The interplanetary magnetic field environment at Mercury's orbit

Mercury is exposed to the most dynamic heliospheric space environment of any planet in the solar system. The magnetosphere is particularly sensitive to variations in the interplanetary magnetic field (IMF), which control the intensity and geometry of the magnetospheric current systems that are the dominant source of uncertainty in determinations of the internal planetary magnetic field structure. The Magnetometer on the MErcury Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) spacecraft has made extensive magnetic field observations in the inner heliosphere over the heliocentric distances of Mercury's orbit, between 0.31 and 0.47 AU. In this paper, Magnetometer data from MESSENGER, obtained at rates of 2 and 20 vector samples per second, are used together with previous observations in the inner heliosphere by Helios and at Earth by the Advanced Composition Explorer, to study the characteristics of IMF variability at Mercury's orbit. Although the average IMF geometry and magnitude depend on heliocentric distance as predicted by Parker, the variability is large, comparable to the total field magnitude. Using models for the external current systems we evaluate the impact of the variability on the field near the planet and find that the large IMF fluctuations should produce variations of the magnetospheric field of up to 30% of the dipole field at 200 km altitude, corresponding to the planned periapsis of MESSENGER's orbit at Mercury. The IMF fluctuations in the frequency range are consistent with turbulence, whereas evidence for dissipation was observed for . The transition between the turbulent and dissipative regimes is indicated by a break in the power spectrum, and the frequency of this break point is proportional to the IMF magnitude.     

Observations of suprathermal electrons in Mercury's magnetosphere during the three MESSENGER flybys

In 2008 the MESSENGER spacecraft made the first direct observation of Mercury's magnetosphere in the more than 30 years since the Mariner 10 encounters. During MESSENGER's first flyby on 14 January 2008, the interplanetary magnetic field (IMF) was northward immediately prior to and following MESSENGER's equatorial passage through this small magnetosphere. The Energetic Particle Spectrometer (EPS), one of two sensors on the Energetic Particle and Plasma Spectrometer instrument that responds to electrons from ∼35 keV to 1 MeV and ions from ∼35 keV to 2.75 MeV, saw no increases in particle intensity above instrumental background (∼5 particles/cm²/sr/s/keV at 45 keV) at any time during the probe's magnetospheric passage. During MESSENGER's second flyby on 6 October 2008, there was a steady southward IMF, and intense reconnection was observed between the planet's magnetic field and the IMF. However, once again EPS did not observe bursts of energetic particles similar to those reported by Mariner 10 from its March 1974 encounter. On 29 September 2009, MESSENGER flew by Mercury for the third and final time before orbit insertion in March 2011. Although a spacecraft safe-hold event stopped science measurements prior to the outbound portion of the flyby, all instruments recorded full observations until a few minutes before the closest approach. In particular, the MESSENGER Magnetometer documented several substorm-like signatures of extreme loading of Mercury's magnetotail, but again EPS measured no energetic ions or electrons above instrument background during the inbound portion of the flyby. MESSENGER's X-Ray Spectrometer (XRS) nonetheless observed photons resulting from low-energy (∼10 keV) electrons impinging on its detectors during each of the three flybys. We infer that suprathermal plasma electrons below the EPS energy threshold caused the bremsstrahlung seen by XRS. In this paper, we summarize the energetic particle observations made by EPS and XRS during MESSENGER's three Mercury flybys, and we revisit the observations reported by Mariner 10 in the context of these new results.     

A Barometric Survey of Dust-Devil Vortices on a Desert Playa

Dust devils, and other columnar vortices, are associated with local surface pressure drops that can be observed in time-series data on both Earth and Mars. High cadence measurements are needed to resolve these small structures, and we report a month-long survey (June/July 2012) on a Nevada desert playa using microbarographs sampled multiple times per second. Candidate dust-devil signatures are classified, with detections being robust at about one per day for pressure drops exceeding 0.3 hPa (roughly a 5:1 signal-to-noise threshold, where the observed noise level corresponds reasonably well with the dynamic pressure associated with the estimate convective velocity scale). The vortex population is evaluated and compared with those observed on Mars: a broken power law or a more convex distribution describes the terrestrial data. A single station observes about three events per week (for normalized pressure drops of 0.06 %), about three times fewer than Mars observations for the same normalized drop. We find evidence for clustering of vortex events in a pseudo-periodic manner with a 20-min period, consistent with the size of boundary-layer convection cells.     

Optimizing the Environmental Performance of In Situ Thermal Remediation Technologies Using Life Cycle Assessment

In situ thermal remediation technologies provide efficient and reliable cleanup of contaminated soil and groundwater, but at a high cost of environmental impacts and resource depletion due to the large amounts of energy and materials consumed. This study provides a detailed investigation of four in situ thermal remediation technologies (steam enhanced extraction, thermal conduction heating, electrical resistance heating, and radio frequency heating) in order to (1) compare the life‐cycle environmental impacts and resource consumption associated with each thermal technology, and (2) identify options to reduce these adverse effects. The study identifies a number of options for environmental optimization of in situ thermal remediation. In general, environmental optimization can be achieved by increasing the percentage of heating supplied in off peak electricity demand periods as this reduces the pressure on coal‐based electricity and thereby reduces the environmental impacts due to electricity production by up to 10%. Furthermore, reducing the amount of concrete in the vapor cap by using a concrete sandwich construction can potentially reduce the environmental impacts due to the vapor cap by up to 75%. Moreover, a number of technology‐specific improvements were identified, for instance by the substitution of stainless steel types in wells, heaters, and liners used in thermal conduction heating, thus reducing the nickel consumption by 45%. The combined effect of introducing all the suggested improvements is a 10 to 21% decrease in environmental impacts and an 8 to 20% decrease in resource depletion depending on the thermal remediation technology considered. The energy consumption was found to be the main contributor to most types of environmental impacts; this will, however, depend on the electricity production mix in the studied region. The combined improvement potential is therefore to a large extent controlled by the reduction/improvement of energy consumption.     

