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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Detection and imaging of chemicals and hidden explosives using terahertz time-domain spectroscopy and deep learning

Detecting concealed chemicals and explosives remains a critical challenge in global security. Terahertz time-domain spectroscopy (THz-TDS) offers a promising non-invasive and stand-off detection technique owing to its ability to penetrate optically opaque materials without causing ionization damage. While many chemicals exhibit distinct spectral features in the terahertz range, conventional terahertz-based detection methods often struggle in real-world environments, where variations in sample geometry, thickness, and packaging can lead to inconsistent spectral responses. In this study, we present a chemical imaging system that integrates THz-TDS with deep learning to enable accurate pixel-level identification and classification of different explosives. Operating in reflection mode and enhanced with plasmonic nanoantenna arrays, our THz-TDS system achieves a peak dynamic range of 96 dB and a detection bandwidth of 4.5 THz, supporting practical, stand-off operation. By analyzing individual time-domain pulses with deep neural networks, the system exhibits strong resilience to environmental variations and sample inconsistencies. Blind testing across eight chemicals—including pharmaceutical excipients and explosive compounds—resulted in an average classification accuracy of 99.42% at the pixel level. Notably, the system maintained an average accuracy of 88.83% when detecting explosives concealed under opaque paper coverings, demonstrating its robust generalization capability. These results highlight the potential of combining advanced terahertz spectroscopy with neural networks for highly sensitive and specific chemical and explosive detection in diverse and operationally relevant scenarios.

Imaging and sensing↗
NASA NTRS2019

Synthesis of Meteoritic Reaction Intermediates

The organic compounds of carbo- naceous chondrites are structurally diverse products of the prolonged abiotic chemistry that occurred before and during the early stages of the solar system [1]. They also represent the types of prebiotic compounds that may have participated in chemical evolutionary processes that gave rise to life [2]. Pyruvic acid is a key component of primary metabolism that has recently been found in carbonaceous chondrites [3]. Its prominence in biology has inspired us to explore its chemistry and possible role in the origin of metabolism. Our laboratory investigations have found that pyruvate (the ionized form of pyruvic acid) can serve as a single-source reactant to generate what we term a pyruvate reaction network (PRN). The core of the PRN is driven by pyruvate aldol polymerization and decay reactions. These decay reactions lead to the production of stable and unstable compounds which include mono, di, and tricarboxylic acids and a variety of keto acids. Finding evidence of this reaction network in meteorites would establish that the chemistry of pyruvate did occur in a prebiotic environment. Many of the known compounds found in pyruvate reaction mixtures were originally detected in meteorite samples by Cooper et al in 2011. However, multiple synthetic origins not tied to pyruvate chemistry might also explain their meteoritic presence. Thus, a search to find compounds unique to the PRN, such as reaction intermediates, would provide stronger evidence to demonstrate its prebiotic relevance. The identity of these intermediates can only be confirmed by acquiring chemical standards, however, as most are not available commercially, they need to be accessed through chemical synthesis.

Rios, Andro C.↗
NASA NTRS2019

Finding Evidence of a Prebiotic Pyruvate Reaction Network in Meteorites

The organic compounds of carbonaceous chondrites are structurally diverse products of the prolonged abiotic chemistry that occurred before and during the early stages of the solar system. They also represent the types of prebiotic compounds that may have participated in chemical evolutionary processes that gave rise to life. Pyruvic acid is a key component of primary metabolism that has recently been found in carbonaceous chondrites. Its prominence in biology has inspired us to explore its chemistry and possible role in the origin of metabolism. Our laboratory investigations have found that pyruvate (the ionized form of pyruvic acid) can serve as a single-source reactant to generate what we term a pyruvate reaction network (PRN). The core of the PRN is driven by pyruvate aldol polymerization and decay reactions. These decay reactions lead to the production of stable and unstable compounds which include mono, di, and tricarboxylic acids and a variety of keto acids. Importantly, many of these reactions apparently lead back to pyruvate, establishing a feedback process. Finding evidence of this reaction network in meteorites would establish that the chemistry of pyruvate did occur in a prebiotic environment and indeed many of the known compounds found in pyruvate reaction mixtures were detected in the Murchison and Murray meteorites. However, multiple synthetic origins, not tied to pyruvate chemistry, might also explain their meteoritic presence. Thus finding compounds unique to the PRN, such as reaction intermediates, would provide stronger evidence in support of its prebiotic relevance. The identity of these intermediates can only be confirmed by acquiring chemical standards, however, as most are not available commercially, we engaged in extensive chemical synthesis. Obtaining these standards also provides the opportunity to study their subsequent chemistry and roles in the PRN.

