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The Mega-MUSCLES Treasury Survey: X-Ray to Infrared Spectral Energy Distributions of a Representative Sample of M Dwarfs
We present 5–1 × 107 Å spectral energy distributions (SEDs) for 12 M dwarf stars covering spectral types M0–M8. Our SEDs are provided for community use as a sequel to the Measurements of the Ultraviolet Spectral Characteristics of Low-mass Exoplanetary Systems (MUSCLES) survey. The 12 stars include eight known exoplanet hosts and four stars chosen to fill out key parameter space in spectral type and rotation period. The SEDs are constructed from Hubble Space Telescope ultraviolet spectroscopy and XMM Newton, Chandra, and/or Swift X-ray observations, and completed with various model data, including Lyα reconstructions, PHOENIX optical models, APEC coronal models, and differential emission measure models in the currently-unobservable extreme ultraviolet. We provide a complete overview of the Mega-MUSCLES program, including a description of the observations, models, and SED construction. The SEDs are available as MAST high-level science products and we describe the various data products here. We also present ensemble measurements from our sample that are of particular relevance to exoplanet science, including the high-energy fluxes in the habitable zone and the farultraviolet to near-ultraviolet ratio. Combined with MUSCLES, Mega-MUSCLES provides SEDs covering a wide range of M dwarf spectral types and ages such that suitable proxies for any M dwarf planet host of interest may be found in our sample. However, we find that ultraviolet and X-ray fluxes can vary even between stars with similar parameters, such that observations of each exoplanet host star will remain the gold standard for interpreting exoplanet atmosphere observations.
Sensitivity of Modeled Soil NOx Emissions to Soil Moisture
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Longitudinal modulation of the brightness of Io's auroral footprint emission: Comparison with models
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A Leptonic Model for Neutrino Emission From Active Galactic Nuclei
It is often stated that the observation of high-energy neutrinos from an astrophysical source would constitute a smoking gun for the acceleration of hadronic cosmic rays. Here, we point out that there exists a purely leptonic mechanism to produce TeV-scale neutrinos in astrophysical environments. In particular, very high-energy synchrotron photons can scatter with X-rays, exceeding the threshold for muon-antimuon pair production. When these muons decay, they produce neutrinos without any cosmic-ray protons or nuclei being involved. In order for this mechanism to be efficient, the source in question must produce very high-energy photons which interact in an environment that is dominated by keV-scale radiation. As an example, we consider the active galaxy NGC 1068, which IceCube has recently detected as a source of TeV-scale neutrinos. We find that the neutrino emission observed from this source could potentially be generated through muon pair production for reasonable choices of physical parameters.
Peat Fires and Climate Change: Modeling Greenhouse Gas Emissions by 2100.
Abstract not provided.
Lunar surface roughness shadowing and thermal emission
Statistical model of lunar surface roughness for shadow and infrared emission characteristics
A critical test of the electrical discharge model of the Venus microwave emission
Critical test of electric discharge model for Venus microwave emission
Building Stock Models for Embodied Carbon Emissions—A Review of a Nascent Field
Building stock modeling emerges as a critical tool in the strategic reduction of embodied carbon emissions, which is pivotal in reshaping the evolving construction sector. This review provides an overall view of modern methodologies in building stock modeling, homing in on the nuances of embodied carbon analysis in construction. Examining 23 seminal papers, our study delineates two primary modeling paradigms—top-down and bottom-up—each further compartmentalized into five innovative methods. This study points out the challenges of data scarcity and computational demands, advocating for methodological advancements that promise to refine the precision of building stock models. A groundbreaking trend in recent research is the incorporation of machine learning algorithms, which have demonstrated remarkable capacity, improving stock classification accuracy by 25% and urban material quantification by 40%. Furthermore, the application of remote sensing has revolutionized data acquisition, enhancing data richness by a factor of five. This review offers a critical examination of current practices and charts a course toward an environmentally prudent future. It underscores the transformative impact of building stock modeling in driving ecological stewardship in the construction industry, positioning it as a cornerstone in the quest for sustainability and its significant contribution toward the grand vision of an eco-efficient built environment.
