetary atmospheres throughout the Solar System by different investigators (Clancy et al., 1987; Summers et al., 2002; Moses et al., 2005) and (2) the Caltech/JPL 2D model that has been applied to simulations of the terrestrial atmosphere (e.g., Morgan et al., 2004; Liang et al. 2008) and the atmosphere of Venus (Yung et al. 2009). In reality both the 1D and 2D models are modes of a single unified CTM, in which the chemistry and ultraviolet/visible radiative transfer software components are shared among all the different transport model modes. In the 1D mode, the continuity equation with chemistry and diffusion is solved simultaneously using a matrix inversion method. This allows large time steps (>Courant limit) to be taken. Due to the limitation of computing power, we cannot apply this inversion method to the 2D model. Instead, in the 2D model, a time splitting procedure for solving the 2D continuity equation has been adopted. In each time step, the different processes of chemistry, diffusion and advection in different directions are calculated sequentially. Note that both transport schemes (1D and 2D) are positive definite and have minimal numerical diffusion. As long as the time step is small enough compared with the time scale of the different processes, the model simulations are independent of the order of the processes being calculated and the model results are acceptable. The validity of the numerical method for solving the continuity equation was tested against analytic solutions first derived by members of our science team (Shia et al., 1990; Landry et al., 1991). The H-2D model takes a new approach to efficiently simulating planetary atmospheres. The chemistry and vertical diffusion are solved simultaneously as a 1D problem at different latitudes. Then, the horizontal diffusion and the advection in the horizontal and vertical directions are treated sequentially in the time-splitting approach. To test this new operational mode, numerical experiment 4 in Shia et al. (1990, see their Fig. 9d) was expanded using the H2D (Zhang et al. 2013b). The numerical results are based on our H-2D code, which is able to reproduce the analytical results almost perfectly. The largest differences between the analytical and numerical simulations are found at the two poles, but even there the errors are less than 4%. Considering the dynamical range of the chemical species simulated in the model, this test is a significant step beyond Shia et al. (1990), and provides confidence in the results derived from our CTM. The lower and upper boundary levels for the H-2D will be 250 mbar and 0.9x10-9 μbar, respectively. In the region near the upper boundary, we have UVIS data (Koskinen et al. 2011; Kammer et al. 2012) to constrain our model. The chemical model to be employed is based on Gladstone et al (1996) with updates drawn from Moses et al. (2005). Updates to the chemical kinetics and their uncertainties will be discussed in a later section. Previous efforts to use the Caltech/JPL H-2D to understand trace gas redistribution in the Jovian stratosphere have been reported in Liang et al. (2005) and Zhang et al. (2013a). The 2D model currently is being parallelized using the Message Passing Interface standard. This will enhance the computational speed and make simulations with large chemical reaction networks practical. 2.2 Task II: Photochemistry in the Atmosphere of Titan The chemistry and ultraviolet/visible radiative transfer codes are common to any of the KINETICS transport modes. The chemistry code utilizes a reaction library that includes both neutral and ion reactions. For any specific simulation, the selection of chemical species for the simulation determines which reactions from the library are activated. In a series of papers published by the Caltech/JPL group and groups in other institutions using KINETICS, the chemical composition of the atmospheres of Venus, Earth, Mars, Jupiter, Saturn, Titan, Neptune, 8 and Triton have been reproduced with reasonable accuracy. The 2-D model has been used by Yung and Miller (1997), Morgan et al. (2004) and Jiang et al. (2004) to study the spatial and temporal patterns of chemical species in the terrestrial stratosphere, by Liang et al. (2005) and Zhang et al. (2013a) to simulate the meridional distributions of C2H6 and C2H2 on Jupiter and by Yung et al. (2009) to model the sulfur chemistry on Venus. Much of the chemistry can be explored in the 1-D mode. However, with its large obliquity, Titan exhibits a pronounced seasonal cycle. During the polar night, the mesosphere is exposed to solar ultraviolet radiation, while the lower atmosphere is in darkness. Organic synthesis can readily occur and the products are transported downward into the polar cap stratosphere, which stays in the shadow of Titan. This process can lead to a significant accumulation of organic species, a scenario similar to the building up of O3 in the winter and early spring in the polar regions of the Earth’s stratosphere. Thus a 2-D model is