Rios, Andro↗
DOE OSTI2023

Revealing the Chemical State of Palladium in Operating In 2 O 3 Gas Sensors: Metallic Pd Enhances Sensing Response and Intermetallic In x Pd y Compound Blocks It

The sensing response of metal oxides activated with noble metal nanoparticles is significantly influenced by changes to the chemical state of corresponding elements under operating conditions. Here, a PdO/rh-In 2 O3 consisting of PdO nanoparticles loaded onto rhombohedral In 2 O 3 was studied as a gas sensor for H 2 gas (100–40000 ppm in an oxygen-free atmosphere) in the temperature range of 25–450 °C. The phase composition and chemical state of elements were examined by resistance measurements combined with synchrotron-based in situ X-ray diffraction and ex situ X-ray photoelectron spectroscopy. As found, PdO/rh-In 2 O 3 undergoes a series of structural and chemical transformations during operation: from PdO to Pd/PdH x and finally to the intermetallic In x Pd y phase. The maximal sensing response (R N2 /R H2 ) of ~5 · 10 7 towards 40000 ppm (4 vol %) H 2 at 70 °C is correlated with the formation of PdH 0.706 /Pd. The In x Pd y intermetallic compounds formed around 250 °C significantly decrease the sensing response.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2019

Finding Evidence of a Prebiotic Pyruvate Reaction Network in Meteorites

The organic compounds of carbonaceous chondrites are structurally diverse products of the prolonged abiotic chemistry that occurred before and during the early stages of the solar system. They also represent the types of prebiotic compounds that may have participated in chemical evolutionary processes that gave rise to life. Pyruvic acid is a key component of primary metabolism that has recently been found in carbonaceous chondrites. Its prominence in biology has inspired us to explore its chemistry and possible role in the origin of metabolism. Our laboratory investigations have found that pyruvate (the ionized form of pyruvic acid) can serve as a single-source reactant to generate what we term a pyruvate reaction network (PRN). The core of the PRN is driven by pyruvate aldol polymerization and decay reactions. These decay reactions lead to the production of stable and unstable compounds which include mono, di, and tricarboxylic acids and a variety of keto acids. Importantly, many of these reactions apparently lead back to pyruvate, establishing a feedback process. Finding evidence of this reaction network in meteorites would establish that the chemistry of pyruvate did occur in a prebiotic environment and indeed many of the known compounds found in pyruvate reaction mixtures were detected in the Murchison and Murray meteorites. However, multiple synthetic origins, not tied to pyruvate chemistry, might also explain their meteoritic presence. Thus finding compounds unique to the PRN, such as reaction intermediates, would provide stronger evidence in support of its prebiotic relevance. The identity of these intermediates can only be con-firmed by acquiring chemical standards, however, as most are not available commercially, we engaged in extensive chemical synthesis. Obtaining these standards also provides the opportunity to study their subsequent chemistry and roles in the PRN.

