Dr Payel Das

We show how the interplay between feedback and mass-growth histories introduces scatter in the relationship between stellar and neutral gas properties of field faint dwarf galaxies (M-*less than or similar to 10(6) M-circle dot). Across a suite of cosmological, high-resolution zoomed simulations, we find that dwarf galaxies of stellar masses 10(5)

We present detailed implementations of (a) binary stellar evolution (using binary_c) and (b) dust production and destruction into the cosmological semi-analytic galaxy evolution simulation, L-Galaxies. This new version of L-Galaxies is compared to a version assuming only single stars and to global and spatially-resolved observational data across a range of redshifts ($z$). We find that binaries have a negligible impact on the stellar masses, gas masses, and star formation rates of galaxies only if the total mass ejected by massive stars is unchanged. This is because massive stars determine the strength of supernova (SN) feedback, which in turn regulates galaxy growth. Binary effects, such as common envelope ejection and novae, affect carbon and nitrogen enrichment in galaxies, however heavier alpha elements are more affected by the choice of SN and wind yields. Unlike many other simulations, the new L-Galaxies reproduces observed dust-to-metal (DTM) and dust-to-gas (DTG) ratios at $z\sim{}0-4$. This is mainly due to shorter dust accretion timescales in dust-rich environments. However, dust masses are under-predicted at $z>4$, highlighting the need for enhanced dust production at early times in simulations, possibly accompanied by increased star formation. On sub-galactic scales, there is very good agreement between L-Galaxies and observed dust and metal radial profiles at $z=0$. A drop in DTM ratio is also found in diffuse, low-metallicity regions, contradicting the assumption of a universal value. We hope that this work serves as a useful template for binary stellar evolution implementations in other cosmological simulations in future.

Low-mass dwarf galaxies are expected to showcase pristine `cuspy' inner dark matter density profiles compared to their stellar sizes, as they form too few stars to significantly drive dark matter heating through supernovae-driven outflows. Here, we study such simulated faint systems ($10^4 \leq M_{\star} \leq 2\times 10^6 \, M_\mathrm{\odot}$) drawn from high-resolution (3 pc) cosmological simulations from the `Engineering Dwarf Galaxies at the Edge of galaxy formation' (EDGE) project. We confirm that these objects have steep and rising inner dark matter density profiles at $z=0$, little affected by galaxy formation effects. But five dwarf galaxies from the suite showcase a detectable HI reservoir ($M_{\mathrm{HI}}\approx 10^{5}-10^{6} \, M_\mathrm{\odot}$), analogous to the observed population of faint, HI-bearing dwarf galaxies. These reservoirs exhibit episodes of ordered rotation, opening windows for rotation curve analysis. Within actively star-forming dwarfs, stellar feedback easily disrupts the tenuous HI discs ($v_{\phi} \approx 10\, \mathrm{km} \, \mathrm{s}^{-1}$), making rotation short-lived ($\ll 150 \, \mathrm{Myr}$) and more challenging to interpret for dark matter inferences. Contrastingly, we highlight a long-lived ($\geq 500 \, \mathrm{Myr}$) and easy-to-interpret HI rotation curve extending to $\approx 2\, r_{1/2, \text{3D}}$ in a quiescent dwarf, that has not formed new stars since $z=4$. This stable gas disc is supported by an oblate dark matter halo shape that drives high angular momentum gas flows. Our results strongly motivate further searches for HI rotation curves in the observed population of HI-bearing low-mass dwarfs, that provide a key regime to disentangle the respective roles of dark matter microphysics and galaxy formation effects in driving dark matter heating.

Improved housing has the potential to advance health and contribute to the Sustainable Development Goals. Research examining housing, health and energy use in low-income countries is limited; understanding these connections is vital to inform interventions for healthy sustainable human settlements. This paper investigates the low-income setting of Delhi, where rapid urbanisation, a varied climate, high pollution levels, and a wide variation in housing quality could result in significant energy use and health risks. Drawing on approaches from health and the built environment and existing data and literature, a characterisation of energy use and health risks for Delhi's housing stock is completed. Four broad settlement types were used to classify Delhi housing and energy use calculations and health risk assessment were performed for each variant. Energy use is estimated to be nearly two times higher per household among planned housing compared with other settlement types. Health risks, however, are found to be largest within informal slum settlements, with important contributions from heat and particulate matter across all settlements. This paper highlights intervention priorities and outlines the need for extensive further research, particularly through data gathering, to establish evidence to accelerate achieving healthy, sustainable and equitable housing in Delhi.

Abstract We present detailed implementations of (a) binary stellar evolution (using binary_c) and (b) dust production and destruction into the cosmological semi-analytic galaxy evolution simulation, L-Galaxies. This new version of L-Galaxies is compared to a version assuming only single stars and to global and spatially-resolved observational data across a range of redshifts (z). We find that binaries have a negligible impact on the stellar masses, gas masses, and star formation rates of galaxies if the total mass ejected by massive stars is unchanged. This is because massive stars determine the strength of supernova (SN) feedback, which in turn regulates galaxy growth. Binary effects, such as common envelope ejection and novae, affect carbon and nitrogen enrichment in galaxies, however heavier alpha elements are more affected by the choice of SN and wind yields. Unlike many other simulations, the new L-Galaxies reproduces observed dust-to-metal (DTM) and dust-to-gas (DTG) ratios at z ∼ 0 − 4. This is mainly due to shorter dust accretion timescales in dust-rich environments. However, dust masses are under-predicted at z ≳ 4, highlighting the need for enhanced dust production at early times in simulations, possibly accompanied by increased star formation. On sub-galactic scales, there is very good agreement between L-Galaxies and observed dust and metal radial profiles at z = 0. A drop in DTM ratio is also found in diffuse, low-metallicity regions, contradicting the assumption of a universal value. We hope that this work serves as a useful template for binary stellar evolution implementations in other cosmological simulations in future.

Aims. We study the kinematics and dynamics of the extreme outer halo of M 87, the central galaxy in the Virgo cluster, and its transition to the intracluster light (ICL). Methods. We present high resolution FLAMES/VLT spectroscopy of intracluster planetary nebula (PN) candidates, targeting three new fields in the Virgo cluster core with surface brightness down to $\mu_B$ = 28.5. Based on the projected phase space information (sky positions and line-of-sight velocities) we separate galaxy and cluster components in the confirmed PN sample. We then use the spherical Jeans equation and the total gravitational potential as traced by the X-ray emission to derive the orbital distribution in the outer stellar halo of M 87. We determine the luminosity-specific PN number for the M 87 halo and the ICL from the photometric PN catalogs and sampled luminosities, and discuss the origin of the ICL in Virgo based on its measured PN velocities. Results. We confirm a further 12 PNs in Virgo, five of which are bound to the halo of M 87, and the remainder are true intracluster planetary nebulas (ICPNs). The M 87 PNs are confined to the extended stellar envelope of M 87, within a projected radius of ~160 kpc, while the ICPNs are scattered across the whole surveyed region between M 87 and M 86, supporting a truncation of M 87's luminous outer halo at a 2σ level. The line-of-sight velocity distribution of the M 87 PNs at projected radii of 60 kpc and 144 kpc shows (i) no evidence for rotation of the halo along the photometric major axis; and (ii) that the velocity dispersion decreases in the outer halo, down to $\sigma_{\rm last}$ = 78±25 km s-1 at 144 kpc. The Jeans model for the M 87 halo stars fits the observed line-of-sight velocity dispersion profile only if the stellar orbits are strongly radially anisotropic (β $\simeq$ 0.4 at r $\simeq$ 10 kpc increasing to 0.8 at the outer edge), and if additionally the stellar halo is truncated at $\simeq$ 150 kpc average elliptical radius. The α-parameters for the M 87 halo and the ICL are in the range of values observed for old (>10 Gyr) stellar populations. Conclusions. Both the spatial segregation of the PNs at the systemic velocity of M 87 and the dynamical model support that the stellar halo of M 87 ends at ~150 kpc. We discuss several possible explanations for the origin of this truncation but are unable to discriminate between them: tidal truncation following an earlier encounter of M 87 with another mass concentration in the Virgo core, possibly around M 84, early AGN feedback effects, and adiabatic contraction due to the cluster dark matter collapsing onto M 87. From the spatial and velocity distribution of the ICPNs we infer that M 87 and M 86 are falling towards each other and that we may be observing them just before the first close pass. The new PN data support the view that the core of the Virgo cluster is not yet virialized but is in an ongoing state of assembly, and that massive elliptical galaxies are important contributors to the ICL in the Virgo cluster.

