Coal fly ash has long been considered a potential resource for recovery of valuable elements, such as rare earth elements (REE), which are retained and concentrated upon combustion of coal feedstocks. Understanding REE occurrence within fly ash is a key to developing possible recovery methods. Recent results using modern analytical approaches shed light on the distribution REE in fly ash and the approaches required for their recovery. Some of the highest REE contents occur in fly ash derived from U.S. Appalachian Basin coals, and among these, coals influenced by input volcanic ash (Fire Clay coal, Kentucky) are especially enriched. Leaching studies of bulk fly ash show that, as a proportion of the total REE present, samples from eastern U.S. coals are generally less readily extractible than fly ash derived from western U.S. coals having lower REE contents. Direct determinations by ion microprobe show that REE in a range of fly ash samples are partitioned into aluminosilicate glasses formed during melting at boiler temperatures. These glasses comprise the largest mass fraction of coal fly ash. REE-enriched domains are present locally in fly ash at the nanometer scale (as shown by TEM), and these REE coexist with the glass phase. To enable systematic study of these REE, Ce has been proposed as a proxy for the trivalent lanthanides, as supported by speciation determinations demonstrating that Ce occurs in the trivalent form in fly ash. Despite a decreasing proportion of coal use for electric power generation in the U.S. and elsewhere, annual fly ash production, combined with coal ash already in storage, make up a large resource for potential recovery of rare earths and associated critical elements. Further developments in extraction technologies are needed to overcome difficulties in REE concentration and purification to produce REE materials of saleable purity derived from coal ash.

Horse collar aurora (HCA) are an auroral feature where the dawn and dusk sector auroral oval moves polewards and the polar cap becomes teardrop shaped. They form during prolonged periods of northward IMF, when the IMF clock angle is small. Their formation has been linked to dual-lobe reconnection (DLR) closing magnetic flux at the dayside magnetopause. The conditions necessary for DLR are currently not well-understood therefore understanding HCA statistics will allow DLR to be studied in more detail. We have identified over 600 HCA events between 2010 and 2016 in UV images captured by the Special Sensor Ultraviolet Spectrographic Imager (SSUSI) instrument on-board the Defense Meteorological Satellite Program (DMSP) spacecraft F16, F17 and F18. As expected, there is a clear preference for HCA occurring during northward IMF. We find no clear seasonal dependence in their occurrence, with an average of 8 HCA events per month. The occurrence of HCA events does not appear to depend on the Bx component of the IMF, suggesting that Bx does not modulate the rate of lobe reconnection. Considering the average radiance intensity across the dusk-dawn meridian shows the HCA as a separate bulge inside the auroral oval and that the dawn side arc of the HCA is usually brighter than the dusk in the Lyman-Birge-Hopfield short band (LBHs). We relate this to the expected field aligned current (FAC) pattern of HCA formation. We further suggest that transpolar arcs observed in the dawn sector simultaneously in both northern and southern hemispheres are misidentified HCA.

For decades, the distinction between statistical models and machine learning ones has been clear. The former are optimized to produce interpretable results, whereas the latter seeks to maximize the predictive performance of the task at hand. This is valid for any scientific field and for any method belonging to the two categories mentioned above. When attempting to predict natural hazards, this difference has lead researchers to make drastic decisions on which aspect to prioritize, a difficult choice to make. In fact, one would always seek the highest performance because at higher performances correspond better decisions for disaster risk reduction. However, scientists also wish to understand the results, as a way to rely on the tool they developed. Today, very recent development in deep learning have brought forward a new generation of interpretable artificial intelligence, where the prediction power typical of machine learning tools is equipped with a level of explanatory power typical of statistical approaches. In this work, we attempt to demonstrate the capabilities of this new generation of explainable artificial intelligence (ExAI). To do so, we take the landslide susceptibility context as reference. Specifically, we build an ExAI trained to model landslides occurred in response to the Gorkha earthquake (25 April 2015), providing an educational overview of the model design and its querying opportunities. The results are surprising, the performance are extremely high, while the interpretability can be extended to the probabilistic result assigned to single mapping units. This is also showcased in a web-GIS (\textcolor{blue}{https://arcg.is/0unziD}) platform we built.