Rios, A. C.↗
NASA NTRS2022

Chirality in Organic and Mineral Systems: A Review of Reactivity and Alteration Processes Relevant to Prebiotic Chemistry and Life Detection Missions

Chirality is a central feature in the evolution of biological systems, but the reason for biology’s strong preference for specific chiralities of amino acids, sugars, and other molecules remains a controversial and unanswered question in origins of life research. Biological polymers tend toward homochiral systems, which favor the incorporation of a single enantiomer (molecules with a specific chiral configuration) over the other. There have been numerous investigations into the processes that preferentially enrich one enantiomer to understand the evolution of an early, racemic, prebiotic organic world. Chirality can also be a property of minerals; their interaction with chiral organics is important for assessing how post-depositional alteration processes could affect the stereochemical configuration of simple and complex organic molecules. In this paper, we review the properties of organic compounds and minerals as well as the physical, chemical, and geological processes that affect organic and mineral chirality during the preservation and detection of organic compounds. We provide perspectives and discussions on the reactions and analytical techniques that can be performed in the laboratory, and comment on the state of knowledge of flight-capable technologies in current and future planetary missions, with a focus on organics analysis and life detection.

chirality↗
DOE OSTI2025

Soft X-ray Emission Spectroscopy of Phosphorus Compounds for Energy Conversion and Storage

Phosphorus (P) is a ubiquitous component of materials for energy conversion and storage. Despite the effectiveness of soft X-ray emission spectroscopy (XES) to characterize these complex materials, XES studies of P-containing compounds are still largely missing. In this investigation, the electronic structure and XES signatures from the P L 2,3 -edge are probed for nine solid-state P-containing compounds characterized by various oxidation states and chemical environments: GaP (3−) , InP (3−) , red-P (0) , H 3 P (3+) O 3 , Na 2 H 2 P 2 (4+) O 6 , H 3 P (5+) O 4 , KH 2 P (5+) O 4 , Na 2 HP (5+) O 4 , and InP (5+) O 4 . The XES spectrum of each material exhibits distinct spectral fingerprints, which provide a robust basis for the speciation of complex P-containing samples. Density functional theory calculations shed light on the electronic structure of selected materials and particularly on the effect of phosphorus-oxygen hybridization. This study provides a comprehensive understanding of P L 2,3 XES spectral fingerprints across a wide range of oxidation states and chemical environments. These data sets and insights pave the way for dedicated future work, such as in situ and operando investigations of P-containing compounds in energy-related applications, where speciation of P compounds is needed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Pickaxe: a Python library for the prediction of novel metabolic reactions

Abstract Background Biochemical reaction prediction tools leverage enzymatic promiscuity rules to generate reaction networks containing novel compounds and reactions. The resulting reaction networks can be used for multiple applications such as designing novel biosynthetic pathways and annotating untargeted metabolomics data. It is vital for these tools to provide a robust, user-friendly method to generate networks for a given application. However, existing tools lack the flexibility to easily generate networks that are tailor-fit for a user’s application due to lack of exhaustive reaction rules, restriction to pre-computed networks, and difficulty in using the software due to lack of documentation. Results Here we present Pickaxe, an open-source, flexible software that provides a user-friendly method to generate novel reaction networks. This software iteratively applies reaction rules to a set of metabolites to generate novel reactions. Users can select rules from the prepackaged JN1224min ruleset, derived from MetaCyc, or define their own custom rules. Additionally, filters are provided which allow for the pruning of a network on-the-fly based on compound and reaction properties. The filters include chemical similarity to target molecules, metabolomics, thermodynamics, and reaction feasibility filters. Example applications are given to highlight the capabilities of Pickaxe: the expansion of common biological databases with novel reactions, the generation of industrially useful chemicals from a yeast metabolome database, and the annotation of untargeted metabolomics peaks from an E. coli dataset. Conclusion Pickaxe predicts novel metabolic reactions and compounds, which can be used for a variety of applications. This software is open-source and available as part of the MINE Database python package ( https://pypi.org/project/minedatabase/ ) or on GitHub ( https://github.com/tyo-nu/MINE-Database ). Documentation and examples can be found on Read the Docs ( https://mine-database.readthedocs.io/en/latest/ ). Through its documentation, pre-packaged features, and customizable nature, Pickaxe allows users to generate novel reaction networks tailored to their application.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Computational prediction of ferromagnetic 𝐴⁢𝑇 6 ⁢𝑋 6 kagome compounds

