The NASA Ames Stereo Pipeline (ASP) is an open source software of automated geodesy and photogrammetry tools to process satellite, aerial camera, and historical imagery with and without accurate camera pose information using a structure-from-motion (SfM) methodology. ASP is designed to generate topographic digital surface models (DSM). We added to the ASP topographic module a bathymetric module to derive near shore bathymetry using satellite panchromatic bands (PAN), and multispectral bands. The process is semiautomatic and can generate either topographic, bathymetric or topo-bathymetric (TB) seamless 3D point clouds and DSM in the same vertical and horizontal coordinate systems. The bathymetric results depend heavily on the water surface elevation and while previous methods considered the water surface horizontal, our bathymetric module takes into consideration the earth curvature for the considered satellite imagery. A land / water mask can be automatically derived using NIR bands or can be user defined. The new ASP bathymetry module was tested using WorldView-2 panchromatic and green band stereo imagery in Florida Keys (Key West) FL from May 2015. The nearshore PAN and GRN bathymetric results around Key West, FL were validated against bathymetric lidar collected in 2017. The validation errors improve with adding camera calibration and finally alignment to prior topographic lidar data (no bathymetry data used) from 1.0778 m root mean square error (RMSE) to 0.4052 m RMSE to 0.2480 m RMSE, respectively. For PAN bands the depth penetration around Key West was around 4 m with a TB DSM resolution of 1 m. For the same area, using the green (GRN) band the bathymetric validation RMSE in absence of camera adjustment or alignment was 1.1040 m, with camera adjustment RMSE improves to 0.6846 m, and with topographic alignment RMSE is 0.5854. For the green bands the depth penetration in Key West was approximately 7 m with a TB DSM resolution of 2 m.

In the energy transition context, the design of integrated multi-energy systems is key for reaching ambitious sustainability objectives. Due to the intermittent nature of the renewable energy sources, introducing technologies for storing and transforming energy in different carriers (e.g., electricity, gas, heat) is, in fact, a strategic solution for fully exploiting the renewable power generation, increasing the flexibility of the system, and contributing to the decarbonization. Although the need to rely on multi-energy systems is widely shared, identifying their optimal design requires the use of complex modelling tools able to characterize the territory, simulate the system dynamics, and evaluate the solutions with respect to different sustainability objectives. To support the decarbonization decision-making process, in this work we develop a three-step modelling chain for planning optimal multi-energy systems at the local scale. More precisely, we first perform a territory characterization by estimating, through different methodologies, input data of renewable resource availability, territory exploitation potential, and energy demand of electricity and heat. Then, we carry out a multi-energy analysis identifying Pareto optimal system designs with respect to two sustainability objectives, namely the Net Present Cost and the CO2 emissions. Finally, we perform an intersectoral Multi Criteria Analysis-Cost Benefit Analysis (MCA-CBA) for evaluating the solutions obtained in the previous step with respect to a wide range of indicators representing energy, economic, and social acceptance aspects. The CBA approach is adopted for evaluating the financial and economic viability of the investment options, while the assessment of non-monetary impacts is performed through the MCA approach. We apply the modelling chain to the real case study of Sulcis Iglesiente (Sardinia, Italy), a territory characterized by carbon-intensive industries, recently selected for receiving funding from the Just Transition Fund launched by the EU Commission in the context of the Green Deal. Expected results aim to demonstrate the validity of the proposed modelling chain in the identification of the best interventions for supporting the decarbonization and the sustainable development of Sulcis Iglesiente.

