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To learn more about the properties of the Vela Supercluster (VSCL), located behind the Milky Way at cz ∼ 18,000 km s ^−1 , we determine the K _s -band luminosity function (LF) of VC04, the richest known galaxy cluster in the VSCL, and two other VSCL clusters (VC02 and VC08). The galaxy sample is based on NIR observations that are complete to an extinction-corrected absolute magnitude of ${M}_{{Ks}}^{o}\lt -21\buildrel{\rm{m}}\over{.} 5$ (∼2.ͫ5 below ${M}_{K}^{* }$ ), within the clustercentric radius of r _c < 1.5 Mpc (∼70% of the Abell radius). For VC04, we obtained 90 new spectroscopic redshifts of galaxies, observed with the 11 m Southern African Large Telescope. We found the Schechter parameters of the VC04 LF to be M * = −24.ͫ41 ± 0.44, α = −1.10 ± 0.20, and ϕ * = 8.84 ± 0.20. Both the redshift data and the LF confirm VC04 to be a rich but not yet fully relaxed cluster. We independently determined the LF of VC04 on membership defined by the red-sequence method and demonstrated that this method can be used in the absence of high spectroscopic coverage over a cluster. This allowed us to determine the LFs of VC02 and VC08. We also derived the LFs of the Coma, Norma, and Virgo clusters to similar depth and extent as the VSCL clusters. We found that the Schechter parameters of VC04 are within 1 σ uncertainties of these local clusters, as well as VC02 and VC08. We do not find significant differences between the LFs in the different cluster environments probed in this work down to ${M}_{K}^{* }+2\buildrel{\rm{m}}\over{.} 5$ .

We describe the motivation, design, and execution of the Greenhouse gAs Uk and Global Emissions (GAUGE) project. The overarching scientific objective of GAUGE was to use atmospheric data to estimate the magnitude, distribution, and uncertainty of the UK greenhouse gas (GHG, defined here as CO2, CH4, and N2O) budget, 2013–2015. To address this objective, we established a multi-year and interlinked measurement and data analysis programme, building on an established tall-tower GHG measurement network. The calibrated measurement network comprises ground-based, airborne, ship-borne, balloon-borne, and space-borne GHG sensors. Our choice of measurement technologies and measurement locations reflects the heterogeneity of UK GHG sources, which range from small point sources such as landfills to large, diffuse sources such as agriculture. Atmospheric mole fraction data collected at the tall towers and on the ships provide information on sub-continental fluxes, representing the backbone to the GAUGE network. Additional spatial and temporal details of GHG fluxes over East Anglia were inferred from data collected by a regional network. Data collected during aircraft flights were used to study the transport of GHGs on local and regional scales. We purposely integrated new sensor and platform technologies into the GAUGE network, allowing us to lay the foundations of a strengthened UK capability to verify national GHG emissions beyond the project lifetime. For example, current satellites provide sparse and seasonally uneven sampling over the UK mainly because of its geographical size and cloud cover. This situation will improve with new and future satellite instruments, e.g. measurements of CH4 from the TROPOspheric Monitoring Instrument (TROPOMI) aboard Sentinel-5P. We use global, nested, and regional atmospheric transport models and inverse methods to infer geographically resolved CO2 and CH4 fluxes. This multi-model approach allows us to study model spread in a posteriori flux estimates. These models are used to determine the relative importance of different measurements to infer the UK GHG budget. Attributing observed GHG variations to specific sources is a major challenge. Within a UK-wide spatial context we used two approaches: (1) Δ14CO2 and other relevant isotopologues (e.g. δ13CCH4) from collected air samples to quantify the contribution from fossil fuel combustion and other sources, and (2) geographical separation of individual sources, e.g. agriculture, using a high-density measurement network. Neither of these represents a definitive approach, but they will provide invaluable information about GHG source attribution when they are adopted as part of a more comprehensive, long-term national GHG measurement programme. We also conducted a number of case studies, including an instrumented landfill experiment that provided a test bed for new technologies and flux estimation methods. We anticipate that results from the GAUGE project will help inform other countries on how to use atmospheric data to quantify their nationally determined contributions to the Paris Agreement.

High methane (CH4) mixing ratios (up to 4 ppm) have occurred sporadically at our measurement site in Haddenham, Cambridgeshire, since July 2012. Isotopic measurements and back trajectories show that the source is the Waterbeach Waste Management Park 7 km SE of Haddenham. To investigate this further, measurements were made on 30 June and 1 July 2015 at other locations nearer to the source. Landfill emissions have been estimated using three different approaches at different scales; near source using the WindTrax inversion dispersion model, middle distance using a Gaussian plume (GP) model and at the landscape scale using the Numerical Atmospheric Modelling Environment (NAME) Inversion Technique for Emission Modelling (InTEM) inversion. The emission estimates derived using the WindTrax and Gaussian plume (GP) approaches agree well for the period of intense observations. Applying the Gaussian plume approach to all periods of elevated measurements seen at Haddenham produces year-round and monthly landfill emission estimates with an estimated annual emission of 11.6 Gg CH4 yr−1. The monthly emission estimates are highest in winter (2160 kg h−1 in February) and lowest in summer (620 kg h−1 in July). These data identify the effects of environmental conditions on landfill CH4 production and highlight the importance of year-round measurements to capture seasonal variability in CH4 emission.

We present Hubble WFC3/IR slitless grism spectra of a remarkably bright z ≳ 10 galaxy candidate, GN-z11, identified initially from CANDELS/GOODS-N imaging data. A significant spectroscopic continuum break is detected at . The new grism data, combined with the photometric data, rule out all plausible lower redshift solutions for this source. The only viable solution is that this continuum break is the Lyα break redshifted to , just ∼400 Myr after the Big Bang. This observation extends the current spectroscopic frontier by 150 Myr to well before the Planck (instantaneous) cosmic reionization peak at z ∼ 8.8, demonstrating that galaxy build-up was well underway early in the reionization epoch at z > 10. GN-z11 is remarkably, and unexpectedly, luminous for a galaxy at such an early time: its UV luminosity is 3× larger than measured at z ∼ 6−8. The Spitzer IRAC detections up to 4.5 μm of this galaxy are consistent with a stellar mass of ∼109M⊙. This spectroscopic redshift measurement suggests that James Webb Space Telescope (JWST) will be able to similarly and easily confirm such sources at z > 10 and characterize their physical properties through detailed spectroscopy. Furthermore, WFIRST, with its wide-field near-IR imaging, would find large numbers of similar galaxies and contribute greatly to JWST's spectroscopy, if it is launched early enough to overlap with JWST. [ABSTRACT FROM AUTHOR]

We investigate the use of tensegrity structures with morphing and prestress-stability capabilities for the design of active solar façades of smart buildings. Morphing tensegrity lattices are used to design shading screens composed of umbrella-shaped ‘eyes’ that are opened and closed by adjusting the elongation in a limited number of cables. Prestressable lattices are instead employed to design superstable Venetian blinds that are composed of orientable slats. Future use of tensegrity solutions for next-generation smart buildings are outlined, with the aim of designing kinetic solar façades that combine morphing abilities with prestress-stability. [ABSTRACT FROM AUTHOR]