We present a systematic high-throughput density-functional-theory investigation of the structural and magnetic stability of 312 substitutional compounds in the magnetic kagome 𝐴⁢𝑇 6⁢ 𝑋 6 family. Our screening confirms the stability of many previously reported structures and predicts several additional stable candidates. Within collinear spin configurations, we find that Fe-based systems predominantly adopt antiferromagnetic ground states, whereas Mn-based analogs exhibit a more balanced distribution between ferromagnetic and antiferromagnetic order. For compounds exhibiting several nearly degenerate collinear configurations, we analyze the nature of their magnetic ground states, assess the possible emergence of noncollinear order, and discuss the limitations and uncertainties inherent to standard density-functional approaches. Our electronic structure analysis further reveals that predicted ferromagnetic kagome systems display characteristic features of topological metals, with rich magnetic configurations that can be tuned by chemical substitution. Altogether, these ferromagnetic kagome compounds constitute a broad and still largely unexplored materials platform for the emergence of exciting magnetotransport phenomena.

Density functional calculations↗
DOE OSTI2025

Formation of late-generation atmospheric compounds inhibited by rapid deposition

Reactive organic carbon species are important fuel for atmospheric chemical reactions, including the formation of secondary organic aerosol. However, in parallel to atmospheric oxidation processes, deposition can remove compounds from the atmosphere and impact downstream environments. To understand the impact of deposition on atmospheric oxidation, we present a framework for predicting and visualizing the fate of a molecule on the basis of the physicochemical properties of compounds (Henry’s law constant, vapour pressure and reaction rate constants), which are used to estimate timescales for oxidation and deposition. Further, by implementing our deposition rates in chemical models, we show that deposition substantially suppresses atmospheric reactivity and aerosol formation by removing early-generation products and preventing the formation of large fractions (up to 90%) of downstream, late-generation compounds. Deposition is frequently missing in the laboratory experiments and detailed chemical modelling, which probably biases our understanding of atmospheric composition.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2017

Using Advanced Mass Spectrometry Techniques to Fully Characterize Atmospheric Organic Carbon: Current Capabilities and Remaining Gaps

Organic compounds in the atmosphere vary widely in their molecular composition and chemical properties, so no single instrument can reasonably measure the entire range of ambient compounds. Over the past decade, a new generation of in-situ, field-deployable mass spectrometers has dramatically improved our ability to detect, identify, and quantify these organic compounds, but no systematic approach has been developed to assess the extent to which currently available tools capture the entire space of chemical identity and properties that is expected in the atmosphere. Reduced-parameter frameworks that have been developed to describe atmospheric mixtures are exploited here to characterize the range of chemical properties accessed by a suite of instruments. Multiple chemical spaces (e.g. oxidation state of carbon vs. volatility, and oxygen number vs. carbon number) were populated with ions measured by several mass spectrometers, with gas- and particle-phase α-pinene oxidation products serving as the test mixture of organic compounds. Few gaps are observed in the coverage of the parameter spaces by the instruments employed in this work, though the full extent to which comprehensive measurement was achieved is difficult to assess due to uncertainty in the composition of the mixture. Overlaps between individual ions and regions in parameter space were identified, both between gas- and particle-phase measurements, and within each phase. These overlaps were conservatively found to account for little (<10%) of the measured mass. However, challenges in identifying overlaps and in accurately converting molecular formulas into chemical properties (such as volatility or reactivity) highlight a continued need to incorporate structural information into atmospheric measurements.