The relatively weak tropical storms, known as low-pressure systems (LPSs), contribute as much as 60% of the seasonal precipitation over the hugely populated central India. More than a third of LPS are formed by the downstream amplification of the westward propagating disturbances from the Pacific. Here, we show that the downstream LPS genesis are associated with the tropical cyclones (TCs) in the Western North Pacific (WNP). Four major clusters of landfalling TCs that have a relatively lesser degree of recurvature account for about 83% of the downstream LPS genesis. Causality in the fluctuations of the sea level pressure over the Bay of Bengal (BoB) prior to the initiation of LPS is attributed to the Rossby wave activity over WNP through transfer entropy analysis. Our results suggest a potential for the prediction of the downstream synoptic activity over the BoB at least seven days ahead.

A document by Patrick Ongom. Click on the document to view its contents.

The shallowest intracrustal layer (extending to 8 ± 2 km depth) beneath the Mars InSight Lander site exhibits low seismic wave velocity, which are likely related to a combination of high porosity and other lithological factors. The SsPp phase, an SV-to P-wave reflection on the receiver side, is naturally suited for constraining the seismic structure of this top crustal layer since its prominent signal makes it observable with a single station without the need for stacking. We have analyzed eight broadband and low-frequency seismic events recorded on Mars and made the first coherent detection of the SsPp phase on the red planet. The timing and amplitude of SsPp confirm the existence of the ~8 km interface in the crust and the large wave speed (or impedance) contrast across it. With our new constraints from the SsPp phase, we determined that the P-wave speed in the top crustal layer is between 2.5 km/s and 3.3 km/s, which is a more precise and robust estimate than the previous range of 2.0-3.5 km/s obtained by receiver function analysis. The porosity in Layer 1 is estimated to be as much as 21-31% (assuming an aspect ratio of 0.1 for the pore space), but could be lower if some pores are filled by low-density cements or other secondary 1 mineral phases. These porosities and P-wave speeds are compatible with our current understanding of the upper crustal stratigraphy beneath the InSight Lander site.

The Earth’s magnetosheath and cusps are the sources of soft X-rays. In the accompanying paper (Part 1) and this paper, we discuss the methods of finding the magnetopause position by analyzing the X-ray images. We use the software developed for the Soft X-ray Imager (SXI) on board the forthcoming Solar wind - Magnetosphere - Ionosphere Link Explorer (SMILE) mission. We show how to find the maximum SXI count rate in noisy count maps. We verify the assumption that the maximum of the X-ray emissivity integrated along the Line-of-Sight (Ix) is tangent to the magnetopause. We consider two cases using two MHD models and apply different methods of magnetospheric masking. Overall, the magnetopause is located close to the maximum Ix gradient or between the maximum Ix gradient and the maximum Ix depending on the method used. But since the angular distance between the maximum Ix gradient and the maximum Ix is relatively small (about 3{degree sign}), the maximum Ix might be used as an indicator of the outer boundary of a wide magnetopause layer usually obtained in MHD simulations.

Recent estimates of the crustal thickness of Mars show a bimodal result of either ∼20 km or ∼40 km beneath the InSight lander. We propose an approach based on random matrix theory applied to receiver functions to further constrain the subsurface structure. Assuming a spiked covariance model for our data, we first use the phase transition properties of the singular value spectrum of random matrices to detect coherent arrivals in the waveforms. Examples from terrestrial data show how the method works in different scenarios. We identify three new converted arrivals in the InSight data, including the second multiply reflected phase from a deeper third interface. We then use this information to jointly invert receiver functions with the absolute S-wave velocity information in the polarization of body waves. Results show a crustal thickness of 43±5 km beneath the lander with two mid-crustal interfaces at depths of 8.5±1.5 km and 22±3 km.

The magnetopause standoff distance characterizes global magnetospheric compression and deformation in response to changes in the solar wind dynamic pressure and interplanetary magnetic field orientation. We cannot derive this parameter from in-situ spacecraft measurements. However, time-series of the magnetopause standoff distance can be obtained in the near future using observations by soft X-ray imagers. In two companion papers, we describe methods of finding the standoff distance from X-ray images. In Part 1, we present the results of MHD simulations which we use for the calculation of the X-ray emissivity in the magnetosheath and cusps. Some MHD models predict relatively high density in the magnetosphere, larger than observed in the data. Correcting this, we develop magnetospheric masking methods to separate the magnetosphere from the magnetosheath and cusps. We simulate the X-ray emissivity in the magnetosheath for different solar wind conditions and dipole tilts.