It is widely recognised that a major source of uncertainty in building performance simulation relates to occupancy and behavioural assumptions. This paper aims to assess the relative impact of lifestyle patterns, occupant-controlled window opening and shading use on indoor overheating risk levels in dwellings. The indoor thermal environment of a set of broadly representative archetypes of the London housing stock was simulated using dynamic thermal modelling. Two lifestyle patterns and four scenarios of window opening and shading use schedules were combined with multiple other varying parameters (building geometry and orientation, insulation levels, level of overshadowing by adjacent buildings), leading to a total of 27,648 modelled dwelling variants. It was found that the rankings obtained for dwellings occupied by a family with children at school and dwellings occupied by pensioners were broadly similar for all combinations of behaviour and the majority of overheating metrics. Lower ranking correlations were, however, observed between simple temperature-dependent window opening scenarios and a more sophisticated scenario of combined shading and night ventilation. This is an indication that shading and/or night cooling could modify indoor overheating risk significantly. The findings of the study add to a growing body of literature suggesting that the way inhabitants occupy and operate a building has a measurable impact on thermal discomfort and potentially the health risks associated with their exposure to high indoor temperatures. This should be taken into consideration in the design of retrofit interventions and public health strategies aiming to minimise such risks. •The relative influence of occupant behaviour for overheating risk in dwellings was examined.•A large notional housing stock was modelled under different occupancy and behaviour assumptions.•Similar overheating rankings were obtained for a family vs. an elderly couple occupancy scenario.•Rankings are markedly different to standard assumptions if windows remain constantly closed.•Daytime shading and night cooling can be significant modifiers of overheating risk.

A number of studies have estimated population exposure to PM2.5 by examining modeled or measured outdoor PM2.5 levels. However, few have taken into account the mediating effects of building characteristics on the ingress of PM2.5 from outdoor sources and its impact on population exposure in the indoor domestic environment. This study describes how building simulation can be used to determine the indoor concentration of outdoor-sourced pollution for different housing typologies and how the results can be mapped using building stock models and Geographical Information Systems software to demonstrate the modifying effect of dwellings on occupant exposure to PM2.5 across London. Building archetypes broadly representative of those in the Greater London Authority were simulated for pollution infiltration using EnergyPlus. In addition, the influence of occupant behavior on indoor levels of PM2.5 from outdoor sources was examined using a temperature-dependent window-opening scenario. Results demonstrate a range of I/O ratios of PM2.5, with detached and semi-detached dwellings most vulnerable to high levels of infiltration. When the results are mapped, central London shows lower I/O ratios of PM2.5 compared with outer London, an apparent inversion of exposure most likely caused by the prevalence of flats rather than detached or semi-detached properties.

The risk of overheating in UK dwellings is predicted to increase due to anthropogenic climate change and local urban climate modification leading to an increased urban heat island effect. Dwelling geometry characteristics such as orientation, aspect, and glazing, and building fabric characteristics such as thermal mass and resistance can influence the risk of overheating. The majority of simulation-based studies have focused on identifying the importance of building characteristics on overheating risk using a small number of weather files, or focus solely on the impact of external temperatures rather than a full set of climatic variables. This study examines the overheating risk in London dwelling archetypes when simulated under different UK climates, both in the present and under 'hot future' conditions, with the objective of identifying whether the conclusions drawn from location-specific studies can be generically applied to different cities. Simulations were carried out using the dynamic thermal simulation tool EnergyPlus using 3456 dwelling variants and six different Design Summer Year (DSY) climate files from locations within the UK. In addition, a 2050 Medium Emissions scenario weather file was used to model a particularly hot summer in all locations. The results indicate that weather files can influence the ranking of relative overheating risk between dwelling types, with significant variations in the relative ranking between London, Scotland and the North of England, and the rest of England. These results show that studies examining the overheating risk across the UK need to consider the variability of building performance under regional weather conditions. (C) 2014 Elsevier Ltd. All rights reserved.

We analyse six X-ray bright elliptical galaxies, observed with Chandra and XMM-Newton, and approximate their gravitational potentials by isothermal spheres phi = v2(c) log r over a range of radii from similar to 0.5 to similar to 25 kpc. We then compare the circular speed v(c) derived from X-ray data with the estimators available from optical data. In particular, we discuss two simple and robust procedures for evaluating the circular speed of the galaxy using the observed optical surface brightness and the line-of-sight velocity dispersion profiles. The best-fitting relation between the circular speeds derived from optical observations of stars and X-ray observations of hot gas is v(c,opt) similar or equal to eta v(c,X), where eta = 1.10-1.15 (depending on the method), suggesting, albeit with large statistical and systematic uncertainties, that non-thermal pressure on average contributes similar to 20-30 per cent of the gas thermal pressure.

It is important to limit dwelling infiltration to reduce energy demand and help meet national climate change commitments while concurrently providing sufficient ventilation to deliver adequate indoor air quality. DOMVENT3D is a model of infiltration and exfiltration that assumes a linear pressure distribution over any number of uniformly porous facades and integrates the airflow rate in the vertical plane to predict the theoretically correct airflow rate through them. DOMVENT3D is a new development of an existing two-dimensional model of infiltration that provides more opportunities for investigating a greater number of dwellings than was previously possible. Initial testing suggests that DOMVENT3D is mathematically robust and is suitable for modelling a wide variety of dwelling types and geometries to assist engineers and policy makers. Practical application: The modern building services engineer may be required to model airflow networks in a building to balance the conflicting needs of energy consumption reduction and occupant health. Limiting exfiltration is one method of reducing heat losses from a building and so there is a need to model it accurately. This article presents a new model of infiltration and exfiltration through a uniformly porous facade that can be incorporated within advanced complex airflow network tools or applied using a simple spreadsheet.

We present a new approach (MADE) that generates mass, age, and distance estimates of red giant stars from a combination of astrometric, photometric, and spectroscopic data. The core of the approach is a Bayesian artificial neural network (ANN) that learns from and completely replaces stellar isochrones. The ANN is trained using a sample of red giant stars with mass estimates from asteroseismology. A Bayesian isochrone pipeline uses the astrometric, photometric, spectroscopic, and asteroseismology data to determine posterior distributions for the training outputs: mass, age, and distance. Given new inputs, posterior predictive distributions for the outputs are computed, taking into account both input uncertainties, and uncertainties in the ANN parameters. We apply MADE to similar to 10 000 red giants in the overlap between the 14th data release from the APO Galactic Evolution Experiment (APOGEE) and the Tycho-Gaia astrometric solution (TEAS). The ANN is able to reduce the uncertainty on mass, age, and distance estimates for training-set stars with high output uncertainties allocated through the Bayesian isochrone pipeline. The fractional uncertainties on mass are < 10 per cent and on age are between 10 to 25 per cent. Moreover, the time taken for our ANN to predict masses, ages, and distances for the entire catalogue of APOGEE-TGAS stars is of a similar order of the time taken by the Bayesian isochrone pipeline to run on a handful of stars. Our resulting catalogue clearly demonstrates the expected thick- and thin-disc components in the [M/H]-[alpha /M] plane, when examined by age.

