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We analyze the properties of relativistic (>700 keV) electron precipitation (REP) events measured by the low-Earth-orbit (LEO) POES/MetOp constellation of spacecraft from 2012 through 2023. Leveraging the different profiles of REP observed at LEO, we associate each event with its possible driver: waves or field line curvature scattering (FLCS). While waves typically precipitate electrons in a localized radial region within the outer radiation belt, FLCS drives energy-dependent precipitation at the edge of the belt. Wave-driven REP is detected at any MLT sector and L shell, with FLCS-driven REP occurring only over the nightside–a region where field line stretching is frequent. Wave-driven REP is broader in radial extent on the dayside and accompanied by proton precipitation over 03–23 MLT, either isolated or without a clear energy-dependent pattern, possibly implying that electromagnetic ion cyclotron (EMIC) waves are the primary driver. Across midnight, both wave-driven and FLCS-driven REP occur poleward of the proton isotropic boundary. On average, waves precipitate a higher flux of >700 keV electrons than FLCS. Both contribute to energy deposition into the atmosphere, estimated of a few MW. REP is more associated with substorm activity than storms, with FLCS-driven REP and wave-driven REP at low L shells occurring most often during strong activity (SML* < −600 nT). A preliminary analysis of the Solar Wind (SW) properties before the observed REP indicates a more sustained (∼5 h) dayside reconnection for FLCS-driven REP than for wave-driven REP (∼3 h). The magnetosphere appears more compressed during wave-driven REP, while FLCS-driven REP is associated with a faster SW of lower density. These findings are useful not only to quantify the contribution of >700 keV precipitation to the atmosphere but also to shed light on the typical properties of wave-driven vs FLCS-driven precipitation which can be assimilated into physics-based and/or predictive radiation belt models. In addition, the dataset of ∼9,400 REP events is made available to the community to enable future work.

Abstract We statistically evaluate the global distribution and energy spectrum of electron precipitation at low‐Earth‐orbit, using unprecedented pitch‐angle and energy resolved data from the Electron Losses and Fields INvestigation CubeSats. Our statistical results indicate that during active conditions, the ∼63 keV electron precipitation ratio peaks at L > 6 at midnight, whereas the spatial distribution of precipitating energy flux peaks between the dawn and noon sectors. ∼1 MeV electron precipitation ratio peaks near midnight at L > ∼6 but is enhanced near dusk during active times. The energy spectrum of the precipitation ratio shows reversal points indicating energy dispersion as a function of L shell in both the slot region and at L > ∼6, consistent with hiss‐driven precipitation and current sheet scattering, respectively. Our findings provide accurate quantification of electron precipitation at various energies in a broad region of the Earth's magnetosphere, which is critical for magnetosphere‐ionosphere coupling.

Abstract Whistler mode waves in the plasmasphere and plumes drive significant losses of energetic electrons from the Earth's radiation belts into the upper atmosphere. In this study, we conducted a survey of amplitude‐dependent whistler wave properties and analyzed their associated background plasma conditions and electron fluxes in the plasmasphere and plumes. Our findings indicate that extremely large amplitude (>400 pT) whistler waves (a) tend to occur at L > 4 over the midnight‐dawn‐noon sectors and have small wave normal angles; (b) are more likely to occur during active geomagnetic conditions associated with higher fluxes of anisotropic electrons at 10 s keV energies; and (c) tend to occur at higher latitudes up to 20° with increasing amplitude. These results suggest that extremely large amplitude whistler waves in the plasmasphere and plumes could be generated locally by injected electrons during substorms and further amplified when propagating to higher latitudes.

Electromagnetic ion cyclotron (EMIC) waves can scatter radiation belt electrons with energies of a few hundred keV and higher. To accurately predict this scattering and the resulting precipitation of these relativistic electrons on short time scales, we need detailed knowledge of the wave field’s spatio-temporal evolution, which cannot be obtained from single spacecraft measurements. Our study presents EMIC wave models obtained from two-dimensional (2D) finite-difference time-domain (FDTD) simulations in the Earth’s dipole magnetic field. We study cases of hydrogen band and helium band wave propagation, rising-tone emissions, packets with amplitude modulations, and ducted waves. We analyze the wave propagation properties in the time domain, enabling comparison with in situ observations. We show that cold plasma density gradients can keep the wave vector quasiparallel, guide the wave energy efficiently, and have a profound effect on mode conversion and reflections. The wave normal angle of unducted waves increases rapidly with latitude, resulting in reflection on the ion hybrid frequency, which prohibits propagation to low altitudes. The modeled wave fields can serve as an input for test-particle analysis of scattering and precipitation of relativistic electrons and energetic ions.