Satellite observations are widely used to investigate, monitor, and forecast volcanic activity. Spaceborne thermal infrared (TIR) measurements of high-temperature volcanic features improve our understanding of the underlying processes and our ability to identify reactivation of activity, forecast eruptions, and assess hazards. In particular, thermal changes, indicative of subtle pre-eruptive volcanic thermal activity, have been observed. Over the last several decades, different approaches have been explored to detect and estimate the temperature above background of these thermal anomalies. The most common approach relies on a spatial statistical analysis based on a scene by scene choice of the background temperature region. Satisfactory results have also been shown by using time series anomaly detection algorithms based on statistical profiling approach. Artificial intelligence (AI) is growing sharply in different remote sensing fields because of its capability to automatically learn patterns from the data. Here, we develop an AI approach to automatically detect volcanic thermal features by using spatiotemporal information from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), LANDSAT-8 Thermal Infrared Sensor (TIRS) and MODerate-resolution Imaging Spectroradiometer (MODIS) data acquired over several decades. Our goal is to exploit AI techniques using a combination of high temporal and high spatial resolution satellite data to improve thermal volcanic monitoring and detect very low-level anomalies caused by pre-eruptive activity. We use both low-spatial, high-temporal resolution MODIS data to detect hotter thermal features at short time scales; as well as high-spatial low-temporal resolution ASTER TIR and TIRS data to detect more subtle thermal changes otherwise missed by MODIS. Our analysis is conducted in Google Earth Engine (GEE), a cloud computing platform with fast access and processing of satellite data. The comparison with a new statistical algorithm is documented in a companion abstract in this session.

Stable isotope geochemistry of terrestrial carbonates provides important opportunities to answer questions about climates, environments, and ecosystems both in the present day and the geologic past. Here we present a case study from the Cretaceous Newark Canyon Formation (NCF) type section (~98–113 Ma), where we explore how climate and depositional settings influence the stable isotope record in highly variable lacustrine and palustrine carbonates. The NCF was deposited within the hinterland of the Sevier orogenic belt and allows us to examine how North American terrestrial climate changed during the mid-Cretaceous, a time of potentially significant regional surface uplift and increasing global temperatures related to the Cretaceous Thermal Maximum (Di Fiori et al., 2020; Huber et al., 2018). In this study, we find substantial inter- and intra-facies heterogeneity, despite having formed in the same overall climate setting, highlighting the differences between lacustrine and palustrine environments. Stable carbon, oxygen, and clumped isotopes (δ13C, δ18Ocarbonate, and Δ47) paired with optical and cathodoluminescence petrography from along-strike lateral and vertical stratigraphic sections show significant isotopic variability between and within seven carbonate facies (Fetrow et al., 2020). Palustrine deposition is interpreted to have occurred along a spectrum of shallow water depths preserved in two key palustrine sub-facies endmembers – shallower mottled micrite and deeper pebbly, peloid-rich micrite. These record mean Δ47 temperatures of 51ºC and 44°C, respectively. The mottled micrite has heavier calculated δ18O of formation water (δ18Owater) values indicating increased evaporative enrichment, which suggests more intense desiccation during deposition. Lacustrine sediments preserved in laminated biomicrite to massive micrite have mean Δ47 temperatures of 50ºC and 37°C, respectively. Elevated temperatures and δ13C, δ18Ocarb, and δ18Owater values more similar to values from NCF secondary spar veins indicate that the biomicrite sub-facies underwent diagenetic alteration. We will discuss the implications of these results for the NCF and the Cretaceous western USA paleoclimate record, as well as general lessons learned for interpreting mixed terrestrial carbonate facies records.

The stated mission of the International Arctic Research Center (IARC) at the University of Alaska Fairbanks (UAF) is ”to foster Arctic research to help the nation and the world understand, prepare for, and adapt to the pan-Arctic impacts of climate change.” IARC’s work and collaborations are everywhere in the Arctic and beyond. One of IARC’s core values is actively cultivating an environment of diversity and inclusion where all individuals and groups feel welcomed and are heard. Through the work of the IARC Diversity and Inclusion Working Group, we affirm that our different experiences, expertise, and ways of knowing are our strength, fostering diverse thoughts and ideas. Collaborative science and administrative support by people from diverse backgrounds and knowledge systems helps IARC build a professional culture of inclusion, listening, caring and respect. We face challenges in DEI work and are actively addressing them. For example, in addressing the challenge of time constraints by the all-volunteer membership, a DEI coordinator position to spearhead our efforts is being created and funding sought. We highlight efforts from the IARC Diversity and Inclusivity Working Group to cultivate a culture of inclusion, equity and access: 1) collaboratively developing an institutional diversity and inclusivity statement and land acknowledgement statement, 2) creating safe spaces for conversation and action through open biweekly working group meetings and discussions, 3) elevating awareness through relevant workshops, trainings and discussions, 4) collectively incorporating diversity and inclusion values into the IARC strategic plan, 5) making presentations and documents accessible, and 6) actively collaborating on inclusion efforts within UAF, Alaska and beyond. We welcome new members with their ideas and perspectives to the working group. At IARC, we recognize that inclusion is an ongoing process that has to be woven into all that we do in research, education and outreach.