Strategies to reduce domestic heating loads by minimizing the infiltration of cold air through adventitious openings located in the thermal envelopes of houses are highlighted by the building codes of many countries. Consequent reductions of energy demand and CO2e emission are often unquantified by empirical evidence. Instead, a mean heating season infiltration rate is commonly inferred from an air leakage rate using a simple ratio scaled to account for the physical and environmental properties of a dwelling. The scaling does not take account of the permeability of party walls in conjoined dwellings and so cannot differentiate between the infiltration of unconditioned ambient air that requires heating, and conditioned air from adjacent dwellings that does not. A stochastic method is presented that applies a theoretical model of adventitious infiltration to predict distributions of mean infiltration rates and the associated total heat loss in any stock of dwellings during heating hours. The method is applied to the English and UK housing stocks and provides probability distribution functions of stock infiltration rates and total heat loss during the heating season for two extremes of party wall permeability. The distributions predict that up to 79% of the current English stock could require additional purpose-provided ventilation to limit negative health consequences. National models predict that fewer dwellings are under-ventilated. The distributions are also used to predict that infiltration is responsible for 3–5% of total UK energy demand, 11–15% of UK housing stock energy demand, and 10–14% of UK housing stock carbon emissions. •Heating season infiltration and heat loss distributions for English housing stock.•Up to 79% of English dwellings may be under ventilated.•Exfiltration estimated to be responsible for 3–5% of total UK energy demand.•Exfiltration estimated to be responsible for 11–15% UK housing stock energy demand.•Exfiltration estimated to be responsible for 10–14% UK housing stock CO2 emissions.

We develop a probabilistic framework for modelling indoor air quality in housing stocks, selecting appropriate sensitivity analyses to understand indoor air quality determinants, and constructing a reliable metamodel from the most relevant determinants to allow quick assessments of future intervention scenarios. The replicated Latin Hypercube sampling method is shown to be efficient at propagating variations between model input and output variables. A comparison of a range of sample-based sensitivity methods shows that an initial visual assessment can help to select appropriate sensitivity analyses, as they test for different types of relations (i.e. linear, monotonic, and non-monotonic). An advantage of linear regression methods is that the total output can be apportioned to various input variables. The advantage of tests with correlation coefficients is that the associated p-values can be used to assess whether input variables are significant. An artificial neural network constructed from a reduced set of input variables selected at a 5% level of significance is able to accurately predict indoor air quality. In the application of the framework to the modelling of winter indoor air quality in single-storey flats in England, the drivers for internally- and externally-generated PM2.5 are found to be different, therefore allowing interventions that reduce both concentrations simultaneously. Principal determinants for externally-generated PM2.5 are the internal deposition rate of PM2.5, weather-corrected volumetric infiltration rate, and ambient concentration of PM2.5, while for PM2.5 produced by gas cooking, they are the kitchen window opening area, generation rate of PM2.5, and indoor temperature. (C) 2014 Elsevier Ltd. All rights reserved.

As part of an effort to reduce carbon emissions in the UK, policies encouraging the energy-efficient retrofit of domestic properties are being implemented. Typical retrofits, including installation of insulation and double glazing can cause tightening of the building envelope which may affect indoor air quality (IAQ) impacting occupant health. Using the example of PM 2.5 (an airborne pollutant with known health impacts), this study considers the influence of energy-efficient retrofits on indoor PM 2.5 concentrations in domestic properties both above and below the low-income threshold (LIT) for a range of tenancies across England. Simulations using EnergyPlus and its integrated Generic Contaminant model are employed to predict indoor PM 2.5 exposures from both indoor and outdoor sources in building archetypes representative of (i) the existing housing stock and (ii) a retrofitted English housing stock. The exposures of occupants for buildings occupied by groups above and below the LIT are then estimated under current conditions and following retrofits. One-way ANOVA tests were applied to clarify results and investigate differences between the various income and tenure groups. Results indicate that all tenures below the LIT experience greater indoor PM 2.5 concentrations than those above, suggesting possible social inequalities driven by housing, leading to consequences for health.

Dwellings are a substantial source of global CO2 emissions. The energy used in homes for heating, cooking and running electrical appliances is responsible for a quarter of current total UK emissions and is a key target of government policies for greenhouse gas abatement. Policymakers need to understand the potential impact that such decarbonization policies have-on the indoor environment and health for a full assessment of costs and benefits. We investigated these impacts in two contrasting settings of the UK: London, a predominantly older city and Milton Keynes, a growing new town. We employed SCRIBE, a building physics-based health impact model of the UK housing stock linked to the English Housing Survey, to examine changes, 2010-2050, in end-use energy demand, CO2 emissions, winter indoor temperatures, airborne pollutant concentrations and associated health impacts. For each location we modelled the existing (2010) housing stock and three future scenarios with different levels of energy efficiency interventions combined with either a business-as-usual, or accelerated decarbonization of the electricity grid approach. The potential for CO2 savings was appreciably greater in London than Milton Keynes except when substantial decarbonization of the electricity grid was assumed, largely because of the lower level of current energy efficiency in London and differences in the type and form of the housing stock. The average net impact on health per thousand population was greater in magnitude under all scenarios in London compared to Milton Keynes and more beneficial when it was assumed that purpose-provided ventilation (PPV) would be part of energy efficiency interventions, but more detrimental when interventions were assumed not to include PPV. These findings illustrate the importance of considering ventilation measures for health protection and the potential variation in the impact of home energy efficiency strategies, suggesting the need for tailored policy approaches in different locations, rather than adopting a universally rolled out strategy. (C) 2015 Elsevier Ltd. All rights reserved.

Mathematical models can be used to evaluate the health impacts of housing energy efficiency interventions. However by their nature, models are subject to uncertainty and variability, which are important to quantify if used to support policy decisions. Models that are used to assess the impacts on health of housing energy efficiency interventions are likely to be based on a pair of linked component models: a building physics model which calculates changes in exposures and whose Outputs then feed into a health impact model. Current methods to propagate uncertainty in a series of models, where the outputs of one model are inputs to another, invariably use Monte Carlo (MC) numerical simulation. In this paper, two methods are used to quantify the uncertainty in the impact of draught proofing on childhood asthma: the MC simulation method and a semi-analytical method based on integral transforms. Both methods give close results but it is argued that the semi-analytical method has some advantages over the MC method, particularly in quantifying the uncertainties in the main outputs of the building physics model before propagating them to the health model. (C) 2015 Elsevier B.V. All rights reserved.

We present new Planetary Nebula Spectrograph observations of the ordinary elliptical galaxy NGC 4494, resulting in positions and velocities of 255 planetary nebulae out to seven effective radii (25 kpc). We also present new wide-field surface photometry from MMT/Megacam, and long-slit stellar kinematics from VLT/FORS2. The spatial and kinematical distributions of the planetary nebulae agree with the field stars in the region of overlap. The mean rotation is relatively low, with a possible kinematic axis twist outside 1R(e). The velocity dispersion profile declines with radius, though not very steeply, down to similar to 70 km s(-1) at the last data point. We have constructed spherical dynamical models of the system, including Jeans analyses with multi-component Lambda cold dark matter (CDM) motivated galaxies as well as logarithmic potentials. These models include special attention to orbital anisotropy, which we constrain using fourth-order velocity moments. Given several different sets of modelling methods and assumptions, we find consistent results for the mass profile within the radial range constrained by the data. Some dark matter (DM) is required by the data; our best-fitting solution has a radially anisotropic stellar halo, a plausible stellar mass-to-light ratio and a DM halo with an unexpectedly low central density. We find that this result does not substantially change with a flattened axisymmetric model. Taken together with other results for galaxy halo masses, we find suggestions for a puzzling pattern wherein most intermediate-luminosity galaxies have very low concentration haloes, while some high-mass ellipticals have very high concentrations.