Hiss waves play an important role in removing energetic electrons from Earth’s radiation belts by precipitating them into the upper atmosphere. Compared to plasmaspheric hiss that has been studied extensively, the evolution and effects of plume hiss are less understood due to the challenge of obtaining their global observations at high cadence. In this study, we use a neural network approach to model the global evolution of both the total electron density and the hiss wave amplitudes in the plasmasphere and plume. After describing the model development, we apply the model to a storm event that occurred on 14 May 2019 and find that the hiss wave amplitude first increased at dawn and then shifted towards dusk, where it was further excited within a narrow region of high density, namely, a plasmaspheric plume. During the recovery phase of the storm, the plume rotated and wrapped around Earth, while the hiss wave amplitude decayed quickly over the nightside. Moreover, we simulated the overall energetic electron evolution during this storm event, and the simulated flux decay rate agrees well with the observations. By separating the modeled plasmaspheric and plume hiss waves, we quantified the effect of plume hiss on energetic electron dynamics. Our simulation demonstrates that, under relatively quiet geomagnetic conditions, the region with plume hiss can vary from L = 4 to 6 and can account for up to an 80% decrease in electron fluxes at hundreds of keV at L > 4 over 3 days. This study highlights the importance of including the dynamic hiss distribution in future simulations of radiation belt electron dynamics.

Abstract Precipitation into the Earth's atmosphere due to pitch angle scattering by plasma waves has been recognized as one of the major loss mechanisms for energetic electrons. In this study, we quantitatively evaluate their roles in precipitating electrons during a conjunction event with modulated electron precipitation observed at low altitudes by Electron Loss and Fields INvestigation and three types of whistler mode waves (hiss, plume hiss, and chorus) measured near the equator by Time History of Events and Macroscale Interactions during Substorms. Electron precipitation was observed from ∼50 keV to

We show an application of supervised deep learning in space sciences. We focus on the relativistic electron precipitation into Earth’s atmosphere that occurs when magnetospheric processes (wave-particle interactions or current sheet scattering, CSS) violate the first adiabatic invariant of trapped radiation belt electrons leading to electron loss. Electron precipitation is a key mechanism of radiation belt loss and can lead to several space weather effects due to its interaction with the Earth’s atmosphere. However, the detailed properties and drivers of electron precipitation are currently not fully understood yet. Here, we aim to build a deep learning model that identifies relativistic precipitation events and their associated driver (waves or CSS). We use a list of precipitation events visually categorized into wave-driven events (REPs, showing spatially isolated precipitation) and CSS-driven events (CSSs, showing an energy-dependent precipitation pattern). We elaborate the ensemble of events to obtain a dataset of randomly stacked events made of a fixed window of data points that includes the precipitation interval. We assign a label to each data point: 0 is for no-events, 1 is for REPs and 2 is for CSSs. Only the data points during the precipitation are labeled as 1 or 2. By adopting a long short-term memory (LSTM) deep learning architecture, we developed a model that acceptably identifies the events and appropriately categorizes them into REPs or CSSs. The advantage of using deep learning for this task is meaningful given that classifying precipitation events by its drivers is rather time-expensive and typically must involve a human. After post-processing, this model is helpful to obtain statistically large datasets of REP and CSS events that will reveal the location and properties of the precipitation driven by these two processes at all L shells and MLT sectors as well as their relative role, thus is useful to improve radiation belt models. Additionally, the datasets of REPs and CSSs can provide a quantification of the energy input into the atmosphere due to relativistic electron precipitation, thus offering valuable information to space weather and atmospheric communities.