required to adequately explore this intricate interaction among chemistry, radiation and dynamics. Photochemistry. Preliminary 1-D modeling results were reported by Liang et al. (2007a) for 12 major species: N2, H2, CH4, C2H2, C2H4, C2H6, C4H2, C6H6, C6N2, C2N2, HCN, HC3N and tholins (see their Table 1 and Fig. 3; see also updates by Li et al. 2012). The photochemical model will be updated in light of new kinetic data that have become available (e.g., Vuitton et al. 2012; Dutuit et al. 2013). One of the salient features of chemistry on Titan is the formation of organic aerosols, an inevitable consequence of gas-phase organic synthesis with the growth of larger molecules limited by condensation and coagulation (see, e.g., Lavvas et al. 2009, 2013). Initial simple condensates of gas-phase constituents and subsequent reactions in the condensed phase can lead to formation of chemically complex, low volatility organic aerosols. The latter material is the colored, visible haze in the Titan atmosphere, with the particles being the tholins well known in the scientific literature. Cassini observations have yielded spectacular new results on aerosols. The first is the discovery of multiple aerosol layers high in the atmosphere. In addition, there is compelling evidence for small tholin particles (radius ~20-100 Å) above 400 km from independent analyses of Cassini UVIS data (see Fig. 2 of Liang et al. 2007a; Fig. 1 of Ajello et al. 2008; Lavvas et al. 2009, 2010, 2011; Cours et al. 2011; Koskinen et al. 2011). The temperature profile in Titan’s atmosphere produces the super-saturations of methane and ethane that is needed to condense these gases to form clouds, provided that sufficient cloud condensation nuclei (CCN) are present (Tokano et al., 2001; Samuelson and Mayo, 1997; Guez et al., 1997). Recently published measurements of the heterogeneous nucleation of butane on laboratory-generated tholins suggest that these particles are lyophobic, requiring super-saturation in excess of 1.3 to induce activation. In those experiments, butane condensation was observed in a thick, porous deposit of solid tholin particles. The activation behavior is further complicated by the complex structures of solid particles that form by homogeneous nucleation and grow by a combination of vapor deposition and coagulation (Friedson et al., 2002). Further evolution of organic composition occurs as the simple condensate aerosols are transformed into complex tholins in the presence of solar radiation. The chemical synthesis of large, non-volatile organic compounds from simple organic compounds through only photochemical pathways has been demonstrated in many published laboratory experiments (for recent examples, see Adamkovics and Boering 2003, Tran et al. 2003a,b). That photochemistry is currently believed to be the dominant driver of organic chemistry at the haze altitudes warrants new and quantitative approaches to extend the state of knowledge of Titan aerosol chemistry and organic growth. One area of photochemistry that has been largely 9 neglected is longer wavelength UV photochemistry (200–300 nm); only the photon flux at long wavelengths may be present at altitudes below 600 km. Consequently primary photochemical processes may be significantly reduced owing to insufficient photon energies to produce high yields of active organic free radicals. At the shorter end of this spectral range, in the region below 230 nm, photoexcitation of reagents such as the diacetylenes or cyanoacetylenes can lead to bond scission with radical generation (Titarchuk and Halpern 2000). The NC-C2H bond energy in cyanoacetylene corresponds to photon energy of 199 nm while the CH bond scission in acetylene requires photon energies below 230 nm (see Okabe, 1978). As discussed in the previous section, the radicals in the gas phase induce a wide range of complex addition/substitution reactions that can lead to molecules of greater complexity than the original parent. For instance, diacetylene is known to form conjugated polyynes H-(C2)n-H molecules (n=3-4) when irradiated in the 230 nm region in the gas phase through stepwise radical addition processes (Arrington et al. 1999). The primary products of acetylene vapor photolysis appear to be ethylene, diacetylene, vinylacetylene and benzene with some production of polymer (Zelikoff and Aschenbrand 1956). While these radical chain polymerizations can be even more effective in condensed phases, irradiation of solid diacetylene ice yields complex mixtures of highly polymerized poly-acetylenes and poly-diacetylenes owing strongly to the oriented nature of the reactive chromophores in the solid, conducive to efficient polymer chain growth dynamics of the closed shell molecules (Basilevsky 1985). At longer wavelengths much above 230 nm, excitation leads predominantly to electronically excited states which can lead to a different set of molecular rearrangements or additional products, especially with near neighbors in the condensed phase. Diacetylene solids