Imaging the Heliosphere using neutral Atoms from Solar Wind Energy down to 15 eV

We study the spatial and temporal distribution of hydrogen energetic neutral atoms (ENAs) from the heliosheath observed with the IBEX-Lo sensor of the Interstellar Boundary EXplorer (IBEX) from solar wind energies down to the lowest available energy (15 eV). All available IBEX-Lo data from 2009 January until 2013 June were included. The sky regions imaged when the spacecraft was outside of Earth's magnetosphere and when the Earth was moving toward the direction of observation offer a sufficient signal-to-noise ratio even at very low energies. We find that the ENA ribbon—a 20° wide region of high ENA intensities—is most prominent at solar wind energies whereas it fades at lower energies. The maximum emission in the ribbon is located near the poles for 2 keV and closer to the ecliptic plane for energies below 1 keV. This shift is an evidence that the ENA ribbon originates from the solar wind. Below 0.1 keV, the ribbon can no longer be identified against the globally distributed ENA signal. The ENA measurements in the downwind direction are affected by magnetospheric contamination below 0.5 keV, but a region of very low ENA intensities can be identified from 0.1 keV to 2 keV. The energy spectra of heliospheric ENAs follow a uniform power law down to 0.1 keV. Below this energy, they seem to become flatter, which is consistent with predictions. Due to the subtraction of local background, the ENA intensities measured with IBEX agree with the upper limit derived from Lyα observations.

Chandrayaan-1 observations of backscattered solar wind protons from the lunar regolith: Dependence on the solar wind speed

We study the backscattering of solar wind protons from the lunar regolith using the Solar Wind Monitor of the Sub-keV Atom Reflecting Analyzer on Chandrayaan-1. Our study focuses on the component of the backscattered particles that leaves the regolith with a positive charge. We find that the fraction of the incident solar wind protons that backscatter as protons, i.e., the proton-backscattering efficiency, has an exponential dependence on the solar wind speed that varies from ~0.01% to ~1% for solar wind speeds of 250 km/s to 550 km/s. We also study the speed distribution of the backscattered protons in the fast (~550 km/s) solar wind case and find both a peak speed at ~80% of the solar wind speed and a spread of ~85 km/s. The observed flux variations and speed distribution of the backscattered protons can be explained by a speed-dependent charge state of the backscattered particles.

Model for ranking freshwater fish farms according to their risk of infection and illustration for viral haemorrhagic septicaemia

We developed a model to calculate a quantitative risk score for individual aquaculture sites. The score indicates the risk of the site being infected with a specific fish pathogen (viral haemorrhagic septicaemia virus (VHSV); infectious haematopoietic necrosis virus, Koi herpes virus), and is intended to be used for risk ranking sites to support surveillance for demonstration of zone or member state freedom from these pathogens. The inputs to the model include a range of quantitative and qualitative estimates of risk factors organised into five risk themes (1) Live fish and egg movements; (2) Exposure via water; (3) On-site processing; (4) Short-distance mechanical transmission; (5) Distance-independent mechanical transmission. The calculated risk score for an individual aquaculture site is a value between zero and one and is intended to indicate the risk of a site relative to the risk of other sites (thereby allowing ranking). The model was applied to evaluate 76 rainbow trout farms in 3 countries (42 from England, 32 from Italy and 2 from Switzerland) with the aim to establish their risk of being infected with VHSV. Risk scores for farms in England and Italy showed great variation, clearly enabling ranking. Scores ranged from 0.002 to 0.254 (mean score 0.080) in England and 0.011 to 0.778 (mean of 0.130) for Italy, reflecting the diversity of infection status of farms in these countries. Requirements for broader application of the model are discussed. Cost efficient farm data collection is important to realise the benefits from a risk-based approach.