This study investigated the synchronous responses of vegetation to extreme temperatures and/or precipitation in the middle to high latitudes of Asia using semi-monthly observations of the leaf area index (LAI) from 1982 to 2016. The extreme states of vegetation and climate were specified using standard anomalies of the annual cycle removed variables. The results show that the area with the maximum/minimum LAI increased or decreased in correspondence with global warming. The LAI reached its maximum mostly in spring and autumn, and its minimum in summer. Generally, extreme cold and/or wet conditions inhibited forest and crop growth in the area south of 60°N, particularly from October to November. In contrast, extremely hot and/or dry conditions promoted forest growth, particularly in the central and northern parts of Siberia from August to September. However, in the arid areas of Central Asia and the Mongolian Highlands which are covered mainly by sparse vegetation and grasses, low temperature extremes and/or strong precipitation promoted vegetation growth, while high temperature extremes and/or low precipitation had adverse effects on vegetation growth. The compound extreme climates of hot-and-dry and cold-and-wet were more frequent than the cold-and-dry and hot-and-wet climates. The overall positive response of vegetation was superior to that of the negative response. The results of this study suggest a continuous increase in vegetation density and coverage over the boreal region in the future if the warming trend persists. The consequent climate feedback at regional and global scales should be given more attention.

The Radiative-Convective Equilibrium (RCE) of two models exhibiting convective aggregation has been compared. The goal of the work, following the suggestion from the Radiative-Convective Equilibrium Model Intercomparison Project (RCEMIP), is to identify key parameters controlling self-aggregation in RCE for both models and discuss the processes controlled by these parameters in order to find the simulations similarities and to test their differences. The two models studied, the SAM (System for Atmospheric Modeling) and the ARPS (Advanced Regional Prediction System), have different physical and numerical formulations. This allowed us to compare the sensitivity to processes related to self-aggregation. When self-aggregation occurs, the two models present similar statistics for what concerns precipitation, warming, and drying of the atmosphere and anvil cloud area reduction (leading to an “Iris effect’), within the spread of the RCEMIP values. On the other hand, they differ both in the degree of organization and the organization feedback: SAM is strongly organized (is on the highest quartile of the RCEMIP for the Iorg Index) and the convective organization is achieved by cloud-radiative feedback; ARPS is weakly organized (on the multi-model average of the RCEMIP for the Iorg Index) and the moisture-convection feedback is leading to the convective organization. The prevalence of one mechanism over the other has been found in the interaction between the microphysics and the sub-cloud layer properties. This comparison suggests that, in order to have a robust measure of climate sensitivity, climate models should include both types of convective organization mechanisms as shown by the two models.

These are the slides used in the RBSP Online Seminar presentation (March 25, 2022), which describe ray tracing calculations to study VLF wave dynamics in the magnetosphere.

With the advent of the array-based methods, the observations of leaky modes from earthquake records and ambient noise are frequently reported. It is urgently needed to have an effective guide to the selection of certain leaky modes to put into practical inversion combined with other imaging methods. To this end the excitation of leaky modes for multi-layered models is theoretically investigated. By computing theoretical seismograms for different source mechanisms and different source depths with the discrete wavenumber method and the normal-mode summation method separately, the contribution of leaky modes to the resultant seismograms is qualitatively evaluated and the effect of the source depth for the same source mechanism is in detail examined. Further, we perform accurate computation of leaky modes for two models and categorize the leaky modes into PL and OP (organ-pipe) modes, whose distinctive properties are characterized both from the attenuation and from the eigen-displacements of these two types of modes. Also, these results could help explain very well the occurrence of certain leaky modes on the dispersion spectrum and be indicative of the reasonable choice of certain leaky modes to put them into practical inversion for P-velocity structures.

Extensive research has shown that wind has a strong influence on estuarine circulation and salt transport. However, the response to wind forcing in estuarine systems presents challenges due in part to the complexities of realistic forcing conditions, system states, and geomorphologies. To further advance the understanding of estuarine responses to wind forcing, a comprehensive analysis of stratification and mixing during a typical southeast wind event was conducted in Mobile Bay, a microtidal, wide, shallow, and river-dominated estuary in the northern Gulf of Mexico. An analysis of the vertical salinity variance and its associated budget terms shows that the system generally becomes less stratified and fully mixed across much of the system; however, there was significant spatial heterogeneity in physical processes driving the evolution of the water column stratification over the course of the event. Surprisingly, in some regions of the bay, dissipation of salinity variance was secondary to contributions from straining and advection. Furthermore, local wind stress and remote wind driven Ekman transport affected stratification responses and their relative impacts varied spatially across the estuary. Direct turbulent mixing from local wind stress and straining dominated the stratification responses away from the main tidal inlet where estuarine-shelf exchange (i.e., current velocity structure and advection of salinity) from Ekman transport controlled the vertical mixing. This detailed case study highlights the complexity of wind influences in a system like Mobile Bay, a representative typical of the northern Gulf of Mexico and other coastal region.