have long been known to photo-polymerize with near unit efficiency producing solid polymers containing very low fractions of monomers. Wegner (1979) suggests that diacetylene polymerization initiated by electronically excited (non-fragmented) monomer can proceed through production of conjugated carbene intermediates and can carry the chain polymerization in condensed phase. Recently, Gudipati et al. (2013) demonstrated photopolymerization of C4N2 (dicyanoacetylene) at wavelengths as long as 355 nm. There are two major consequences of the effects of the aerosols in the atmosphere. The first is shielding of UV radiation in the stratosphere. We will use aerosol concentration and optical properties derived by Lavvas et al. (2009, 2010, 2011). The electronic files have been made available to our team (P. Lavvas, private communication, 2013). The second potentially important effect is the scavenging of H atoms by aerosols. We will model this effect on the photochemistry in the atmosphere using the aforementioned aerosol data from Lavvas and kinetic data from Sekine et al. (2008a, 2008b). An Innovative Method to Compare Model to Observations. The results of our modeling of chemical species and aerosols will be compared to Cassini and ground-based observations (Coustenis et al. 2007; Teanby et al. 2007, 2008; Roe et al. 2004; Vinatier et al. 2010; Koskinen et al. 2011; Kammer et al. 2012). It has been noted that long-lived species such as CO and CO2 have nearly uniform meridional distributions (de Kok et al. 2007), while the short-lived species have steep latitudinal gradients (see, e.g., Fig. 3 and Teanby et al. 2008). For short-lived species and aerosols, there is significant variability with season (Bampasidis et al. 2012; West et al. 2011). Therefore, the correct simulation of all observed chemical species and aerosols could provide a stringent test of the chemistry-transport model, to within the uncertainties of the observations and model input parameters. How this is done systematically will be described below. In atmospheric studies, we very often encounter an intriguing problem. In trying to explain observed data, there is usually a conflict between what the data are telling us and what 10 the model predicts from fundamental principles. This conflict would be irreconcilable if the data were perfect and the model absolutely correct. In reality, the data have measurement errors and the model has adjustable parameters. The “adjustable parameters” often include aerosol properties, chemical rate coefficients and transport coefficients. The optimal estimation method (OEM) is a common tool in retrieval algorithms for estimating atmospheric variables from satellite measurements (Rodgers 2000). More advanced methods such as the adjoint method have also been used to study the sensitivity of a timedependent system to kinetic parameters (Sandu et al., 2003). Since we will be dealing only with steady states, OEM suffices and is much simpler to implement. Given that Y is the observed quantity, F is the forward model and k is a list of parameters to be varied, the OEM aims to minimize the following cost function: Y F k SY1 Y F k k k a S a1 k k a T T where SY is a diagonal matrix whose diagonal elements are the variances of the measurements, k a is the a priori and S a is also a diagonal matrix, whose diagonal elements are the uncertainties of k a . The second term on the right hand side limits the extent to which k is allowed to vary away from k a , so that the estimated k is consistent with the physical constraints. The “retrieved” profile F k thus represents the best fit of Y under the constraints of the best a priori knowledge and uncertainties of Y and k . A number of minimization algorithms can be employed to minimize ∆ with respect to k . We prefer the Levenberg-Marquart algorithm, which combines the advantages of the steepest-descent method (that ensures convergence but is computationally slow), and the Gauss-Newton method (that is computationally fast but does not guarantee convergence). This method (OEM) was recently developed by our group under previous NASA funding and applied successfully to the retrieval of aerosol properties in the atmosphere of Jupiter (Zhang et al. 2012b). OEM was also applied to the 1D model of the atmosphere of Titan, where we attempted to “retrieve” the eddy diffusion coefficient from 200 to 800 km (Li et al. 2012). The uncertainties in chemical kinetics in the chemical model have been explored by previous workers (Hebrard et al. 2005, 2006, 2009). Gans et al. (2013) performed Monte-Carlo simulations on their impacts on model predictions. However, all previous studies restricted themselves to testing uncertainties in a “forward model”. There was no attempt to confront the model with observations to extract an optimal solution that objectively takes into account the model and observational uncertainties. The proposed research will attempt to fill this gap between model and data. 2.3 Task III: Modeling Isotopic Fractionation