G. Isaacman-VanWertz↗
NASA NTRS2013

Surface-Enhanced Raman Scattering Using Silica Whispering-Gallery Mode Resonators

The motivation of this work was to have robust spectroscopic sensors for sensitive detection and chemical analysis of organic and molecular compounds. The solution is to use silica sphere optical resonators to provide surface-enhanced spectroscopic signal. Whispering-gallery mode (WGM) resonators made from silica microspheres were used for surface-enhanced Raman scattering (SERS) without coupling to a plasmonic mechanism. Large Raman signal enhancement is observed by exclusively using 5.08-micron silica spheres with 785-nm laser excitation. The advantage of this non-plasmonic approach is that the active substrate is chemically inert silica, thermally stable, and relatively simple to fabricate. The Raman signal enhancement is broadly applicable to a wide range of molecular functional groups including aliphatic hydrocarbons, siloxanes, and esters. Applications include trace organic analysis, particularly for in situ planetary instruments that require robust sensors with consistent response.

Anderson, Mark S.↗
DOE OSTI2020

Application and assessment of deep learning for the generation of potential NMDA receptor antagonists

Uncompetitive antagonists of the N-methyl D-aspartate receptor (NMDAR) have demonstrated therapeutic benefit in the treatment of neurological diseases such as Parkinson's and Alzheimer's, but some also cause dissociative effects that have led to the synthesis of illicit drugs. The ability to generate NMDAR antagonists in silico is therefore desirable for both new medication development and preempting and identifying new designer drugs. Recently, generative deep learning models have been applied to de novo drug design as a means to expand the amount of chemical space that can be explored for potential drug-like compounds. In this study, we assess the application of a generative model to the NMDAR to achieve two primary objectives: (i) the creation and release of a comprehensive library of experimentally validated NMDAR phencyclidine (PCP) site antagonists to assist the drug discovery community and (ii) an analysis of both the advantages conferred by applying such generative artificial intelligence models to drug design and the current limitations of the approach. We apply, and provide source code for, a variety of ligand- and structure-based assessment techniques used in standard drug discovery analyses to the deep learning-generated compounds. Overall, we present twelve candidate antagonists that are not available in existing chemical databases to provide an example of what this type of workflow can achieve, though synthesis and experimental validation of these compounds are still required.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Structural Phase Transitions in the van der Waals Ferromagnets Fe x Pd y Te 2

Two-dimensional van der Waals (vdW) magnets are attracting significant attention, both as platforms for studying fundamental magnetic interactions and for the exciting possibility of utilizing them as building blocks in devices and heterostructures, which may lead to new physical phenomena and functionalities. Here, we provide a detailed study of the crystal structure and physical properties of the recently discovered vdW ferromagnet FePd 2 Te 2 . We find this compound has a relatively wide width of formation, and grow single crystals with compositions Fe x Pd y Te 2 where x ranges from 0.9 to 1.1 and y from 1.8 to 2.5, respectively. Temperature-dependent X-ray diffraction and transport measurements reveal that a first-order structural transition occurs in the range of T = 360–420 K, where the critical temperature, modulation wave vector, and corresponding room-temperature crystal structures all depend on chemical composition. Above the transition, the compounds with Pd fraction y > 2 adopt a disordered derivative of the tetragonal FeTe structure, with the Fe layer showing mixed Fe/Pd occupancy and the extra Pd atoms partially occupying interstitial sites. Below 370 K, the structure is incommensurately modulated, likely associated with the complex ordering of Pd/Fe atoms in the metal layers or the interstitial Pd in the vdW gaps. For y < 2, the composition Fe 1.1 Pd 1.8 Te 2 has monoclinic symmetry at room temperature that is consistent with the reported structure of FePd 2 Te 2 . This phase undergoes a structural transition at 420 K for which the high temperature structure is yet to be determined; however, based on the similarities with the y > 2 compounds, we speculate that its T > 420 K structure is also tetragonal. Importantly, the high temperature, symmetry-breaking structural transition observed here provides a likely explanation for the origin of the structural domains previously observed in FePd 2 Te 2 . All compounds investigated in the Fe x Pd y Te 2 series show metallic behavior, with magnetic characterization indicating that they are easy-plane, hard, ferromagnets with T C spanning 98–180 K. Both the critical temperature for the structural transition and the Curie temperature are moderately suppressed with increasing Pd fraction y and corresponding decreasing Fe fraction x, indicating that synthetic control over x and y paves way for the further exploration of these compounds.