Acetone is an abundant volatile organic compound with important influence on ozone and atmospheric self-cleaning processes. The budget of acetone is influenced by various sources and sinks. Direct sources include anthropogenic, terrestrial vegetation, oceanic, and biomass burning emissions, while chemistry forms acetone from other compounds. Sinks include deposition onto the land and ocean surfaces, as well as chemical loss. The GISS Earth System Model, ModelE, is capable of simulating a variety of Earth system interactions. Previously, acetone had a very simplistic representation in the ModelE chemical scheme. This study assesses a greatly improved acetone tracer scheme, in which acetone's sources, sinks and atmospheric transport are now tracked in 3 dimensions. Extensive research was conducted to assess how well past literature supported the new global acetone budget. Anthropogenic, vegetation, biomass burning, and deposition schemes fit well with previous studies. While their net fluxes were well-supported, source and sink terms for chemistry and the ocean were overestimated and underestimated, respectively. In iterations of the chemistry scheme, it was found that the production of acetone from hydrocarbon oxidation is a strong leverage to the overall chemical source. Spatial distributions reveal that ocean uptake of acetone dominates northern latitudes, while production is mainly in mid-southern latitudes. Ocean surface conditions influence ocean-acetone interactions and will be considered when modifying the ocean scheme in future work. The seasonality of acetone-related processes was also studied in conjunction with field measurements around the world. These comparisons show promising results, but have shortcomings at urban locations, since the model's resolution is too coarse to capture high-emission areas. Overall, an analysis of the acetone budget aids the development of the tracer in the GISS ModelE, a crucial step to parameterizing the role of acetone in the atmosphere.

The radiation bias over the Southern Ocean was terribly bad in MRI-CGCM3 that was used for CMIP5 simulations. However, the bias is significantly reduced in MRI-ESM2 (Yukimoto et al. 2019) that is used for CMIP6 simulations by various modifications related to clouds (Kawai et al. 2019). On the other hand, the double-ITCZ problem is also alleviated in the MRI-ESM2 (Tian and Dong, 2020). Is the reduction in the Southern Ocean radiation bias the cause of alleviation of the double-ITCZ problem? Each modification that contributed to the reduction of the Southern Ocean radiation bias in the MRI-ESM2 was progressively reverted to the corresponding older treatment in order to examine their individual impacts on the ITCZ problem. Results show the double-ITCZ problem worsens almost monotonically when the excessive shortwave insolation over the Southern Ocean increases (Kawai et al. 2020, 2021).

The twin pressures to achieve mind-share and to harness available computing power drive the evolution of geoscientific data analysis tools. Such tools have enabled a remarkable progression in the atomic or fundamental unit of data they can easily analyze. In the mid-1980s we analyzed one or a few naked arrays at at time, and now researchers routinely intercompare climatological ensembles each comprising thousands of files of heterogeneous variables richly dressed in metadata. Two complementary semantic trends have empowered this analytical revolution: more intuitive and concise analysis commands that can exploit more standardized and brokered self-describing data stores. This talk highlights how tool developers can leverage these trends to successfully imagine and build the analysis tools of tomorrow by understanding the needs of domain researchers and the power of domain specific languages today. This talk will also highlight recent improvements in compression speed and interoperability that geoscientists can exploit to reduce our carbon footprint. Observations and simulations to advance Earth system sciences generate exabytes of archived data per year. Storage accounts for about 40% of datacenter power consumption, with its attendant consequences for greenhouse gas emissions and environmental sustainability. Precision-preserving lossy compression can further reduce the size of losslessly compressed data by 10-25% without compromising its scientific content. Modern lossless codecs (e.g., Zstandard or Zlib-ng) accelerate compression and decompression, relative to the traditional Zlib, by factors of 2-5x with no penalty in compression ratio. These proven modern compression technologies can help geoscientific datacenters become significantly greener.