The built environment remains a strategic research and innovation domain in view of the goal of full decarbonization. The priority is the retrofitting of existing buildings as zero-emission to improve their energy efficiency with renewable energy technologies pulling the market with cost-effective strategies. From the first age of photovoltaics (PV) mainly integrated in solar roofs, we rapidly moved towards complete active building skins where all the architectural surfaces are photoactive (Building Integrated Photovoltaics - BIPV). This change of paradigm, where PV replaces a conventional building material, shifted the attention to relate construction choices with energy and cost effectiveness. However, systematic investigations which put into action a cross-disciplinary approach between construction, economic and energy related domains is still missing. This paper provides the detailed assessment of a real multifamily building, taking into account retrofit scenarios for making active the building skin, with the goal to identify the sensitive aspects of the energetic and economic effectiveness of BIPV design options. By assuming a real case study with monitored data, the analysis will consider a breakdown of the main individual parts composing the building envelope, by then combining alternative re-configurations in merged clusters with different energy and construction goals. Results will highlight the correlation between building skin construction strategies and the energy and cost parameters by identifying the cornerstones for enhancing efficiency. The outcomes, related to the total life cost, self-consumption/sufficiency, in combination with different building design options (façade, roof, balconies, surface orientations, etc.), provide a practical insight for researchers and professionals to identify renovation strategies by synergistically exploiting the solar active parts towards lower global costs and higher energy efficiency of the whole building system.

In the last decades, the topic of lighting of the historical minor centres is taking a prominent role in the cultural debate on the urban recovery interventions, because of the development of a greater awareness of the regenerative potential role that a careful planning system of urban lighting can take in this context. The latter, which had a purely functional role in the past, has recently taken a figurative and emotional role, associated with the vision of the urban light scene during the night and its valorization. The study of light, therefore, has inevitably turned into an instrument of knowledge and critical interpretation of the urban spaces, aimed both to functional recovery of the lighting network technology, and the regeneration of the urban image and its night scenes. The needs that this sector should satisfy are multiple and, sometimes, conflicting: the need for road safety, the reduction of light pollution, the need for energy and cost savings. The research aims to define an operative methodology to deal with the light planning in complex contexts as the minor historical centers, in which the concept of transformation of the urban scene clashes directly with the concept of preserving the identity features of the places and its constructive values and materials. Among the goals, there is therefore the aim of highlighting the main gaps in the network, due both to plant engineering reasons and to the obsolescence of the existing lighting fixtures. We operatively work in the urban voids system field, as spaces that characterize the urban scene. Through the knowledge of their dominant features it is possible to preserve their identity and, at the same time, enhance their singularity, with a suitable lighting project, which requires the study of materials, colors and consumption. The purpose is to promote an urban development, able to produce positive economic, social and cultural effects, oriented to improve the quality of life, as well as to value the architectural and environmental heritage giving importance to energy and economic saving.

This article looks at a knowledge-based approach to emergency situations caused by earthquakes or other natural disasters, and illustrates how a multidisciplinary approach enables the integration of technical requirements with those of a historical and cultural nature. The case study presented is the recovery of the ex-city hospital of L’Aquila, in Italy, which was hit by an earthquake in 2009. The integrated use of varying investigation methodologies allowed us to establish the effectiveness of a knowledge-based approach, and generated new ideas for the development of the structure and its strategic role within the city.

We analyze the Cartwheel coronal mass ejection's (CME; 2008 April 9) trajectory in the low corona with the ForeCAT model. This complex event presented a significant rotation in the low corona and a reversal in its original latitude direction. We successfully reproduce the observed CME’s trajectory (latitude and longitude deflection) and speed. Through a test, we are able to constrain the CME’s mass to (2.3−3.0) × 1014 g and the CME’s initial shape. We are able to constrain the expansion of the CME as well: the angular width linearly increases until 2.1 , and is constant afterward. In order to match the observed latitude, we include a non-radial initial speed of −42 km s−1. Despite allowing the CME to rotate in the model, the magnetic forces of the solar background are not able to reproduce the observed rotation. We suggest that the complex reversal in latitude and the significant rotation of the Cartwheel CME can be justified with an asymmetrical reconnection event that ejected the CME non-radially and also initiated its rotation. [ABSTRACT FROM AUTHOR]