in the Atmosphere of Titan Data on the isotopic fractionation of H, C, N and O species on Titan have recently become available (see Table 2). The study of the isotopic composition of the atmosphere of Titan is motivated by two objectives. First, the successful modeling of the isotopologues and isotopomers could provide valuable confirmation of the chemical schemes used for modeling the most abundant isotopic species. Second, we can derive insight into the origin and evolutionary history of the atmosphere from the isotopic fractionations (see, e.g., Pinto et al. 1986; Lunine et al. 1999; Mandt et al. 2009; Nixon et al. 2012), as discussed in the following. The observed isotopic fractionation in the atmosphere of Titan reflects chemical fractionation and fractionation caused by loss of material at the top of the atmosphere (Yelle et al. 2006, 2008; Strobel 2008). 11 We will incorporate three major improvements in our modeling of isotopic fractionation in the atmosphere of Titan: (1) updated chemical kinetics for isotopic fractionation, based on the extensive work of Nixon et al. (2012); (2) better production and loss rates using our 2D model described in the previous two tasks; (3) inclusion of the effects of fractionation in the condensation of species near the tropopause – these effects are known for CO2 and simple hydrocarbons (Eiler et al. 2000; Jancso and van Hook 1974), but have not been included in previous models of Titan. Hydrogen. The D/H ratio for three hydrogen-bearing species has been measured on Titan: CH3D, HD and C2HD. The D/H ratio for methane is 1.59 0.33 10-4, a value that should be compared to the protosolar value of 2.35 0.2 10-5. Part of the enrichment may be attributed to atmospheric evolution (Cordier et al. 2008) but not all of it (Mandt et al. 2009). We will use our model to investigate the causes of isotopic fraction for the hydrogen bearing species. We will explore four mechanisms in our model. One mechanism for the enrichment of CH3D is the photo-induced isotopic fractionation effect (PHIFE) proposed by Yung and Miller (1997). The idea is based on the difference between the zero point energies and the wavefunctions for isotopologues and has been applied to a number of molecules (Liang et al. 2004). The heavier isotopologue is usually more stable with respect to photolytic destruction and would be enriched as a result. The second mechanism for isotopic enrichment is the preferential destruction by C 2H of CH4 relative to CH3D (see discussion in Lunine et al. 1999). The third mechanism is due to isotopic exchange such as D + H2 H + HD and D + CH3 H + CH2D (see Lee et al. 2001). The fourth mechanism is the preferential escape of H and H2 over D and HD. The rate coefficients for isotopic species of hydrogen will be taken from Lee et al. (2001) and Parkinson et al. (2006), with updates. Carbon. There is little to add to the definitive modeling of 13C/12C by Nixon et al. (2012), except for improvements in the chemical production rates and possible effects of isotopic fractionation during condensation. The 13C/12C in C2H2 and C2H6 appears to be similar to that in CH4, within the limits of measurement uncertainties. Nitrogen. The isotopic composition of nitrogen from Table 2 is given by 14N/15N = 167, a value that should be compared to the terrestrial value of 272. Thus heavy nitrogen is isotopically enriched by about 50% relative to the Earth, as would be expected if there has been massive loss of nitrogen in the past (Lunine et al. 1999). However, this model is no longer favored and the current idea is that the isotopic ratio is primordial (Mandt et al. 2009). On the other hand in HCN we have 14N/15N ~70, indicating that there is be further enrichment in 15N during during the formation of HCN from the destruction of N2 (Liang et al. 2007b). We propose to continue the investigation of the outstanding problem related to the isotopic fractionation of nitrogen in HCN relative to N2. The Cassini observations suggest that 15N in HCN is about 100% enriched relative to N2 on Titan, or about 200% enriched relative to N2 on Earth. Preliminary modeling (Liang et al. 2007b) suggests that PHIFE coupled with self-shielding of UV by N2 is an important mechanism and could quantitatively account for the revised observed fractionation in HCN summarized in Table 2. Oxygen. The preferred model for the origin of CO and CO2 (Hörst et al. 2008) will be discussed in the next section. The ultimate source of O in the three observed oxygen-bearing species, H2O, CO and CO2, is most likely from Enceladus and the rings of Saturn. A careful modeling of the isotopic fractionation for these three species will be carried out and will shed light on the isotopic fractionation of the source. See the following section on implications for atmospheric evolution. 