Previous studies of the East African upper mantle have invoked one or more mantle upwellings with varying thermochemical nature to underly the distribution of surface volcanism. For example, Boyce and Cottaar (2021) suggest that a hot, chemically distinct upwelling beneath the southern East African Rift (EAR) is sourced from the African Large Low Velocity Province (LLVP), while magmatism in Ethiopia may lie above an additional purely thermal upwelling. Constraints on chemical heterogeneities in the upper mantle may be derived from studying the seismically observable impedance contrasts that they produce. Away from subduction zones, two causal mechanisms are possible to explain the X-discontinuity (X; 230-350km): the coesite-stishovite phase transition and/or carbonate silicate melting, both of which require entrainment of basalt from the lower mantle. Intriguingly, carbonate silicate melt was invoked by Rooney et al., (2012) to explain the discrepancy in upper mantle temperature anomalies predicted by seismic wavespeed and petrological estimates beneath East Africa. Further, active carbonatite magmatism occurs along the edge of the Tanzanian craton (Muirhead et al., 2020). Several recent regional to continental receiver function (RF) studies have identified potential observations of the X in East Africa. These studies are not focused on the presence of these upper mantle phases or lack the spatial sampling needed to robustly identify the X and its causal mechanism. Targeted high-resolution observations of the X are required to confirm the presence of exotic converted phases in the East African upper mantle and their relationship to mantle upwellings. We capitalise on the new TRAILS dataset from the Turkana depression (Bastow, 2019; Ebinger, 2018) and an adjacent network in neighbouring Uganda (Nyblade, 2017), to supplement our existing RF database and characterise the X across active continental rift setting in unprecedented detail. The prevalence of the X is mapped beneath East Africa, and subsequently compared to other areas of the African continent.

California’s Central Valley is responsible for $17 billion of annual agricultural output, producing 1/4 of the nation’s food. However, land in the Central Valley is sinking at a rapid rate (as much as 20 cm per year) due to continued groundwater pumping. Land subsidence has a significant impact on infrastructure resilience and groundwater sustainability. It is important to understand subsidence and groundwater depletion in a consistent framework using improved models capable of simulating in-situ well observations and observed subsidence. Currently, groundwater well data is sparse and sampled irregularly, compromising our understanding of groundwater changes. Moreover, groundwater pumping data is a major missing piece of the puzzle. Limited data availability and spatial/temporal uncertainty in the available data have hampered understanding the complex dynamics of groundwater and subsidence. To address this limitation, we first integrated multimodal data including InSAR, groundwater, precipitation, and soil composition by interpolating data with the same spatial and temporal resolutions. We then identified regions with different temporal dynamics of land displacement, groundwater depth, and precipitation. Some areas (e.g., Helm) with coarser grain soil compositions exhibited potentially reversible land transformations (elastic land compaction). Finally, we fed the integrated data into the deep neural network of a gated recurrent unit-based sequence-to-sequence generation model. We found that the combination of InSAR, groundwater depth, and precipitation data had predictive power for soil composition using deep neural networks (correlation coefficient R=0.83, normalized Nash-Sutcliffe model efficiency NNSE=0.84). A random forest model was tested as baseline (R=0.65, NNSE=0.69). We also achieved significant accuracy with only 40% of the training data (NNSE=0.8), suggesting that the model can be generalized to other regions for indirect estimation of soil composition. Our results indicate that soil composition can be estimated using InSAR, groundwater depth and precipitation data. In-situ measurements of soil composition can be expensive and time consuming and may be impractical in some areas. The generalizability of the model sheds light on high spatial resolution soil composition estimation utilizing existing measurements.

