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We present multiwavelength photometry and spectroscopy of SN 2022jli, an unprecedented Type Ic supernova discovered in the galaxy NGC 157 at a distance of ≈ 23 Mpc. The multiband light curves reveal many remarkable characteristics. Peaking at a magnitude ofg= 15.11 ± 0.02, the high-cadence photometry reveals periodic undulations of 12.5 ± 0.2 days superimposed on the 200-day supernova decline. This periodicity is observed in the light curves from nine separate filter and instrument configurations with peak-to-peak amplitudes of ≃ 0.1 mag. This is the first time that repeated periodic oscillations, over many cycles, have been detected in a supernova light curve. SN 2022jli also displays an extreme early excess that fades over ≈25 days, followed by a rise to a peak luminosity ofL_opt= 10^42.1erg s⁻¹. Although the exact explosion epoch is not constrained by data, the time from explosion to maximum light is ≳ 59 days. The luminosity can be explained by a large ejecta mass (M_ej≈ 12 ± 6M_⊙) powered by⁵⁶Ni, but we find it difficult to quantitatively model the early excess with circumstellar interaction and cooling. Collision between the supernova ejecta and a binary companion is a possible source of this emission. We discuss the origin of the periodic variability in the light curve, including interaction of the SN ejecta with nested shells of circumstellar matter and neutron stars colliding with binary companions.

 

By direct measurements of the gas temperature, the Atacama Large Millimeter/submillimeter Array (ALMA) has yielded a new diagnostic tool to study the solar chromosphere. Here, we present an overview of the brightness-temperature fluctuations from several high-quality and high-temporal-resolution (i.e. 1 and 2 s cadence) time series of images obtained during the first 2 years of solar observations with ALMA, in Band 3 and Band 6, centred at around 3 mm (100 GHz) and 1.25 mm (239 GHz), respectively. The various datasets represent solar regions with different levels of magnetic flux. We perform fast Fourier and Lomb–Scargle transforms to measure both the spatial structuring of dominant frequencies and the average global frequency distributions of the oscillations (i.e. averaged over the entire field of view). We find that the observed frequencies significantly vary from one dataset to another, which is discussed in terms of the solar regions captured by the observations (i.e. linked to their underlying magnetic topology). While the presence of enhanced power within the frequency range 3–5 mHz is found for the most magnetically quiescent datasets, lower frequencies dominate when there is significant influence from strong underlying magnetic field concentrations (present inside and/or in the immediate vicinity of the observed field of view). We discuss here a number of reasons which could possibly contribute to the power suppression at around 5.5 mHz in the ALMA observations. However, it remains unclear how other chromospheric diagnostics (with an exception of H α line-core intensity) are unaffected by similar effects, i.e. they show very pronounced 3-min oscillations dominating the dynamics of the chromosphere, whereas only a very small fraction of all the pixels in the 10 ALMA datasets analysed here show peak power near 5.5 mHz. This article is part of the Theo Murphy meeting issue ‘High-resolution wave dynamics in the lower solar atmosphere’. 

A frequent barrier to addressing some of our world’s most pressing environmental challenges is a lack of funding. Currently, environmental project funding largely comes from philanthropic and public sources, but this does not meet current needs. Increased coordination and collaboration between multiple levels and sectors of government, in addition to private sector funding, can help address the environmental funding challenge. New financial tools and strategies can enable this transition and facilitate uptake of innovative solutions. One such mechanism, the Environmental Impact Bond (EIB), is an emerging financial tool with the potential to transform the environmental funding landscape. However, these financial instruments are not well understood or recognized beyond those actively involved in EIB projects or in the field of conservation finance. As EIBs gain momentum, there is a clear need for a common framework, including definitions and nomenclature, research needs, and outlook for the future. In this paper, we define EIB mechanics, elucidate the difference between EIBs and Green Bonds, and propose a common vocabulary for the field. Drawing on first-hand experience with the few EIBs which have been deployed, we review and assess lessons learned, trends, and paths for the future. Finally, we propose a set of future targets and discuss research goals for the field to unify around. Through this work, we identify a concrete set of research gaps and objectives, providing evidence for EIBs as one important tool in the environmental finance toolbox.

 

In this study, we explore the use of unsteady transit time distribution (TTD) theory to model solute transport in biofilters, a popular form of nature‐based or “green” storm water infrastructure (GSI). TTD theory has the potential to address many unresolved challenges associated with predicting pollutant fate and transport through these systems, including unsteadiness in the water balance (time‐varying inflows, outflows, and storage), unsteadiness in pollutant loading, time‐dependent reactions, and scale‐up to GSI networks and urban catchments. From a solution to the unsteady age conservation equation under uniform sampling, we derive an explicit expression for solute breakthrough during and after one or more storm events. The solution is calibrated and validated with breakthrough data from 17 simulated storms at a field‐scale biofilter test facility in Southern California, using bromide as a conservative tracer. TTD theory closely reproduces bromide breakthrough concentrations, provided that lateral exchange with the surrounding soil is accounted for. At any given time, according to theory, more than half of the water in storage is from the most recent storm, while the rest is a mixture of penultimate and earlier storms. Thus, key management endpoints, such as the pollutant treatment credit attributable to GSI, are likely to depend on the evolving age distribution of water stored and released by these systems.