Several locations across the United States in non-compliance with the national standard for ground-level ozone (O3) are thought to have sizeable influences from distant extra-regional emission sources or natural stratospheric O3, which complicates design of local emission control measures. To quantify the amount of long-range transported O3 (LRT O3), its origin, and change over time, we conduct and analyze detailed sensitivity calculations characterizing the response of O3 to emissions from different source regions across the Northern Hemisphere in conjunction with multi-decadal simulations of tropospheric O3 distributions and changes. Model calculations show that the amount of O3 at any location attributable to sources outside North America varies both spatially and seasonally. On a seasonal-mean basis, during 1990-2010, LRT O3 attributable to international sources steadily increased by 0.06-0.2 ppb yr-1 at locations across the United States and arose from superposition of unequal and contrasting trends in individual source-region contributions, which help inform attribution of the trend evident in O3 measurements. Contributions of emissions from Europe steadily declined through 2010, while those from Asian emissions increased and remained dominant. Steadily rising NOx emissions from international shipping resulted in increasing contributions to LRT O3, comparable to those from Asian emissions in recent years. Central American emissions contribute a significant fraction of LRT O3 in southwestern United States. In addition to the LRT O3 attributable to emissions outside of North America, background O3 across the continental United States is comprised of a sizeable and spatially variable fraction that is of stratospheric origin (29-78%).

This article is composed of three independent commentaries about the state of ICON principles (Goldman et al. 2021) in Science and Society section and discussion on the opportunities and challenges of adopting them. Each commentary focuses on a different topic: Citizen Science; Collaboration across Sciences; and Education Policy. Scientific discoveries, rapid scientific and technological advancements, and solutions benefit society. However, many societal challenges require evolved frameworks and measures to address the 21st-century complex problems. The ICON (Integrated, Coordinated, Open, and Networked) approach to advance science in society formulates the interdisciplinary perspectives and coordinated network that provide solutions to the complex issues in our society. The three independent commentaries embody ICON processes, and further presents challenges and untapped opportunities in these broad areas that can create a better understanding of the impact of science on society.

Lower-band whistler-mode chorus waves are important to the dynamics of Earth’s radiation belts, playing a key role in accelerating seed population electrons (100’s of keV) to relativistic ($>$ 1 MeV) energies, and in scattering electrons such that they precipitate into the atmosphere. When constructing and using statistical models of lower-band whistler-mode chorus wave power, it is commonly assumed that wave power is spatially distributed with respect to magnetic L-shell. At the same time, these waves are known to drop in power at the plasmapause, a cold plasma boundary which is dynamic in time and space relative to L-shell. This study organizes wave power and propagation direction data with respect to distance from the plasmapause location to evaluate what role the location of the plasmapause may play in defining the spatial distribution of lower band whistler-mode chorus wave power. It is found that characteristics of the statistical spatial distribution of equatorial lower band whistler mode chorus are determined by L-shell, and are largely independent of plasmapause location. The primary physical importance of the plasmapause is to act as an Earthward boundary to lower band whistler mode chorus wave activity. This behavior is consistent with an equatorial lower band whistler mode chorus wave power spatial distribution that follows the L-shell organization of the particles driving wave growth.

Many subsurface fluid flows, including the storage of CO underground or the production of oil, are transient processes incorporating multiple fluid phases. The fluids are not in equilibrium meaning macroscopic properties such as fluid saturation and pressure vary in space and time. However, these flows are traditionally modelled with equilibrium (or steady-state) flow properties, under the assumption that the pore scale fluid dynamics are equivalent. In this work, we used fast synchrotron X-ray tomography with 1s time resolution to image the pore scale fluid dynamics as the macroscopic flow transitioned to steady-state. For nitrogen or decane, and brine injected simultaneously into a porous rock we observed distinct pore scale fluid dynamics during transient flow. Transient flow was found to be characterised by intermittent fluid occupancy, whereby flow pathways through the pore space were constantly rearranging. The intermittent fluid occupancy was largest and most frequent when a fluid initially invaded the rock. But as the fluids established an equilibrium the dynamics decreased to either static interfaces between the fluids or small-scale intermittent flow pathways, depending on the capillary number and viscosity ratio. If the fluids were perturbed after an equilibrium was established, by changing the flow rate, the transition to a new equilibrium was quicker than the initial transition. Our observations suggest that transient flows require separate modelling parameters. The timescales required to achieve equilibrium suggest that several metres of an invading plume front will have flow properties controlled by transient pore scale fluid dynamics.