The volcanic eruption that began on 19 March 2021 at Fagradalsfjall is the first one to occur on the Reykjanes Peninsular for nearly 800 years and in Fagradalsfjall for about 6000 years. The feeder-dike was injected from a magma reservoir whose top is at about 10 km depth below the surface (but the reservoir itself reaches much greater depths). The dike formation involved at least two roof ruptures and resulting dike segments. The first occurred on 24 February and the second on 14 March 2021. The first rupture, marked by earthquakes of M23 close to the contact between the roof and the magma, occurred in the eastern half of the toppart of the reservoir. An injected dike segment propagated towards the surface but became arrested at the depths of 0.5-2 km. As its vertical propagation became arrested, while continuing to receive magma, the segment spread laterally, reaching an overall maximum dike strike-dimension (length) of about 10 km. The second rupture, also marked by earthquakes of M2-3, occurred about 1 km to the west of the first rupture. The injected dike segment following the second rupture eventually resulted in the dike propagating to the surface to feed the eruption which started on 19 March. We estimate the average vertical rate of the feeder-dike propagation at about 0.02 m s-1. This is an order of magnitude lower than common rates of lateral dike propagation in rift zones, yet similar to the average rate during the Bardarbunga (Iceland) 2014 dike propagation (around 0.04 m s-1). The initial volcanic fissure fed by the second dike segment had a length of less than 200 m and an opening of a fraction of a metre. Subsequently, several more ‘dike-fingers’ reached the surface and generated volcanic fissure segments. The total length of the discontinuous, segmented fissure is many hundred metres – but only one crater is presently active. Using the aspect ratio of the fissure and basic fracture mechanics, we estimate the magmatic overpressure (driving pressure) at the beginning of the eruption as about 3 MPa. The low driving pressure and small fissure opening displacement and length are in harmony with the very low volumetric flow (effusion) rate of about 10 m3 s-1.

Taylor Glacier, located in the McMurdo Dry Valleys of Antarctica has piqued curiosity since the first observations in 1903. Episodic release of iron-rich brine at or near the glacier terminus rapidly oxidizes, forming a visually striking red stain on the ice and glacier forefield called ‘Blood Falls’. The triggering mechanism behind these releases is unknown. The recent history of brine releases have been well documented since the 1993-94 summer season. To better understand the frequency and extent of brine releases over a longer time period we compile a detailed history of observations of the Taylor terminus from photographs, journals, field reports, oral histories, and published papers prior to the onset of more frequent monitoring in the 1990s. We developed a confidence assessment framework for our interpretation of the presence/absence of brine icing deposits. Results show that of the 30 summer seasons between 1903-1904 and 1993-1994 with interpretable observations, 21 seasons (70%) show evidence of brine flow events, and 9 seasons show no evidence of brine flow. At least two of these brine flow events are newly reported by our study. Concurrent observations of the glacier terminus over the same period showed a localized advance and collapse of a small portion of the southern terminus. We demonstrate a framework to fuse multiple data types and qualitatively assess the confidence level of our interpretations that could be applied to similar investigations of environmental history. We encourage other researchers to explore and contribute to the growing collection of open access historical archives.

Biochar is the carbon rich product of organic waste pyrolysis under oxygen-free conditions. Biochar properties are inherited from the raw materials used and can be enhanced with production methods. The versatility of the raw materials, along with the tweaks in production methods, enable biochars to have a widely varied range of properties, that make it suitable for a multitude of applications. This versatility, in turn, makes characterization, and performance monitoring challenging especially in large scale applications, typical of biochar use. Biochars have unique electrical properties that could be used to fill this gap. The complex electrical properties of biochar remain largely unstudied; this work explores them for different types and concentrations of biochar in porous media. Early measurements on the complex conductivity signatures of biochars, show promising results for both characterization and mass/volume estimation. Biochar surface properties appear have a profound effect on complex conductivity signals, suggesting the potential use of such methods as characterization and monitoring tools, even in large scale operations.