12 2.4 Task IV: Evolution of the Atmosphere of Titan As discussed earlier, a significant insight we obtained from Cassini data is that the CH4 in the atmosphere of Titan is recent, on the order of 10-100 Myr old. However, the latest model for the origin of CO (the fourth most abundant molecule) on Titan requires 300 Myr. A resolution of this conflict may lie in the chemistry of the atmosphere during the period when the atmosphere of Titan was in a collapsed snowball state. The chemistry in this atmosphere has not been investigated. To get an idea of what it may be like, we have to examine how the present atmosphere of Titan is maintained. How does the atmosphere generate and maintain the current state? Starting from a pure N2 and CH4 atmosphere, we can envision the following sequence of events (see, e.g., Yung et al. 1984 and more recent models by Wilson and Atreya 2004, Lavvas et al. 2008, Krasnopolsky 2009): (1) Photolysis of CH4 in the mesosphere leads to the production of C2H2, followed by transport to the stratosphere; (2) C2H2 builds up in the stratosphere; (3) Photolysis of C2H2 results in the photosensitized dissociation of CH4, producing CxHy, and aerosols; (4) Absorption of sunlight by aerosols leads to thermal inversion and dynamical stability; (5) Stratosphere becomes more stable, thus inhibiting vertical transport, resulting in a further increase of the abundances of higher hydrocarbons and leading back to step (3). Steps (3), (4), and (5) constitute a cycle with positive feedback and the cycle is ultimately limited by the availability of UV and visible photons. Therefore, the present atmosphere exists due to a delicate coupling between photochemistry, radiation, and dynamics, like “a house of cards”. To illustrate this, let us compare the total rate of destruction of CH4 by direct photolysis, 2.9x109 cm-2s-1 (step 1 above), with the total rate of destruction (mostly by step 2), 1.5x1010 cm-2s-1. On snowball Titan, direct photolysis would still have occurred as long as there was some small amount of CH4 in the atmosphere, but most of the photosensitized dissociation would have been absent. In addition, even the direct photolysis would have been reduced, as most of the photolysis on snowball Titan would have taken place near the surface. Today photolysis occurs at around 800 km. The reduction factor is roughly (2575km /3375km)2 ~ 0.58. Thus the total destruction rate of CH4 on snowball Titan would be ~1.7 x109 cm-2s-1, or an order of magnitude lower than the rate today. In other words, the present atmospheric chemistry would have collapsed like “a house of cards” on snowball Titan. The evolution model for CO and CO2 on Titan is based on Hörst et al. (2008). A major consequence of this model is that the CO in the atmosphere today was produced in 300 Myr, a time that is in conflict with other evidence (see discussion in the Introduction). We argue that during the time when Titan was in the snowball state, there was a residual atmosphere with a small amount of CH4, whose oxidation by exogenic O+ could continue to provide a source of CO. Very little is known about the snowball Titan except estimates of its surface temperatures under a range of assumptions (Lorenz et al. 1997). We propose to use these results as the boundary conditions and investigate the thermal structure and chemical composition of the atmosphere. A simple 1D model for temperature and photochemistry will be used to study this atmosphere, with the ultimate goal of assessing the possibility of CO production over extended periods. The radiative model will be adapted from Zhang et al. (2012a) for Jupiter. The chemical model of CO and CO2 will be adopted from Hörst et al. (2008) and Liang et al. (2005). The isotopic fractionation of the O-bearing species will be investigated using the model of Wong et al. (2002). We expect additional isotopic fractionation from CO2, based on the measurements of Eiler et al. (2000). This new effect will be incorporated into our model. We note that the 16O/18O measurements in Table 2 have significantly larger error bars than for other species. With 13 additional work, it may be possible to improve the precision of the 16O/18O value on Titan and this can be used to test the validity of the snowball chemistry on Titan (C. Nixon, private communication, 2013). 3. PERCEIVED IMPACT With the completion of the first task, we will have a model with a 2D circulation that is driven by full physics GCMs. With the completion of the second task, we have incorporated all the major recent advances in the hydrocarbon and nitrile chemistry, from CH4 to organic aerosols. We will provide a physical reason for the spatial pattern and temporal variation of hydrocarbons and nitrile species on Titan. The model will predict a number of interesting results that will be directly testable by the Cassini observations in the extended mission phase (see Fig. 2 for the season Titan is in till the end of the mission in 2017). With the completion of the third task, we will have understood the mechanisms of isotopic fractionation in the atmosphere of Titan. With the completion of the fourth task, we will have a deeper understanding the evolutionary history of the