As part of our current programme to test Lambda CDM predictions for dark matter (DM) haloes using extended kinematical observations of early-type galaxies, we present a dynamical analysis of the bright elliptical galaxy NGC4374 (M84) based on similar to 450 planetary nebulae (PNe) velocities from the PN. Spectrograph, along with extended long-slit stellar kinematics. This is the first such analysis of a galaxy from our survey with a radially constant velocity dispersion profile. We find that the spatial and kinematical distributions of the PNe agree with the field stars in the region of overlap. The velocity kurtosis is consistent with zero at almost all radii. We construct a series of Jeans models, fitting both velocity dispersion and kurtosis to help break the mass-anisotropy degeneracy. Our mass models include DM haloes either with shallow cores or with central cusps as predicted by cosmological simulations - along with the novel introduction in this context of adiabatic halo contraction from baryon infall. Both classes of models confirm a very massive dark halo around NGC 4374, demonstrating that PN kinematics data are well able to detect such haloes when present. Considering the default cosmological mass model, we confirm earlier suggestions that bright galaxies tend to have halo concentrations higher than Lambda CDM predictions, but this is found to be solved if either a Salpeter initial mass function (IMF) or an adiabatic contraction with a Kroupa IMF is assumed. Thus for the first time a case is found where the PN dynamics may well be consistent with a standard dark matter halo. A cored halo can also fit the data, and prefers a stellar mass consistent with a Salpeter IMF. The less dramatic dark matter content found in lower-luminosity 'ordinary' ellipticals suggests a bimodality in the halo properties which may be produced by divergent baryonic effects during their assembly histories.

We examine the dark matter properties of nearby early-type galaxies using planetary nebulae (PNe) as mass probes. We have designed a specialised instrument, the Planetary Nebula Spectrograph (PN.S) operating at the William Herschel telescope, with the purpose of measuring PN velocities with best efficiency. The primary scientific objective of this custom-built instrument is the study of the PN kinematics in 12 ordinary round galaxies. Preliminary results showing a dearth of dark matter in ordinary galaxies (Romanowsky et al. 2003) are now confirmed by the first complete PN.S datasets. On the other hand early-type galaxies with a "regular" dark matter content are starting to be observed among the brighter PN.S target sample, thus confirming a correlation between the global dark-to-luminous mass virial ratio (f_DM=M_DM/M_star) and the galaxy luminosity and mass.

Astronomy and Astrophysics, 2010, Volume 518, id.A44 Using a counter-dispersed slitless spectroscopy technique, we detect and measure the line-of-sight velocities of 187 planetary nebulae (PNe) around one of the nearest cD galaxies, NGC 1399, with FORS1 on the VLT. We describe the method for identifying and classifying the emission-line sources and the procedure for computing their J2000 coordinates and velocities. The number of PN detections and the errors in the velocity measurements (37 km/s indicate that this technique is comparable to other methods, such as that described by Teodorescu et al. (2005). We present the spatial distribution of the PNe and a basic analysis of their velocities. The PN two-dimensional velocity field shows marginal rotation consistent with other studies. We also find a low-velocity substructure in the halo and a flatter velocity-dispersion profile compared to previous observations that extends to ~400 arcsec. The detection of a low-velocity subcomponent underscores the importance of discrete velocity tracers for the detection of un-mixed components. The new velocity-dispersion profile is in good agreement with revised velocity dispersions for the red globular clusters in NGC 1399, using the data of Schuberth et al. (2009). The outer parts of this profile are consistent with one of the dynamical models of Kronawitter et al. (2000), which corresponds to a circular velocity of ~340 km/s and a rescaled B-band mass-to-light ratio of ~20 at 7' radius. These measurements trace the kinematics of the outer halo and disentangle the heterogenous populations in the Fornax Cluster core. The new data set the stage for a revised dynamical model of the outer halo of NGC 1399.

The distribution of Milky Way halo blue horizontal-branch (BHB) stars is examined using action-based extended distribution functions (EDFs) that describe the locations of stars in phase space, metallicity, and age. The parameters of the EDFs are fitted using stars observed in the Sloan Extension for Galactic Understanding and Exploration-II (SEGUE-II) survey that traces the phase-space kinematics and chemistry out to similar to 70 kpc. A maximum a posteriori probability (MAP) estimate method and a Markov Chain Monte Carlo method are applied, taking into account the selection function in positions, distance, and metallicity for the survey. The best-fitting EDF declines with actions less steeply at actions characteristic of the inner halo than at the larger actions characteristic of the outer halo, and older ages are found at smaller actions than at larger actions. In real space, the radial density profile steepens smoothly from -2 at similar to 2 kpc to -4 in the outer halo, with an axis ratio similar to 0.7 throughout. There is no indication for rotation in the BHBs, although this is highly uncertain. A moderate level of radial anisotropy is detected, with beta(s) varying from isotropic to between similar to 0.1 and similar to 0.3 in the outer halo depending on latitude. The BHB data are consistent with an age gradient of -0.03 Gyr kpc(-1), with some uncertainty in the distribution of the larger ages. These results are consistent with a scenario in which older, larger systems contribute to the inner halo, whilst the outer halo primarily comprises younger, smaller systems.

Lenticular galaxies display the prominent disks that are characteristic of late-type galaxies, but contain no gas, dust or star formation like early-type systems. So are they more closely related to spiral or ellipticals? One important clue to their origin is recorded in the kinematics. If they are simply quenched spiral galaxies then their stellar motions should be identical to those in spirals, whereas if their origins are closer to an elliptical, produced through merging, then this history should be reflected in more random stellar motions ([1]). We performed a maximum likelihood analysis in order to recover rotation velocity and random motions in the spheroidal and disk component of the galaxy NGC 1023. Its kinematics are consistent with the one of a stripped spiral, somehow complicated by an ongoing minor merger.

Computer simulation of real system behaviour is increasingly used in research and development. As simulation models become more reliable, they also often become more complex to capture the progressive complexity of the real system. Calculation time can be a limiting factor for using simulation models in optimisation studies, for example, which generally require multiple simulations. Instead of using these time-consuming simulation models, the use of metamodels can be considered. A metamodel approximates the original simulation model with high confidence via a simplified mathematical model. A series of simulations then only takes a fraction of the original simulation time, hence allowing significant computational savings. In this paper, a strategy that is both reliable and time-efficient is provided in order to guide users in their metamodelling problems. Furthermore, polynomial regression (PR), multivariate adaptive regression splines (MARS), kriging (KR), radial basis function networks (RBF), and neural networks (NN) are compared on a building energy simulation problem. We find that for the outputs of this example and based on Root Mean Squared Error (RMSE), coefficient of determination (R-2), and Maximal Absolute Error (MAE), KR and NN are the overall best techniques. Although MARS perform slightly worse than KR and NN, it is preferred because of its simplicity. For different applications, other techniques might be optimal. (C) 2014 Elsevier B. V. All rights reserved.