Landslide dams can result in substantial flood hazards caused by dam formation, overtopping, and dam failure. Previous studies have established datasets on a regional or global scale and identified indices to estimate the probability of landslide dam formation. These datasets are collections of landslide dam records from multiple data sources. However, the precision and accuracy of the landslide dam record’s spatial information hinder the completeness of data and prevents the possibility of linking with other relevant datasets, and thus hinders the exploration of factors affecting landslide dam formation. We established a new global-scale landslide dam dataset, named River Augmented Global Landslide Dams (RAGLAD), which geolocates those records whose location was vaguely known or completely unknown and combined this with additional data from global fluvial datasets to make the data record more comprehensive. We use RAGLAD to study the processes of landslide dam formation. The spatial distribution of landslide dam records, data distribution, triggering processes and preconditions, and the relationships between geomorphological parameters directly derived from RAGLAD help understanding areas prone to landslide dam conditions, and delineate potential thresholds for landslide dam formation. The results are compared with relationships achieved from general landslides studies to find the specific conditions of landslide dam formation. These conditions can be further applied for filtering the potential hazard occurrence area and calculating the landslide dam formation susceptibility.

A recent study categorized the Madden-Julian Oscillation (MJO) during the boreal winter season into four types including stand, jump, slow eastward propagating, and fast eastward propagating MJO. This study focuses on the stand and jump MJO events. Based on whether their convection penetrates the Maritime Continent (MC), stand and jump MJO are combined as non-penetrating (NP) MJO, while the rest two types are combined as eastward-penetrating (EP) MJO. Results reveal the relative roles of the westward-propagating wave (WPW), as well as the QBO and ENSO, in limiting MJO propagation. Lack of the pre-moistening over the southern sea surface of MC is responsible for NP MJO’s failure to penetrate MC. The active convection of WPW hinders the NP MJO descending branch over the Pacific and therfore leads to the insufficient meridional advective moistening over the southern sea surface of the MC. The overall drying over the MC for jump MJO also comes from the intraseasonal dry amonalies induced by WPW over the western Pacific, which are then advected to MC by the superposed seasonal mean northern easterlies. The independent convection over the Pacific for jump MJO is influenced by a combined effect of the QBO and ENSO. Under the influence of the preferred QBO westerly (QBOW) phase, the tropopause instability of NP MJO is decoupled with its convection. The decoupled tropopause instability propagates eastward into the Pacific, and amplifies the local WPW convection there for jump MJO. For stand MJO, however, the La Nina-like seasonal mean cool sea surface temperature (SST) anmalies confine WPW within the western Pacific. Therefore, the decoupled tropopause instability of stand MJO is out phase of WPW over the central Pacific, and fails to induce an independent convection as a result. The similar diagnosis is further applied to the CESM2 and E3SM CMIP6 historical simulations to investigate the MJO diversity and propagation in climate models. Four MJO types as in the observation are successfully categorized in these two models. The accompanied westward propagating waves over the central-western Pacific for NP MJO events are also evident. However, models suffer from some biases in MJO propagation such as too many NP MJO events than the observation.

Modeling the terrestrial impacts of the sun’s solar wind is critical to understanding geomagnetic storms. We use a database of 144 storms from 2010-2019 and showed how these storms affect magnetometers on the ground. We also extracted profiles of the magnetic field along the magnetotail. Skill scores are assigned to the individual stations on the ground based on how well they can forecast magnetic indeces like SYM-H and AL. We us our Space Weather Modeling Framework’s geospace configuration. Our model includes coupling of 3D MHD solver (BATSRUS), the Rice Convection Model, and the Ridley Ionospheric Model. We have found that all stations have a positive Heidke Skill Score which is encouraging in terms of space weather forecasting.