The growth of wind-waves in Titan’s hydrocarbon seas

Ocean wave growth on Titan is considered. The classic Sverdrup–Munk theory for terrestrial wave growth is applied to Titan, and is compared with a simple energy balance model that exposes the effect of Titan’s environmental parameters (air density, gravity, and fluid density). These approaches are compared with the only previously-published (semi-empirical) model (Ghafoor, N.A.-L., Zarnecki, J.C., Challenor, P., Srokosz, M.A. [2000] J. Geophys. Res. 105, 12,077–12,091, hereafter G2k), and allow the impact of various parameters such as atmospheric density to be transparently explored.Our model, like G2k, suggests fully-developed significant wave heights on Titan H_s = 0.2 U², where U is the windspeed (SI units): in dimensionless terms this is rather close to H_s = 0.2 U²/g, a rule of thumb previously noted for terrestrial waves (we find various datasets where the prefactor varies by ～2). It is noted that liquid and air densities affect the growth rate of waves, but not their fully-developed height: for 1 m/s winds wave amplitude reaches 0.15 m (75% of fully-developed) with a fetch of only 1 km, rather faster than predicted by G2k. Liquid viscosity has no major effect on gravity wave growth, but does influence the threshold windspeed at which gravity–capillary waves form in the first place.The model is used to develop predicted ranges for wave height to guide the design of the Titan Mare Explorer (TiME), a proposed Discovery-class mission to float a capsule on Ligeia Mare in 2023. For the expected maximum 1 m/s winds, a significant wave height of 0.2 m and wavelength of ～4 m can be expected. Assuming that wave heights follow Rayleigh statistics as they do on Earth, then given the wave period of ～4 s, individual waves of ～0.6 m might be encountered over a 3 month period.For predicted Titan winds at Kraken Mare, significant wave heights may reach ～0.6 m in the peak of summer but do not exceed the tidal amplitude at its northern end, consistent with the area around Mayda Insula being a tidal flat, while elsewhere on Kraken and Ligeia and at Ontario Lacus, shorelines may be wave- or tidally-dominated, depending on the specific location.     

In situ impact of petrochemicals on the photosynthesis of the seagrass Zostera capricorni

We used photosynthetic activity (measured as chlorophyll a fluorescence) and photosynthetic pigment concentrations to assess the effect of pulsed exposures of aged crude oil (Champion Crude), dispersant (VDC) and an oil+dispersant mixture on the seagrass Zostera capricorni Aschers in laboratory and field experiments, using custom-made chambers. Samples were exposed for 10 h to 0.25% and 0.1% concentrations of aged crude oil and dispersant as well as mixtures of 0.25% oil+0.05% dispersant and 0.1% oil+0.02% dispersant. During this time and for the subsequent four day recovery period, the maximum and effective quantum yields of photosystem II (Fv/Fm and DeltaF/Fm' respectively) were measured. In the laboratory experiments, both values declined in response to oil exposure and remained low during the recovery period. Dispersant exposure caused a decline in both values during the recovery period, while the mixture of aged crude oil+dispersant had little impact on both quantum yields. In situ samples were less sensitive than laboratory samples, showing no photosynthetic impact due to dispersant and oil+dispersant mixture. Despite an initial decline in DeltaF/Fm', in situ oil-exposed samples recovered by the end of the experiment. Chlorophyll pigment analysis showed only limited ongoing impact in both laboratory and field situations. This study suggests that laboratory experiments may overestimate the ongoing impact of petrochemicals on seagrass whilst the dispersant VDC can reduce the impact of oil on seagrass photosynthesis.     

Support vector machines (SVMs) for monitoring network design

In this paper we present a hydrologic application of a new statistical learning methodology called support vector machines (SVMs). SVMs are based on minimization of a bound on the generalized error (risk) model, rather than just the mean square error over a training set. Due to Mercer's conditions on the kernels, the corresponding optimization problems are convex and hence have no local minima. In this paper, SVMs are illustratively used to reproduce the behavior of Monte Carlo-based flow and transport models that are in turn used in the design of a ground water contamination detection monitoring system. The traditional approach, which is based on solving transient transport equations for each new configuration of a conductivity field, is too time consuming in practical applications. Thus, there is a need to capture the behavior of the transport phenomenon in random media in a relatively simple manner. The objective of the exercise is to maximize the probability of detecting contaminants that exceed some regulatory standard before they reach a compliance boundary, while minimizing cost (i.e., number of monitoring wells). Application of the method at a generic site showed a rather promising performance, which leads us to believe that SVMs could be successfully employed in other areas of hydrology. The SVM was trained using 510 monitoring configuration samples generated from 200 Monte Carlo flow and transport realizations. The best configurations of well networks selected by the SVM were identical with the ones obtained from the physical model, but the reliabilities provided by the respective networks differ slightly.