We fit an extended distribution function (EDF) to K giants in the Sloan Extension for Galactic Understanding and Exploration survey. These stars are detected to radii similar to 80 kpc and span a wide range in [Fe/H]. Our EDF, which depends on [Fe/H] in addition to actions, encodes the entanglement of metallicity with dynamics within the Galaxy's stellar halo. Our maximum-likelihood fit of the EDF to the data allows us to model the survey's selection function. The density profile of the K giants steepens with radius from a slope similar to a'2 to similar to a'4 at large radii. The halo's axis ratio increases with radius from 0.7 to almost unity. The metal-rich stars are more tightly confined in action space than the metal-poor stars and form a more flattened structure. A weak metallicity gradient similar to a'0.001 dex kpc(-1), a small gradient in the dispersion in [Fe/H] of similar to 0.001 dex kpc(-1), and a higher degree of radial anisotropy in metal-richer stars result. Lognormal components with peaks at similar to a'1.5 and similar to a'2.3 are required to capture the overall metallicity distribution, suggestive of the existence of two populations of K giants. The spherical anisotropy parameter varies between 0.3 in the inner halo to isotropic in the outer halo. If the Sagittarius stream is included, a very similar model is found but with a stronger degree of radial anisotropy throughout.

Objective To investigate the effect of reducing home ventilation as part of household energy efficiency measures on deaths from radon related lung cancer. Design Modelling study. Setting England. Intervention Home energy efficiency interventions, motivated in part by targets for reducing greenhouse gases, which entail reduction in uncontrolled ventilation in keeping with good practice guidance. Main outcome measures Modelled current and future distributions of indoor radon levels for the English housing stock and associated changes in life years due to lung cancer mortality, estimated using life tables. Results Increasing the air tightness of dwellings (without compensatory purpose-provided ventilation) increased mean indoor radon concentrations by an estimated 56.6%, from 21.2 becquerels per cubic metre (Bq/m(3)) to 33.2 Bq/m(3). After the lag in lung cancer onset, this would result in an additional annual burden of 4700 life years lost and (at peak) 278 deaths. The increases in radon levels for the millions of homes that would contribute most of the additional burden are below the threshold at which radon remediation measures are cost effective. Fitting extraction fans and trickle ventilators to restore ventilation will help offset the additional burden but only if the ventilation related energy efficiency gains are lost. Mechanical ventilation systems with heat recovery may lower radon levels and the risk of cancer while maintaining the advantage of energy efficiency for the most airtight dwellings but there is potential for a major adverse impact on health if such systems fail. Conclusion Unless specific remediation is used, reducing the ventilation of dwellings will improve energy efficiency only at the expense of population wide adverse impact on indoor exposure to radon and risk of lung cancer. The implications of this and other consequences of changes to ventilation need to be carefully evaluated to ensure that the desirable health and environmental benefits of home energy efficiency are not compromised by avoidable negative impacts on indoor air quality.

We create dynamical models of the massive elliptical galaxy, NGC 4649, using the N-body made-to-measure code, NMAGIC, and kinematic constraints from long-slit and planetary nebula (PN) data. We explore a range of potentials based on previous determinations from X-ray observations and a dynamical model fitting globular cluster (GC) velocities and a stellar density profile. The X-ray mass distributions are similar in the central region but have varying outer slopes, while the GC mass profile is higher in the central region and on the upper end of the range further out. Our models cannot differentiate between the potentials in the central region, and therefore if non-thermal pressures or multi-phase components are present in the hot gas, they must be smaller than previously inferred. In the halo, we find that the PN velocities are sensitive tracers of the mass, preferring a less massive halo than that derived from the GC mass profile, but similar to one of the mass distributions derived from X-rays. Our results show that the GCs may form a dynamically distinct system, and that the properties of the hot gas derived from X-rays in the outer halo have considerable uncertainties that need to be better understood. Estimating the mass in stars using photometric information and a stellar population mass-to-light ratio, we infer a dark matter mass fraction in NGC 4649 of similar to 0.39 at 1R(e) (10.5 kpc) and similar to 0.78 at 4R(e). We find that the stellar orbits are isotropic to mildly radial in the central similar to 6 kpc depending on the potential assumed. Further out, the orbital structure becomes slightly more radial along R and more isotropic along z, regardless of the potential assumed. In the equatorial plane, azimuthal velocity dispersions dominate over meridional velocity dispersions, implying that meridional velocity anisotropy is the mechanism for flattening the stellar system.

The optimal ventilation rate in a dwelling is a trade-off between the requirement to minimize ventilation heat losses to help meet national greenhouse gas emission targets and the need to minimize adverse health impacts arising from exposure to cold temperatures and pollutants from indoor and outdoor origin. This paper presents approaches for exploring these trade-offs based on two implementations of multi-objective optimization that consider both energy efficiency and health impacts. Both methods aggregate the various performance criteria into a single criterion, but the first method monetizes the performance criteria, while the second method weights them in a more general way. Unlike in the monetization approach, the generalized multi-objective optimization approach is found to be robust against scaling of the health impacts and energy savings that is independent of the ventilation rate. As a result it is less sensitive to assumptions made in the models regarding heating system efficiency, absolute health burden level, and dwelling occupancy. It is however sensitive to assumptions regarding pollutant production rates and balance-point temperatures, which affect health impacts and energy savings in a way correlated with ventilation rate. A preliminary application of the methods to a typical UK flat and detached house finds that the optimal ventilation rate may vary with built form. Application of the generalized multi-objective optimization approach in which health impacts and energy savings are equally weighted, suggests an optimal annual average air change rate of 0.4/h for the detached house, and 0.7/h for the flat. Crown Copyright (C) 2013 Published by Elsevier Ltd. All rights reserved.

We present first results of a study of the halo kinematics for a sample of early type galaxies using planetary nebulae (PNe) as kinematical tracers. PNe allow to extend up to several effective radii (R-e) the information from absorption line kinematics (confined to within 1 or 2R(e)), providing valuable information and constraints for merger simulations and galaxy formation models. We find that the specific angular momentum per unit mass has a more complex radial dependence when the halo region is taken into account and that the halo velocity dispersion is related to the total galaxy luminosity, isophotal shape, and number of PNe per unit of luminosity. (C) 2008 WILEY-VCH Verlag GmbH & Co. KGaA. Weinheim

Using a slitless spectroscopy method with (1) the 8.2 m Subaru telescope and its FOCAS Cassegrain spectrograph and (2) the ESO Very Large Telescope unit 1 (Antu) and its FORS2 Cassegrain spectrograph, we have detected 326 planetary nebulae (PNs) in the giant Virgo elliptical galaxy NGC 4649 (M 60) and measured their radial velocities. After rejecting some PNs more likely to belong to the companion galaxy NGC 4647, we have built a catalog with kinematic information for 298 PNs in M 60. Using these radial velocities, we have concluded that they support the presence of a dark matter halo around M 60. Based on an isotropic, two-component Hernquist model, we estimate the dark matter halo mass within 3R(e) to be 4 x 10(11) M-circle dot, which is almost one-half of the total mass of about 10(12) M-circle dot within 3R(e). This total mass is similar to that estimated from globular cluster, XMM-Newton, and Chandra observations. The dark matter becomes dominant outside. More detailed dynamical modeling of the PN data is being published in a companion paper. We have also measured the m(5007) magnitudes of many of these PNs and built a statistically complete sample of 218 PNs. The resulting PN luminosity function (PNLF) was used to estimate a distance modulus of 30.7 +/- 0.2 mag, equivalent to 14 +/- 1 Mpc. This confirms an earlier PNLF distance measurement based on a much smaller sample. The PNLF distance modulus remains smaller than the surface brightness fluctuation distance modulus by 0.4 mag.