atmosphere of Titan, especially during the extended period when it is in a collapsed snowball phase. Also, we will gain insight as to why the Copernican Principle discussed in the Introduction appears not to hold. Titan possesses a mildly reducing atmosphere in the outer Solar System. The central role of Titan in the origin of life is that it preserves the most complete information for prebiotic synthesis of organic compounds in our Solar System. It is obvious that the present Earth would not promote the origin of life. However, an early Earth, based on a theoretical reconstruction, is more conducive to the origin of life. Indeed, it bears remarkable resemblance to Titan. In an extended investigation after the completion of the principal tasks, we will pursue a parallel study of the atmospheres of Titan and early Earth. 4. RELEVANCE TO THE NASA PATM PROGRAM The proposed research is part of a much larger effort by this group. We are independently funded by NASA to carry out studies of the terrestrial atmosphere. The PI is also a participant in the Virtual Planetary Laboratory, a national Astrobiology Institute led by Professor Meadows at the University of Washington. These efforts are related to and complement the work proposed here for the reducing atmospheres in the outer Solar System. The PI is a co-investigator on the UVIS team of the Cassini Mission to Saturn and Titan. Our goal is to develop the best model for use in interpreting spacecraft measurements, thereby arriving at a fundamental understanding of the photochemical processes in the Solar System. Progress in the proposed work will contribute to answering deep questions on what controls the planetary environment and its evolution, how to best understand physical state through chemical signatures, and how to recognize unusual disequilibrium states of a planet. The knowledge gained from this research can provide a useful guide to NASA’s program to explore beyond our Solar System. This investigation will support specific elements of NASA’s objectives given in the ROSES 2013 Solicitation. It is particularly relevant to NASA's Planetary Atmospheres program because it defines “the determination of compositions, dynamics, energetics, and chemical behaviors of planetary atmospheres” and will “contribute to the understanding of the origins and evolution of the atmospheres of planets and their satellites”. 14 5. GENERAL PLAN OF WORK 5.1 Anticipated Key Milestones for Accomplishments This proposal covers the period FY14 – FY17. The schedule for carrying out the proposed tasks is as follows. Year 1: Start Task I on assembling the 2D model Year 2: Continue Task I and start Task II on photochemistry of the atmosphere; prepare results for publication Year 3: Start Task III on isotopic fractionation; prepare results for publication Year 4: Start Task IV on snowball Titan; prepare results for publication Year 5: Synthesis of modeling effort, detailed comparisons with Cassini observation; write long definitive paper 5.2 Management Structure for Proposal Personnel The proposed work will be carried out by Professor Yuk Yung, a Caltech graduate student and Dr. Mark Allen (co-investigator; JPL). Prof. Yung will commit at least 5% of his time (0.05 FTE) to this project. Also, Prof. Yung is a Chair Professor at Caltech, and most of his salary will be paid by the endowed chair. Dr. Allen will commit 12% of his time (0.12 FTE) to this project. 5.3 Proposed Substantial Collaboration with JPL Dr. Allen will contribute to the chemical kinetics and chemical model development used in the computations. He will participate in scientific discussions related to the research and help write up papers. 5.4 Description of Expected Contribution from PI and Graduate Student As principal investigator, Professor Yung will be responsible for coordinating all aspects of this research. The graduate student will help with modifying and running the Caltech/JPL KINETICS code. It is expected that the work will constitute part of the Ph.D. thesis for the student. 5.4 Description of Collaborators Collaborator Dr. Claire Newman of Ashima will provide the GCM outputs for the dynamics of Titan from the surface to about 500 km, from which we can compute the transport fields for driving the H-2D model in the stratosphere and mesosphere. Collaborator Dr. Ingo Müller-Wodarg of Imperial College London will provide the TGCM outputs for the dynamics of Titan above 500 km, from which we can compute the transport fields for driving the H-2D model in the thermosphere. Both collaborators will participate in the preparation of journal articles and presentation of results at professional meetings. 6. DATA-SHARING PLAN The results obtained in this research will be published in scientific journals and shared with the scientific community. In addition, we will provide key results as a guide to educate students in planetary science and to help the experimentalist to interpret new observations. This research does not generate new data for the PDS. 15