crystal structure↗
NASA NTRS1984

Solar wind and cosmic ray irradiation of grains and ices - application to erosion and synthesis of organic compounds in the solar system

Solar wind and cosmic and cosmic ray irradiation of grains induces physical and chemical effects including their erosion and the synthesis of molecular compounds within the implanted layers. The experiments performed with H2O ice implanted by keV ions are presented. The ion implantation is intended to simulate the irradiation of comets, ring grains, and satellites of outer planets, either by the primitive solar particles or by contemporary solar wind (SW) or solar cosmic rays (SCR) fluxes. The detection of molecules was obtained through in-situ infrared spectroscopy. A model is proposed for the formation of organic matter within icy solar system bodies which is in agreement with experimental results of erosion rates. The organic molecules, frozen-in within the icy mantles of the grains present in the protosolar nebula, would originate from their primitive irradiation. Such an irradiation would have taken place during an early stage of the proto-sun, when both the SW and SCR particles were more intense by orders of magnitude.

Rocard, F.↗
DOE OSTI2025

An energetic link between order and strength in metals: A nanocrystalline strength limit in high-entropy alloys and intermetallic compounds

The metallurgy and materials communities have long understood and exploited fundamental links between chemical and structural ordering in metallic solids to tailor their mechanical properties. We extend these ideas to include prediction of the nanocrystalline strength limit in high-entropy alloys and intermetallic compounds, where a breakdown occurs in the classical Hall-Petch strengthening behavior. The highest reported strength achievable through alloying has rapidly climbed and given rise to new classifications of materials with extraordinary properties, with a notable case being nanocrystalline metals. High-entropy alloys (chemically disordered, concentrated solid solutions) and intermetallic compounds are two boundary cases of how tailored order can be used to manipulate mechanical behavior. Here, we show that the complex electronic-structure mechanisms governing the peak strength of alloys and pure metals can be reduced to a few physically meaningful parameters based on their atomic arrangements and used – with no fitting parameters – to predict the maximum strength of these materials. This includes a generalized energy-based accounting for the degree of structural and chemical ordering that allows for rapid and reasonably accurate prediction of peak strength (validated in the nanocrystalline limit) as a function of temperature. Predictions of maximum strength based on the activation energy (with all materials properties derived from DFT calculations or experiments) for a stress-driven transition to an amorphous state is shown to accurately describe the breakdown in Hall-Petch behavior at the smallest crystallite sizes for pure metals, intermetallic compounds, high-entropy alloys, and metallic glasses. Further, this activation energy is also shown to be directly proportional to interstitial electronic charge density, which is a good predictor of ductility, stiffness (moduli), and phase stability in high-entropy alloys and solid metals generally. The proposed framework suggests the possibility of coupling ordering and intrinsic strength to mechanisms like dislocation nucleation, hydrogen embrittlement, and transport properties, such as through correlations between the activation energies for amorphization with stacking-fault and grain boundary energies. It additionally opens the prospect for greatly accelerated structural materials design and development to address materials challenges limiting more sustainable and efficient use of energy.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Expanding the use of ethanol as a feedstock for cell-free synthetic biochemistry by implementing acetyl-CoA and ATP generating pathways