Indoor temperature and air quality in dwellings are closely coupled. Differences between the indoor temperature and the temperature outside and in adjoining zones can influence airflow due to the stack effect, whilst changes in ventilation can cause changes in indoor pollution and temperature. This paper demonstrates the relationship between an indoor air pollutant, PM2.5, and temperature in UK domestic building archetypes using the dynamic thermal and contaminant modelling capabilities of EnergyPlus 8.0 under various UK Climate Projections 2009 (UKCP09) scenarios (current, current hot', 2050 High Emissions and 2050 High Emissions hot'), with both internal and external PM2.5 sources. Results indicate that flats have 0.7-0.8 times as much outdoor PM2.5 infiltrating indoors compared to detached dwellings, but 1.8-2.8 times more PM2.5 from indoor sources. During hot periods, temperature-dependent window opening increases exposure to outdoor PM2.5, meaning that as temperatures rises, dwelling occupants will become exposed to relatively higher levels of outdoor PM2.5 and lower levels of indoor PM2.5 due to the need to increase dwelling ventilation. The practical implications for government and designers and possible policy implications of this research are discussed.Practical applications: This paper demonstrates how an increase in summertime ventilation is necessary in UK homes to reduce overheating risks due to climate change and energy-efficient building retrofits. This, in turn, will lead to a change in the profile of indoor air pollution exposure, with greater exposure to pollution from outdoor sources and reduced exposure to pollution from indoor sources. Roof insulation and trickle vents reduce overheating risk, whilst increased use of mechanical ventilation heat recovery systems in the UK is encouraged, as it offers the co-benefits of cooling through increased ventilation, energy recovery and the potential to reduce indoor pollution levels.

We present a catalogue of distances, masses, and ages for similar to 3 million stars in the second Gaia data release with spectroscopic parameters available from the large spectroscopic surveys: APOGEE, Gaia-ESO, GALAH, LAMOST, RAVE, and SEGUE. We use a Bayesian framework to characterize the probability density functions of distance, mass, and age using photometric, spectroscopic, and astrometric information, supplemented with spectroscopic masses where available for giant stars. Furthermore, we provide posterior extinction estimates (AV) to every star using published extinction maps as a prior input. We provide an appendix with extinction coefficients for Gaia photometry derived from stellar models, which account for variation with intrinsic colour and total extinction. Our pipeline provides output estimates of the spectroscopic parameters, which can be used to inform improved spectroscopic analysis. We complement our catalogues with Galactocentric coordinates and actions with associated uncertainties. As a demonstration of the power of our catalogue, we produce velocity dispersion profiles of the disc separated by age and Galactocentric radius (between 3 and 15 kpc from the Galactic centre). This suggests that the velocity dispersion profiles flatten with radius in the outer Galaxy (> 8 kpc) and that at all radii the velocity dispersion follows the smooth power law with age observed in the solar neighbourhood.

To investigate the origins of S0 galaxies, we present a new method of analysing their stellar kinematics from discrete tracers such as planetary nebulae. This method involves binning the data in the radial direction so as to extract the most general possible non-parametric kinematic profiles, and using a maximum-likelihood fit within each bin in order to make full use of the information in the discrete kinematic tracers. Both disc and spheroid kinematic components are fitted, with a two-dimensional decomposition of imaging data used to attribute to each tracer a probability of membership in the separate components. Likelihood clipping also allows us to identify objects whose properties are not consistent with the adopted model, rendering the technique robust against contaminants and able to identify additional kinematic features. The method is first tested on an N-body simulated galaxy to assess possible sources of systematic error associated with the structural and kinematic decomposition, which are found to be small. It is then applied to the S0 system NGC 1023, for which a planetary nebula catalogue has already been released and analysed by Noordermer et al. The correct inclusion of the spheroidal component allows us to show that, contrary to previous claims, the stellar kinematics of this galaxy are indistinguishable from those of a normal spiral galaxy, indicating that it may have evolved directly from such a system via gas stripping or secular evolution. The method also successfully identifies a population of outliers whose kinematics are different from those of the main galaxy; these objects can be identified with a stellar stream associated with the companion galaxy NGC 1023A.

Paula Jofré and Payel Das categorize stars using the idea of the family tree. Paula Jofré and Payel Das discuss galactic evolution by applying the biological concept of the family tree to the stars in the Milky Way.

We use a new non-parametric Bayesian approach to obtain the most probable mass distributions and circular velocity curves along with their confidence ranges, given deprojected density and temperature profiles of the hot gas surrounding X-ray bright elliptical galaxies. For a sample of six X-ray bright ellipticals, we find that all circular velocity curves are rising in the outer parts due to a combination of a rising temperature profile and a logarithmic pressure gradient that increases in magnitude. Therefore at large radii, mass density profiles rise more steeply than isothermal profiles, implying that we are probing the more massive group-sized haloes in which these galaxies are embedded. Comparing the circular velocity curves we obtain from X-rays to those obtained from dynamical models, we find that the former are often lower in the central ∼10 kpc. This is probably due to a combination of (i) non-thermal contributions of up to ∼35 per cent in the pressure (with stronger effects in NGC 4486), (ii) multiple-temperature components in the hot gas, (iii) incomplete kinematic spatial coverage in the dynamical models and (iv) mass profiles that are insufficiently general in the dynamical modelling. Complementing the total mass information from the X-rays with photometry and stellar population models to infer the dark matter content, we find evidence for massive dark matter haloes with dark matter mass fractions of ∼35–80 per cent at 2Re, rising to a maximum of 80–90 per cent at the outermost radii. We also find that the six galaxies follow a Tully–Fisher relation with a slope of ∼4 and that their circular velocities at 1Re correlate strongly with the velocity dispersion of the local environment. As a result, the galaxy luminosity at 1Re also correlates with the velocity dispersion of the environment. These relations suggest a close link between the properties of central X-ray bright elliptical galaxies and their environments.

Indoor environmental quality has crucial links to occupant health and well-being. Delhi has experienced rapid population growth and, as a result, there has been a substantial escalation of informal housing that now accounts for up to half of the housing stock. In this work, we investigate the indoor environmental quality in a sample of low-income households in order to make recommendations for housing provision and to improve the health of occupants. The study takes a mixed-method approach to provide a wider understanding of the indoor environmental quality. Indoor temperature monitoring was carried out over a winter period, allowing a review of building performance. Focus groups with household residents allowed comparison between measured and perceived conditions and highlighted a number of housing issues, which is useful in guiding interventions. Indoor temperature ranges were found to vary significantly within and between dwellings, with the greatest range seen in dwellings constructed with temporary materials. All dwellings failed to provide comfortable temperatures above 21 degrees C for more than 40% of hours during the winter monitoring period, suggesting occupant discomfort and risk to health from exposure to cold temperatures. Occupants were found to have multiple adaptive strategies to overcome poorly performing dwellings. However, health is compromised by some approaches, such as the open use of firewood indoors. Thus, substantial work is necessary to improve indoor environmental quality. Interventions which replace roof materials and increasing window areas could potentially improve both actual and perceived conditions. (C) 2015 The Authors. Published by Elsevier Ltd.