With population surge, industrialization and urbanization; use of surfactants has increased manifold. After their use in households and industries, surfactants either end up in sewerage systems or are directly discharged into surface waters. They can hence be found dispersed in water phase or adsorbed onto aquatic sediments and sewage sludge. Due to limited metabolic pathways, most of the common surfactants are not degradable in anaerobic conditions that generally prevail in sewage ingressed water bodies so sludge accumulated in these water bodies after the anaerobic digestion process is rich in surfactants (Ying, 2006, Environ. Int.). Sediment is a complex mixture of organic (bacteria, proteins, humic and fulvic acids, humin, etc.) and inorganic (silica, minerals, metal oxides and hydroxides, aluminosilicates) components. Absorptivity of surfactant depends on the sorbent composition and type of surfactant (Ishiguro & Koopal, 2016, Adv. Colloid Interface Sci.). A crucial question related to surfactant absorption is its reversibility- as to whether the surfactant can desorb. The knowledge of this can be beneficial in understanding the environmental fate of surfactants. The presence of surfactants in water bodies can form foams. Generally, foaming in surface water is a result of a mixture of surfactants from various sources (Schilling & Zessner, 2011, Water Res.). However, contribution of sediment as a source of surfactant in a foaming water body has not been studied adequately. Also, existence of surfactants in water, beyond certain concentrations not only induces unpleasant taste and odor, but also causes undesirable changes in the ecosystem. Thus, it becomes imperative to study the ratio of the surfactant associated with water, to the extent of surfactant associated the sorbent such as sediment/sludge to understand the environmental risk associated with surfactant. This study aims to understand a foaming urban lake which foams only after heavy rainfalls. This study tests the hypothesis that surfactants accumulate in the lake sediment in significant proportions and desorbs upon dilution occurring due to addition of rainwater into the lake. This when churned by heavy runoff causes large quantities of stable foam. This study aims at analyzing the role of lake sediment in foaming of a lake.

Mineral dust particles are ubiquitous in the atmosphere and can be transported vast distances affecting climate, air quality, and human health on a global scale. Mineralogical composition has a substantial impact on dust properties and their effects. Natural dust samples are both fine-grained and composed of many different minerals. Most commonly, X-ray diffraction (XRD) has been used to characterize dust mineralogy; however, this technique is less effective for identifying poorly crystalline or amorphous phases. We used Fourier Transform Infrared (FTIR) spectroscopy as a complementary method to identify minerals and their abundances. Long wave infrared (LWIR) spectra (2.5 to 25 μm) are sensitive to molecular bonds rather than crystallography providing additional details. We performed both XRD and reflectance spectroscopy to characterize 37 atmospheric dust samples collected in Ilam City, Iran. The dominant minerals in these samples are quartz, feldspar (albite), calcite and clays (illite, montmorillonite, kaolinite). LWIR reflectance is strongly dependent on particle size but published data of pure silicate minerals in the size range of the Ilam samples (0-63 μm) still show characteristic signatures between 8 and 10 µm (Salisbury et al. 1991; Wenrich and Christensen, 1996). Surprisingly, diagnostic silicate features were not observed in any of the samples although carbonate and OH bonds in the clay minerals were readily identified. Past studies have shown that porosity, grain size and packing can reduce the spectral contrast in the LWIR and additional effects include grain coatings or the interaction of multiple minerals. We also identify a peak at 7.8 µm which may be attributed to anomalous dispersion or the interaction of quartz and calcite in this spectral range. In order to understand the absence of Si-O features we made transmission measurements of representative samples in KBr pellets. Transmission is not influenced by multiple scattering and should clearly detect fundamental Si-O absorptions. Transmission spectra show broad features that include contributions from all silicate minerals (quartz, feldspar and clays) both near 10 μm and at longer wavelengths. We are using various spectral modeling techniques and will compare abundances derived from reflectance and transmission measurements.