Abstract Ethanol is a widely available carbon compound that can be increasingly produced with a net negative carbon balance. Carbon-negative ethanol might therefore provide a feedstock for building a wider range of sustainable chemicals. Here we show how ethanol can be converted with a cell free system into acetyl-CoA, a central precursor for myriad biochemicals, and how we can use the energy stored in ethanol to generate ATP, another key molecule important for powering biochemical pathways. The ATP generator produces acetone as a value-added side product. Our ATP generator reached titers of 27 ± 6 mM ATP and 59 ± 15 mM acetone with maximum ATP synthesis rate of 2.8 ± 0.6 mM/h and acetone of 7.8 ± 0.8 mM/h. We illustrated how the ATP generating module can power cell-free biochemical pathways by converting mevalonate into isoprenol at a titer of 12.5 ± 0.8 mM and a maximum productivity of 1.0 ± 0.05 mM/h. These proof-of-principle demonstrations may ultimately find their way to the manufacture of diverse chemicals from ethanol and other simple carbon compounds.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRSDate not supplied

Evaluating Diurnal Ozone Emissions: A Comparative Analysis of DSCOVR EPIC, PANDORA, and TOLNet Data for Space-Based Monitoring Assessment: A Case Study by ASDC

Stratospheric ozone occurs naturally in the upper atmosphere, forming a protective layer that shields us from the sun's harmful ultraviolet rays. Tropospheric ozone is not emitted directly into the air but is created by chemical reactions between nitrogen oxides (NOx) and volatile organic compounds (VOC). This reaction happens when pollutants emitted by cars, power plants, industrial boilers, refineries, chemical plants, and other sources chemically react in sunlight [1]. Therefore, increased levels of tropospheric ozone indicate the presence of pollutants in the air. While daily anthropogenic activity causes an increase of ground-level ozone, variation of stratospheric ozone changes happens much slower, so that variation of the total ozone column reflects the variation of the tropospheric column due to natural, e.g., wildfires and anthropogenic air pollution. Both total and tropospheric ozone column products are used in this study. The reflectance spectra measured by the Earth Polychromatic Imaging Camera (EPIC) instrument aboard the Deep Space Climate Observatory (DSCOVR) spacecraft are compared with a set of radiative transfer-derived lookup tables for the EPIC filter transmission functions and a wide range of ozone values to retrieve ozone with a maximum resolution of 18 km at the sub-satellite point [2]. EPIC provides total column ozone in level 2 and level 4 products and tropospheric column ozone in level 4 products. Both EPIC Ozone products [2] are available at the Atmospheric Science Data Center (ASDC) at NASA Langley Research Center [3, 4]. Pandora spectrometer instrument measures columnar amounts of trace gases in the atmosphere. These gases (O3, NO2, CH2O) absorb light from the sun at specific wavelengths in the ultraviolet-visible spectrum [5]. Using the theoretical solar spectrum as a reference, Pandora determines trace gas amounts using differential optical absorption spectroscopy (DOAS). Pandora ozone retrievals are available from the Pandonia Global Network [6]. Pandora data from North American major metropolitan areas, New York, NY, Washington DC, Los Angeles, CA, and Mexico City. Tropospheric Ozone Lidar Network (TOLNet) was established in 2012 to provide high spatiotemporal observations of tropospheric ozone to (1) better understand physical processes driving the ozone budget in various meteorological and environmental conditions and (2) validate the tropospheric ozone measurements of space-borne missions [7]. TOLNet data are available at ASDC [8]. While EPIC provides global coverage of ozone retrievals several times daily, temporal resolution may miss some features in daily ozone variations. Ground-based sensors such as Pandora spectrometers and TOLNet lidars provide better temporal resolution while missing continuous spatial coverage. The forthcoming ozone retrieval from the TEMPO mission [9] will provide better spatial and temporal coverage of air quality (including ozone) over North America. This study investigates whether EPIC ozone products can detect diurnal air quality variations and compare ozone temporal development with retrieval by ground-based instruments.

diurnal ozone emissions, DSCOVR EPIC, PANDORA, spa↗