We present new planetary nebulae (PNe) positions, radial velocities and magnitudes for six early-type galaxies obtained with the Planetary Nebulae Spectrograph (PNS), along with derived two-dimensional velocity and velocity dispersion fields, and the alpha parameters (i.e. the number of PNe per unit luminosity). We also present new deep absorption-line long-slit kinematics for three galaxies in the sample, obtained with the FOcal Reducer and low dispersion Spectrograph (FORS2) at the Very Large Telescope (VLT). We extend this study to include additional 10 early-type galaxies with PNe radial velocity measurements available from the literature, including previous PNS studies, in order to obtain a broader description of the outer-halo kinematics in early-type galaxies. These data extend the information derived from stellar absorption-line kinematics to typically several and up to 8 effective radii. The combination of photometry, absorption-line and PNe kinematics shows (i) a good agreement between the PNe number density distribution and the stellar surface brightness in the region where the two data sets overlap; (ii) a good agreement between PNe and absorption-line kinematics; (iii) that the mean rms velocity profiles fall into two groups, with part of the galaxies characterized by slowly decreasing profiles and the remainder having steeply falling profiles; (iv) a larger variety of velocity dispersion radial profiles; (v) that twists and misalignments in the velocity fields are more frequent at large radii, including some fast rotator galaxies; (vi) that outer haloes are characterized by more complex radial profiles of the specific angular momentum-related lambda(R) parameter than observed within 1 R-e; (vii) that many objects are more rotationally dominated at large radii than in their central parts and (viii) that the halo kinematics are correlated with other galaxy properties, such as total B band and X-ray luminosity, isophotal shape, total stellar mass, V/sigma and alpha parameter, with a clear separation between fast and slow rotators.

Studies have shown that the actual energy consumption of buildings once built and in operation is often far greater than the energy consumption predictions made during design-leading to the term "performance gap." An alternative to traditional, building physics based, prediction methods is an approach based on real-world data, where behavior is learned through observations. Display energy certificates are a source of observed building "behavior" in the United Kingdom, and machine learning, a subset of artificial intelligence, can predict global behavior in complex systems, such as buildings. In view of this, artificial neural networks, a machine learning technique, were trained to predict annual thermal (gas) and electrical energy use of building designs, based on a range of collected design and briefing parameters. As a demonstrative case, the research focused on school design in England. Mean absolute percentage errors of 22.9% and 22.5% for annual thermal and electrical energy use predictions, respectively, were achieved. This is an improvement of 9.1% for the prediction of annual thermal energy use and 24.5% for the prediction of annual electrical energy use when compared to sources evidencing the current performance gap.

Major energy efficiency refurbishment of the UK housing stock is needed to help attain emission reduction targets of greenhouse gases. Such measures typically entail some planned or incidental reduction of uncontrolled ventilation in dwellings. This paper examines the trade-offs for health and sustainability objectives of typical retrofit refurbishments in UK homes. While reducing ventilation can help protect against the ingress of harmful pollutants from the outdoor air, our results demonstrate that reducing permeability to low levels, without additional purpose-provided ventilation, is likely to lead to substantial increases in pollutants derived from indoor sources, including indoor-generated particles, radon and environmental tobacco smoke. The monetised equivalent cost of the health dis-benefits associated with these exposures may exceed the potential benefits of reducing energy costs and greenhouse gas emissions.Practical application: Reducing uncontrolled ventilation of dwellings helps to improve energy efficiency and can protect against the ingress of pollutants from the outdoor environment. However, simulation studies suggest that at high degrees of airtightness (very low permeability) there is a potentially steep rise in pollutants of indoor origin, whose adverse effects on health may outweigh the benefits of reduced energy use, lower CO2 emissions and protection against outdoor pollution. Though the optimal permeability level for a given dwelling will vary with local circumstances, considerations of health protection suggest the need to avoid reducing permeability to low levels.

Using 17 chemical elements as a proxy for stellar DNA, we present a full phylogenetic study of stars in the solar neighbourhood. This entails applying a clustering technique that is widely used in molecular biology to construct an evolutionary tree from which three branches emerge. These are interpreted as stellar populations that separate in age and kinematics and can be thus attributed to the thin disc, the thick disc and an intermediate population of probable distinct origin. We further find six lone stars of intermediate age that could not be assigned to any population with enough statistical significance. Combining the ages of the stars with their position on the tree, we are able to quantify the mean rate of chemical enrichment of each of the populations, and thus show in a purely empirical way that the star formation rate in the thick disc is much higher than that in the thin disc. We are also able to estimate the relative contribution of dynamical processes such as radial migration and disc heating to the distribution of chemical elements in the solar neighbourhood. Our method offers an alternative approach to chemical tagging methods with the advantage of visualizing the behaviour of chemical elements in evolutionary trees. This offers a new way to search for ' common ancestors' that can reveal the origin of solar neighbourhood stars.

We use density and temperature profiles obtained from XMM-Newton observations to derive a potential of NGC 5846 out to 11 R(e), thus probing the mass distribution deep into the halo. The inferred circular velocity is significantly higher than the extrapolation of dynamical models implying a halo, more massive than previously thought. Using an I-band surface-brightness profile and a projected velocity dispersion profile consisting of long-slit kinematic measurements and planetary nebulae (PNe) velocity dispersions, we solve the Jeans equations, assuming a non-rotating spherical system. The solutions suggest a highly radially anisotropic galaxy outside 0.7R(e) with beta similar to 0.75. (C) 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

There are a myriad of options when it comes to designing an uncertain optimization scheme. This work explores the impacts of several of these options using a case-study retrofitting of Swedish attics developed during the Annex 55 project of the International Energy Agency Energy Buildings and Community programme. We find that not considering maintenance costs, increments in energy costs with time, and discount rates in the economic criterion can impact the derived optimal design option. However, for our case study no difference was found between criteria that examined absolute returns, fractional returns, and annulized returns, despite emphasizing different aspects of the investment. If multiple moments of the economic criterion distribution are combined with weights to create a single objective function then several weights should be explored. Alternatively a single moment could be sought, such as the probability that the economic criterion is negative as a sufficient single objective, avoiding having to choose a weight. A hybrid genetic algorithm may offer a more efficient method of determining the optimal design option but a multi-layered sampling scheme offers more flexibility regarding subsequent analysis.

Objective: To assess potential public health impacts of changes to indoor air quality and temperature due to energy efficiency retrofits in English dwellings to meet 2030 carbon reduction targets. Design: Health impact modelling study. Setting: England. Participants: English household population. Intervention: Three retrofit scenarios were modelled: (1) fabric and ventilation retrofits installed assuming building regulations are met; (2) as with scenario (1) but with additional ventilation for homes at risk of poor ventilation; (3) as with scenario (1) but with no additional ventilation to illustrate the potential risk of weak regulations and non-compliance. Main outcome: Primary outcomes were changes in quality adjusted life years (QALYs) over 50 years from cardiorespiratory diseases, lung cancer, asthma and common mental disorders due to changes in indoor air pollutants, including secondhand tobacco smoke, PM2.5 from indoor and outdoor sources, radon, mould, and indoor winter temperatures. Results: The modelling study estimates showed that scenario (1) resulted in positive effects on net mortality and morbidity of 2241 (95% credible intervals (CI) 2085 to 2397) QALYs per 10 000 persons over 50 years follow-up due to improved temperatures and reduced exposure to indoor pollutants, despite an increase in exposure to outdoor-generated particulate matter with a diameter of (2.5) mu m or less (PM2.5). Scenario (2) resulted in a negative impact of -728 (95% CI -864 to -592) QALYs per 10 000 persons over 50 years due to an overall increase in indoor pollutant exposures. Scenario (3) resulted in -539 (95% CI -678 to -399) QALYs per 10 000 persons over 50 years follow-up due to an increase in indoor exposures despite the targeting of pollutants. Conclusions: If properly implemented alongside ventilation, energy efficiency retrofits in housing can improve health by reducing exposure to cold and air pollutants. Maximising the health benefits requires careful understanding of the balance of changes in pollutant exposures, highlighting the importance of ventilation to mitigate the risk of poor indoor air quality.