Take-off Engine Particle Emission Indices for In-Service Aircraft at Los Angeles International Airport
We present ground‐based, advected aircraft engine emissions from flights taking off at Los Angeles International Airport. 275 discrete engine take‐off plumes were observed on 18 and 25 May 2014 at a distance of 400 m downwind of the runway. CO2 measurements are used to convert the aerosol data into plume‐average emissions indices that are suitable for modelling aircraft emissions. Total and non‐volatile particle number EIs are of order 1016‐1017 kg‐1 and 1014‐1016 kg‐1, respectively. Black‐carbon‐equivalent particle mass EIs vary between 175‐941 mg kg‐1 (except for the GE GEnx engines at 46 mg kg‐1). Aircraft tail numbers recorded for each take‐off event are used to incorporate aircraft‐ and engine‐specific parameters into the data set. Data acquisition and processing follow standard methods for quality assurance. A unique aspect of the data set is the mapping of aerosol concentration time series to integrated plume EIs, aircraft and engine specifications, and manufacturer‐reported engine emissions certifications. The integrated data enable future studies seeking to understand and model aircraft emissions and their impact on air quality.
Variability in modelled reservoir greenhouse gas emissions: comparison of select US hydropower reservoirs against global estimates
Abstract Greenhouse gas (GHG) emissions from reservoirs have most often been evaluated on a global extent through areal scaling or linear-regression models. These models typically rely on a limited number of characteristics such as age, size, and average temperature to estimate per reservoir or areal flux. Such approaches may not be sufficient for describing conditions at all types of reservoirs. Emissions from hydropower reservoirs have received increasing attention as industry and policy makers seek to better understand the role of hydropower in sustainable energy solutions. In the United States (US), hydropower reservoirs span a wide range of climate regions and have diverse design and operational characteristics compared to those most heavily represented in model literature (i.e., large, tropical reservoirs). It is not clear whether estimates based on measurements and modeling of other subsets of reservoirs describe the diverse types of hydropower reservoirs in the US. We applied the Greenhouse Gas from Reservoirs (G‐res) emissions model to 28 hydropower reservoirs located in a variety of ecological, hydrological, and climate settings that represent the range of sizes and types of facilities within the US hydropower fleet. The dominant pathways for resulting GHG emissions estimates in the case-study reservoirs were diffusion of carbon dioxide, followed by methane ebullition. Among these case-study reservoirs, total post-impoundment areal flux of carbon ranges from 84 to 767 mgCm −2 d −1 , which is less variable than what has been reported through measurements at other US and global reservoirs. The net GHG reservoir footprint was less variable and towards the lower end of the range observed from modeling larger global reservoirs, with a range of 138 to 1,052 g CO 2 eq m −2 y −1 , while the global study reported a range of 115 to 145,472 g CO 2 eq m −2 y −1 . High variation in emissions normalized with respect to area and generation highlights the need to be cautious when using area or generation in predicting or communicating emissions footprints for reservoirs relative to those of other energy sources, especially given that many of the hydropower reservoirs in the US serve multiple purposes beyond power generation.
Models relating the radio emission and ionised gas in Seyfert nuclei
Possible models are discussed in which the radio emitting components in Seyfert II nuclei can compress and accelerate the ambient nuclear medium to produce the characteristics of the narrow line region. A first order model, which considers only the expansion of the radio components, is briefly described. However, in many Seyfert nuclei it appears that the linear motion of the radio components is also important. This can result in shock heating of the ambient medium, and if the cooling time is long enough, can lead to a displacement between the radio component and the associated emission lines. This effect may be present in NGC 1068 and NGC 5929 and by considering ram pressure balance and the cooling length it is possible to estimate lobe velocities and ambient densities.
A comparison of radiative transfer models for predicting the microwave emission from soils
Two general types of numerical models for predicting microwave emission from soils are compared-coherent and noncoherent. In the former, radiation in the soil is treated coherently, and the boundary conditions on the electric fields across the layer boundaries are used to calculate the radiation intensity. In the latter, the radiation is assumed to be noncoherent, and the intensities of the radiation are considered directly. The results of the two approaches may be different because of the effects of interference, which can cause the transmitted intensity at the surface (i.e., emissivity) to be sometimes higher and sometimes lower for the coherent case than for the noncoherent case, depending on the relative phases of reflected fields from the lower layers. This coupling between soil layers in the coherent models leads to greater soil moisture sampling depths observed with this type of model, and is the major difference that is found between the two types of models. In noncoherent models, the emissivity is determined by the dielectric constraint at the air/soil interface. The subsequent differences in the results are functions of both the frequency of the radiation being considered and the steepness of the moisture gradient near the surface. The calculations were performed at frequencies of 1.4 and 19.4 GHz and for two sets of soil profiles. Little difference was observed between the models at 19.4 GHz; and only at the lower frequency were differences apparent because of the greater soil moisture sampling depth at this frequency.