Housing has long been thought to play a significant role in population exposure to environmental hazards such as high temperatures and air pollution. However, there is sparse data describing how housing may modify heat and air pollution exposure such that housing's role in poor health and mortality from these hazards may be estimated. This paper describes the development of individual-address level indoor overheating and air pollution risk modifiers for Great Britain, for use alongside historical weather, outdoor air pollution, population socio-economic data, and mortality data in a large-scale epidemiological investigation. A geographically-referenced housing stock database was developed using the Homes Energy Efficiency Database (HEED) and the English Housing Survey (EHS). Simulations of unique combinations of building, fabric, occupation, and environment were run using a modelling framework developed for EnergyPlus 8.0, estimating indoor temperature metrics, indoor/outdoor ratio of pollution from outdoor sources, and indoor air pollution from multiple indoor sources. Results were compiled, matched back to individual properties in HEED, and mapped using Geographical Information Systems (GIS). Results indicate urban areas had higher numbers of buildings prone to overheating, reduced levels indoor air pollution from outdoor sources, and higher air pollution from indoor sources relative to rural areas, driven largely by variations in building types. The results provide the first national-scale quantitative estimate of heat and indoor air pollution modification by dwellings, aggregated at levels suitable for inclusion in health analysis. •A spatially-referenced building stock model was developed for housing in Britain.•EnergyPlus simulations estimated indoor overheating and air pollution risks.•Spatial variation of housing modification of risk was examined using GIS.•Housing stock variations led to greater overheating in urban areas.•Variation in housing stock and terrain caused higher I/O ratios in rural areas.

The recent introduction of the Generic Contaminant Model in EnergyPlus allows for the integrated modelling of multizone contaminant and dynamic thermal behaviour within a single simulation package. This article demonstrates how dynamic thermal simulation can modify pollutant transport within a building. PM2.5 infiltration from the external to internal environment under dynamic thermal conditions is compared in CONTAM, EnergyPlus 8.0, and Polluto, an in-house pollutant transport model developed in EnergyPlus 3.1. The influence of internal temperature on indoor PM2.5 levels is investigated by comparing results from standard CONTAM simulations and dynamic thermal EnergyPlus 8 simulations. Circumstances where the predictions of such models can diverge are identified. Practical application:This technical note compares the performance of a new indoor air quality model in EnergyPlus, an EnergyPlus in-house model (Polluto), and an established model (CONTAM). The work then compares the results of indoor air quality models under static and dynamic internal temperature conditions, and demonstrates how predicted indoor pollution levels may deviate significantly if an inappropriate indoor temperature is used. Practically, the work provides confidence in the new models, as well as demonstrating the importance of having a good understanding of the thermal behaviour of a building when modelling indoor air quality.

High temperatures, an extremely polluted ambient environment, alongside disparities in housing quality and household energy use, indicate overheating risk and poor indoor air quality in Delhi dwellings. In this study, we explore a range of interventions to reduce adverse temperature exposure and improve indoor air quality, focusing on PM2.5, for exemplar base case households developed to cover the range of settlements types found in Delhi. Interventions are modelled using dynamic thermal simulation, and include a range of modifications to dwelling operation and building fabric, as well as additional building components. A weighted multi-objective assessment considering annual energy use, intervention cost, and a health metric encompassing heat, cold and PM2.5 exposure, is employed to score the suitability of strategies for each settlement type. The most effective strategy is found to be a combination of changes in building fabric with evaporative cooling and cooking ventilation in all archetypes. The results demonstrate how a weighted multi-objective assessment is effective in selecting strategies for settlement types with differing priorities.Practical application: Current dwellings in Delhi risk significant energy consumption or provide inadequate indoor environmental quality. This work presents the performance of potential interventions, by considering multiple criteria, which could be deployed in Delhi households to provide low-energy healthy homes.

Since chemical abundances are inherited between generations of stars, we use them to trace the evolutionary history of our Galaxy. We present a robust methodology for creating a phylogenetic tree, a biological tool used for centuries to study heritability. Combining our phylogeny with information on stellar ages and dynamical properties, we reconstruct the shared history of 78 stars in the Solar Neighbourhood. The branching pattern in our tree supports a scenario in which the thick disk is an ancestral population of the thin disk. The transition from thick to thin disk shows an anomaly, which we attribute to a star formation burst. Our tree shows a further signature of the variability in stars similar to the Sun, perhaps linked to a minor star formation enhancement creating our Solar System. In this paper, we demonstrate the immense potential of a phylogenetic perspective and interdisciplinary collaboration, where with borrowed techniques from biology we can study key processes that have contributed to the evolution of the Milky Way.

We exploit the [Mg/Mn]-[Al/Fe] chemical abundance plane to help identify nearby halo stars in the 14th data release from the APOGEE survey that have been accreted on to the Milky Way. Applying a Gaussian Mixture Model, we find a ‘blob’ of 856 likely accreted stars, with a low disc contamination rate of ∼7 per cent. Cross-matching the sample with the second data release from Gaia gives us access to parallaxes and apparent magnitudes, which place constraints on distances and intrinsic luminosities. Using a Bayesian isochrone pipeline, this enables us to estimate new ages for the accreted stars, with typical uncertainties of ∼20 per cent. This does not account for systematic uncertainties. Our new catalogue is further supplemented with estimates of orbital parameters. The blob stars span [Fe/H] between −2.5 to −0.5, and [Mg/Fe] between −0.1 to 0.5. They constitute ∼30 per cent of the metal-poor ([Fe/H] < −0.8) halo at [Fe/H] ∼ −1.4. Our new ages mainly range between 8 to 13 Gyr, with the oldest stars the metal-poorest, and with the highest [Mg/Fe] abundance. If the blob stars are assumed to belong to a single progenitor, the ages imply that star formation lasted 5 Gyr after which the system merged with our Milky Way around 8 Gyr ago. Dynamical arguments suggest that such a single progenitor would have had a total mass of $\sim 10^{11}\, \mathrm{M}_{\odot }$, similar to that found by other authors using chemical evolution models and simulations.

We apply four different mass modelling methods to a suite of publicly available mock data for spherical stellar systems. We focus on the recovery of the density and velocity anisotropy as a function of radius, either using line-of-sight velocity data only or adding proper motion data. All methods perform well on isotropic and tangentially anisotropic mock data, recovering the density and velocity anisotropy within their 95 per cent confidence intervals over the radial range 0.25 < R/R1/2 < 4, where R1/2 is the half-light radius. However, radially anisotropic mocks are more challenging. For line-of-sight data alone, only methods that use information about the shape of the velocity distribution function are able to break the degeneracy between the density profile and the velocity anisotropy, β, to obtain an unbiased estimate of both. This shape information can be obtained through directly fitting a global phase-space distribution function, by using higher order ‘virial shape parameters’ or by assuming a Gaussian velocity distribution function locally, but projecting it self-consistently along the line of sight. Including proper motion data yields further improvements, and in this case, all methods give a good recovery of both the radial density and velocity anisotropy profiles.

Selection functions are vital for understanding the observational biases of spectroscopic surveys. With the wide variety of multiobject spectrographs currently in operation and becoming available soon, we require easily generalizable methods for determining the selection functions of these surveys. Previous work, however, has largely been focused on generating individual, tailored selection functions for every data release of each survey. Moreover, no methods for combining these selection functions to be used for joint catalogues have been developed. We have developed a Poisson likelihood estimation method for calculating selection functions in a Bayesian framework, which can be generalized to any multiobject spectrograph. We include a robust treatment of overlapping fields within a survey as well as selection functions for combined samples with overlapping footprints. We also provide a method for transforming the selection function that depends on the sky positions, colour, and apparent magnitude of a star to one that depends on the galactic location, metallicity, mass, and age of a star. This ‘intrinsic’ selection function is invaluable for chemodynamical models of the Milky Way. We demonstrate that our method is successful at recreating synthetic spectroscopic samples selected from a mock galaxy catalogue.