Assessment of Models of Galactic Thermal Dust Emission Using COBE/FIRAS and COBE/DIRBE Observations
Accurate modeling of the spectrum of thermal dust emission at millimeter wavelengths is important for improving the accuracy of foreground subtraction for cosmic microwave background (CMB) measurements, for improving the accuracy with which the contributions of different foreground emission components can be determined, and for improving our understanding of dust composition and dust physics. We fit four models of dust emission to high Galactic latitude COBE/FIRAS and COBE/DIRBE observations from 3 mm to 100m and compare the quality of the fits. We consider the two-level systems (TLS) model because it provides a physically motivated explanation for the observed long wavelength flattening of the dust spectrum and the anti-correlation between emissivity index and dust temperature. We consider the model of Finkbeiner et al. because it has been widely used for CMB studies, and the generalized version of this model that was recently applied to Planck data by Meisner and Finkbeiner. For comparison we have also fit a phenomenological model consisting of the sum of two-graybody components. We find that the two-graybody model gives the best fit and the FDS model gives a significantly poorer fit than the othermodels. The Meisner and Finkbeiner model and the TLS model remain viable for use in Galactic foreground subtraction, but the FIRAS data do not have a sufficient signal-to-noise ratio to provide a strong test of the predicted spectrum at millimeter wavelengths.
Modelling Solar Spectral Irradiance Variations at Ultraviolet Wavelengths
Solar UV irradiance variations with solar activity are examined using a three component model of the CaII K chromospheric emission. This model, developed from ground based observations of the location, area and relative intensity of CaII K plage, in conjunction with measurements throughout solar cycle 21 of the full disc CaII K emission, includes the contributions to the ultraviolet flux from both plage and active network emission. The model successfully replicates changes in the Lyman alpha flux related to the 27 day rotation of solar plage, outbreaks (or rounds) of activity over periods of a year or more, and the growth and accumulation of active regions over the eleven year solar activity cycles. Estimates of the magnitude of the solar cycle variability of the UV emission between 200 and 300 nm are presented but cannot currently be verified by available observations.
A Time-Varying Model for Predicting Formaldehyde Emission Rates in Homes
Recent studies have succeeded in relating emissions of various volatile organic compounds to material mass diffusion transfer using detailed empirical characteristics of each of the individual emitting materials. While significant, the resulting models are often scenario specific and/or require a host of individual component parameters to estimate emission rates. This study developed an approach to estimate aggregated emissions rates based on a wide number of field measurements. We used a multi-parameter regression model based on previous mass transfer models to predict formaldehyde emission rate for a whole dwelling using field-measured, time-resolved formaldehyde concentrations, air exchange rates, and indoor environmental parameters in 63 California single-family houses built between 2011 and 2017. The resulting model provides time-varying formaldehyde emission rates, normalized by floor area, for each study home, assuming a well-mixed mass balance transport model of the home, and a well-mixed layer transport model of indoor surfaces. The surface layer model asserts an equilibrium concentration within the surface layer of the emitted materials that is a function of temperature and RH; the dwelling ventilation rate serves as a surrogate for indoor concentration. We also developed a more generic emission model that is suitable for broad prediction of emission for a population of buildings. This model is also based on measurements aggregated from 27 homes from the same study. We showed that errors in predicting household formaldehyde concentrations using this approach were substantially less than those using a traditional constant emission rate model, despite requiring less unique building information.
An approximate model for backscattering and emission from land and sea
A two-scale model for near nadir backscattering based upon Semyonov's paper is developed for random surfaces with rms surface height smaller than one-half the incident wavelength. Reasonable estimates are obtained when this model is applied to interpret both land and sea measurements. By generalizing this approximate model (not corrected for scattering by small-scale roughnesses for scattering at large incident angles) to the bistatic case and then using it for emission calculations, reasonable estimates near nadir are also obtained when applied to emissions from the bare ground and the sea surfaces.